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Subversion or exacerbation of antigen-presenting cells ( APC ) death modulates host/pathogen equilibrium . We demonstrated during in vitro differentiation of monocyte-derived macrophages and monocyte-derived dendritic cells ( DCs ) that HIV sensitizes the cells to undergo apoptosis in response to TRAIL and FasL , respectively . In addition , we found that HIV-1 increased the levels of pro-apoptotic Bax and Bak molecules and decreased the levels of anti-apoptotic Mcl-1 and FLIP proteins . To assess the relevance of these observations in the context of an experimental model of HIV infection , we investigated the death of APC during pathogenic SIV-infection in rhesus macaques ( RMs ) . We demonstrated increased apoptosis , during the acute phase , of both peripheral blood DCs and monocytes ( CD14+ ) from SIV+RMs , associated with a dysregulation in the balance of pro- and anti-apoptotic molecules . Caspase-inhibitor and death receptors antagonists prevented apoptosis of APCs from SIV+RMs . Furthermore , increased levels of FasL in the sera of pathogenic SIV+RMs were detected , compared to non-pathogenic SIV infection of African green monkey . We suggest that inappropriate apoptosis of antigen-presenting cells may contribute to dysregulation of cellular immunity early in the process of HIV/SIV infection . Monocytes originating from the bone marrow are released into peripheral blood , where they circulate for several days before entering tissues , and replenish tissue macrophage populations in the steady state . Monocytes constitute a considerable systemic reservoir of myeloid precursors . Monocytes exhibit developmental plasticity , with the capability of differentiating into either macrophages or dendritic cells ( DCs ) in vitro depending on the cytokine milieu . They can enter in lymphoid tissues during inflammation and give rise to macrophages and inflammatory DCs [1] , [2] , [3] . Classical DCs represent a distinct lineage of myeloid cells that are also present in the blood and can migrate into the tissues [3] . Mononuclear phagocytes are critical for both innate and adaptive immunity . Recruited to inflammatory sites , cDCs , inflammatory DCs and macrophages play a critical role in the protection against pathogens [3] , [4] , [5] , [6] . Mononuclear phagocytes and DCs which express CD4 receptor and chemokine co-receptors represent important cellular targets for human immunodeficiency virus type-1 ( HIV-1 ) . Circulating monocytes can be latently infected and productive infection can be initiated during differentiation into macrophages [7] , [8] . Mononuclear phagocytes are rendered defective specifically by the envelope glycoprotein that impairs maturation and cytokine secretion [9] , [10] . This contributes to the development of immune deficiency observed during HIV infection [11] , [12] , [13] , [14] . The most striking feature of AIDS is the increased death and progressive depletion of CD4+ T lymphocytes which leads to immunodeficiency [15] . CD4+ T cells from HIV-infected individuals and SIV-infected rhesus macaques are more sensitive to undergo apoptosis due to the effects of death-receptors [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] . Moreover , in the absence of viral replication , HIV or SIV primes CD4+ T cells for apoptosis in vitro [25] , [26] , [27] . In contrast , the impact of HIV on apoptosis of monocytes and DCs has not been extensively studied . Monocytes , but not macrophages , are prone to undergo apoptosis after death-receptor ligation [16] , [28] , [29] , [30] , [31] . Death receptors include Fas/CD95 , TRAIL-Receptor , and TNF-Receptor . The engagement of death-receptors by their counterparts , FasL , TRAIL and TNF , either in soluble form or at the membrane surface of the cells , induce death-signaling cascades . The molecular ba . sis of resistance to death-receptors-mediated apoptosis involves FLIP ( cellular-FLICE-inhibitory protein expressed during differentiation of APCs [31] , [32] , [33] ) , an inhibitor of the DISC ( death-inducing signaling complex ) [34] . Moreover , apoptosis initiated by growth factor deprivation can be prevented by a decoy-receptor that blocked Fas and FasL interaction [31] , [35] , [36] , and mice carrying functional mutations of Fas-FasL displayed elevated monocytic cell counts [37] . In addition , to the extrinsic pathway that involves death-receptors and their counterparts , apoptosis regulation in mononuclear phagocytes includes also the intrinsic pathway . Thus , among the anti-apoptotic members , Mcl-1 predominates in differentiated cells [38] . Mitochondrial outer membrane integrity is highly controlled , primarily through interactions between pro- and anti-apoptotic of the members of the Bcl-2 protein family . On activation , Bax and Bak proteins undergo extensive conformational changes leading to mitochondria permeabilization and cell death [39] . Subversion of monocyte apoptosis by intracellular bacteria or parasites is used by pathogens to favor their own replication and dissemination within the host when death is inhibited [40] , [41] , [42] , [43] , [44] , [45] , [46] . In contrast , massive cell death of infected macrophages induced by the Ebola virus contributes to pathogenesis by abolishing innate immunity [47] . Several viral infections are also associated with the death of DCs [45] , [48] , although DCs , unlike monocytes , are mostly resistant to FasL-induced cell death [33] , [49] , [50] , [51] , [52] . Differentiated macrophages infected by HIV in vitro are more resistant to TRAIL-mediated cell death triggered by the envelope protein [53] whereas another report suggests that HIV-infected macrophages are more prone to undergo apoptosis [54] . In the peripheral blood of chronically HIV-infected individuals and SIV-infected rhesus macaques ( RMs ) , reduced numbers of DCs are found [55] , [56] , [57] , [58] , [59] , [60] , [61] consistent with increased death of those cells [62] , [63] , [64] . Furthermore , in chronically SIV-infected RMs , massive turnover of peripheral monocytes undergoing apoptosis have been reported [65] . In viremic HIV-infected individuals it has been shown that both spontaneous and IFN-ã-induced monocyte cell death are elevated compared to controls [66] although another report describes monocytes resistant to cell death , associated with antiapoptotic gene profiles [67] . However , little information exists on the precise molecular mechanisms involved and only few studies have assessed these processes early after infection . Indeed , an increasing amount of evidence suggests that the acute phase dictates the rate of progression towards AIDS . Experimental infection of RMs of Chinese origin is an extremely valuable model to investigate these early events [22] , [68] , [69] , [70] , [71] . The aims of the present study were to determine whether HIV/SIV infection early after viral exposure sensitizes mononuclear phagocytes for apoptosis and to elucidate the molecular mechanisms behind the process . We assessed the relevance of apoptosis inducing processes during the acute phase of pathogenic lentiviral infection of RMs . We demonstrated that in vitro and in vivo , monocytes and DCs exposed to HIV/SIV are sensitized to death-receptors ligation-mediated cell death . Among death-ligands , TRAIL and FasL were the most potent at promoting apoptosis of monocytes and DCs , respectively . Lower amounts of FLIP and Mcl-1 and an increase in the levels of the active form of Bax and Bak proteins were found . A broad caspase inhibitor prevented cell death and increased the number of TNF-α productive mononuclear cells . Thus , the inappropriate death of circulating mononuclear phagocytes during the acute phase could favor the development of a state of immunodeficiency . Blood monocytes are non-cycling , non-proliferating cells incapable of supporting viral replication . Indeed , establishment of productive infection coincides with entry into G1/S phase of the cell cycle [72] , and GM-CSF is one of the main cytokines that promotes and sustains productive infection [7] , [8] , [73] , [74] , [75] . We infected monocyte-derived macrophages ( MØ ) - and monocyte-derived DCs ( immature DCs ) during differentiation . One day after the process of differentiation was initiated , with either GM-CSF and IL-6 for MØ or GM-CSF and IL-4 for DCs , the R5 HIV-1 tropic strain , HIV-1BaL was added to simulate the presence of HIV-1 during the maturation process . This contrasts with the addition of virus at the end of the differentiation process utilized in most , if not all , published studies [53] , [76] , [77] . After 5 days , we assessed the percentage of infected MØ and DCs based on intracellular p24 staining by flow cytometry . As expected , we found that the percentage of MØ infected by the R5 tropic strain HIV-1BaL was higher than DCs ( Figure 1A ) . The percentage of HIV-infected MØ varied ( 40%±7 ) among individual preparations , whereas DCs from the same individuals displayed less than 3%±1 of infected cells , consistent with previous reports [13] , [78] . To confirm intracellular staining of p24 antigen , the cells were lysed and western blots performed to detect the profile of viral antigens , using sera from HIV-infected individuals . In MØ , we observed a typical profile displaying both envelope glycoprotein and gag protein , whereas none of these bands were clearly observed in DCs ( Figure 1B ) . We then assessed the capacity of MØ and DCs to produce cytokines and express co-stimulatory molecules in response to LPS and IFN-γ . We found that activated-MØ as well as activated-DCs , incubated in the presence of HIV-1 , secreted less pro-inflammatory cytokines such as IL-6 , IL-8 and TNF-α as compared to uninfected cells . No difference was observed for IL-1β secretion ( Figure 1C ) . Moreover , stimulation with LPS and IFN-γ induced lower expression of the co-stimulatory molecule CD86 ( Figure 1D , E ) and the maturation marker CD83 ( data not shown ) , at the surface of HIV-infected cells as compared to uninfected cells ( CD86 mean expression , MØ: 350±150 vs 1090±230; DCs: 400±220 vs 1570±230 ) . Thus , HIV infection during the process of APC differentiation impacted cytokine secretion and cellular maturation . We then examined whether MØ and DCs were more prone to die at day 5 post-infection with HIV-1BaL . After stimulation with LPS and IFNγ , we observed a significant increase in the percentage of apoptotic cells from HIV-infected culture as compared to non-infected cells ( MØ , 55%±7 vs 31%±3 . 8 , p<0 . 01; DCs , 36%±7 vs 16%±3 . 9 , p<0 . 01 ) . No major difference was observed after stimulation of uninfected cells ( Figure 2A , B ) . The extrinsic apoptotic pathway involves members of the death-receptor family including CD95 ( Fas ) , TNF-R and DR4/DR5 ( Trail-R1/R2 ) [79] . Upon ligation of these death-receptors by their ligands , the association of the adaptor molecule FADD with the initiator caspases forms a death-inducing signaling complex ( DISC ) leading to apoptosis [80] . We assessed whether MØ and DCs in the presence of HIV-1BaL are sensitive to death-receptor ligands including TNF-α , TRAIL and FasL . Actinomycin D ( Act D ) was used as a positive control for cell death . First , both uninfected and HIV-infected MØ ( 51±6% and 62±7% , respectively ) were more sensitive to undergo apoptosis in response to TNF-α in comparison with the medium alone ( 30±4% and 31±5% , respectively ) whereas no similar effect was observed on DCs ( Figure 3A , B ) . Second , MØ infected with HIV-1BaL were more prone to die in response to TRAIL as compared to non-infected cells ( 60±5% versus 36±6% ) ( Figure 3A ) but no difference was observed for FasL ( 38±4% versus 41±6% ) . Finally , HIV-1 infection increased the sensitivity of DCs to die spontaneously ( 20±4% uninfected versus 31±6% in infected DCs ) and after FasL-ligation ( 64±7% versus 31±6% in medium alone ) but not to the binding of TRAIL ( 32±6% ) ( Figure 3B ) . Apoptosis was dependent on the amount of death ligands ( Figure 3C ) . In order to determine if viral replication was necessary for sensitization to apoptosis , we treated the cells with ddI ( 5 µM , a dose that blocks viral replication in MØ; <5% of p24+ ) . Our studies showed that in the presence or absence of ddI , both MØ and DCs remain sensitive to TRAIL and FasL , respectively ( Figure 3D ) . Furthermore , we assessed whether stimulation with LPS/IFN-γ-mediated apoptosis may be modulated by antagonists to death ligands using decoy receptors . We demonstrated that decoy receptors of TNF ( TNF-R1 ) , and TRAIL ( TRAIL-R2/TRAIL-R1 ) , reduced monocyte cell death-mediated by LPS/IFN-γ stimulation , whereas decoys receptors of Fas ( Fas-Fc ) and TNF ( TNF-R1 ) reduced DCs cell death ( Figure 3E ) . Thus , despite the fact that soluble TNF-α has no effect on DCs , TNF-R1 partially inhibits cell death . Altogether , these results indicated that HIV induces APC apoptosis after death-receptors ligation . Since cells were more sensitive to undergo apoptosis , we next assessed whether this effect was related either to a modulation in the expression of death-receptors or in the regulation of the signaling pathway . Although , MØ and DCs exhibited a greater sensitivity to die in the presence of death ligands , we did not observe any modulation of death-receptor expression , including TRAIL-R1 and –R2 and Fas/CD95 on cells infected with HIV-1Ba-L compared to uninfected cells ( data not shown ) . The molecular basis of resistance to death-receptors-mediated apoptosis involves the expression of FLIP ( cellular-FLICE-inhibitory protein ) , which is an inhibitor of the DISC ( death-inducing signaling complex ) [34] , and is expressed during differentiation of APCs [31] , [32] , [33] . Therefore , we analyzed the expression of FLIP in HIV-infected MØ and DCs . We observed that FLIP expression is detectable by western blot at day 5 in both uninfected MØ and DCs but decreased in HIV-infected cells ( Figure 4A ) . Thus , the amount of FLIP decreased by 57%±4 in MØ and 46%±5 in DCs following HIV infection ( Figure 4B ) . Altogether , our data suggest that HIV-1 infection increased the propensity of mononuclear phagocytes to undergo apoptosis in response to death-ligands , possibly due to a decrease in the amount of FLIP . This process occurred independently of any modulation of death receptor expression . The molecular basis of macrophage resistance to apoptosis includes the expression of the anti-apoptotic Bcl-2 family members , among which Mcl-1 predominates in differentiated cells [38] . In the absence of growth receptor engagement , Mcl-1 is degraded by the ubiquitin-proteasome pathway [81] , [82] , [83] or cleaved by proteases [84] , [85] . We found a 50% decrease in expression of Mcl-1 protein in infected-MØ , which was not observed in DCs ( Figure 4A ) . In addition , SDS-PAGE analysis revealed that Mcl-1 migrated as a doublet suggesting the presence of phosphorylated Mcl-1 , primed by GSK-3 , on threonine 163 . This phosphorylated form undergoes accelerated degradation [81] , [83] . In HIV-infected MØ , this change in MCL isoforms was clearly observed compared to uninfected cells , whereas no difference was observed for DCs ( Figure 4A ) . Additional bands of approximately 34 KDa on western blots probed with Mcl-1 antibody were also detected ( Figure 4A ) . These product bands correspond to different translational products ( Mcl-1S/ΔTM versus Mcl-1Exon-1 ) . It is important to note that Mcl-1Exon-1 is pro-apoptotic [38] . The amount of Mcl-1Exon-1 protein was clearly enhanced in DCs cultured in the presence of HIV-1BaL ( fold increase 2 . 1 ) as well as in MØ ( fold increase 1 . 7 ) ( Figure 4B ) . Members of the Bcl-2 protein family , in particular Bax and Bak proteins play a critical role in controlling apoptosis [39] . To assess the early commitment of Bax and Bak activation , we subfractionated the cells to isolate a mitochondria-enriched fraction . At day 5 of culture , we observed higher amounts of Bax and Bak proteins within the enriched mitochondrial fraction derived from HIV-1BaL-infected MØ and DCs compared to uninfected cells ( Figure 4C and D ) . Membrane insertion of Bax and Bak supported a dynamic model in which mitochondria is a central sensor . Taken together , these results suggest that HIV shifts the balance towards pro-apoptotic molecules rendering APCs more sensitive to death stimuli . Early events during the acute phase of SIV infection are critical in determining the onset of AIDS , we therefore investigated APC death in RM during acute SIV infection . We analyzed the percentage of monocytes CD14+ that were infected compared to CD4+ T cells in peripheral blood ( the purity was more than 98% for HLA-DR+CD14+ cells as well for CD4+ T cells after cell sorting ) . HIV-1 has been reported to be isolated from CD14+ monocytes of patients under HAART , indicating that monocytes are competent for HIV infection [86] . Moreover , because monocytes circulate in the blood for only a few days before differentiating into macrophages in tissues , they represent important cells in viral dissemination . The frequency of monocytes and CD4+ T cells harboring proviral DNA was quantified using a nested SIV PCR assay in limiting dilutions of purified cells [22] . The frequency of SIV-DNA positive monocytes increased and peaked at days 11–14 ( day 11 , mean: 3 . 8±1 . 3; day 14 , 3 . 6±1 . 2 of monocytes were infected ) which is equivalent to the frequency found in CD4+ T cells ( day 11 , mean: 4 . 8±2 . 1 and day 14 , 1 . 4±0 . 4 ) ( Figure 5 ) . Thereafter , the frequencies of SIV-infected monocytes decreased ( mean: 0 . 5±0 . 18 ) . The dynamics of SIV-DNA is consistent with viral load ( viral RNA ) measured in the plasma ( data not shown ) [22] . Unlike monocytes and CD4+ T cells , the frequency of SIV-DNA in myeloid DCs ( HLA-DR+CD11+ ) was extremely low during the acute phase of infection ( day 11 , mean: 0 . 015±0 . 004; day 14 , 0 . 015±0 . 008 of DCs were infected ) consistent with a previous report [87] . We quantified the percentages of dying HLA-DR+CD3−CD20− and CD4+ T cells before and after incubation with death-ligands by monitoring FITC-labeled annexin V . As previously shown [21] , [25] , [88] , CD4+ T cells derived from SIV-infected RMs at the peak of viral replication ( day 14 ) were prone to undergo apoptosis spontaneously and after FasL ligation as compared to Trail or TNF-α ligation ( Figure 6A and D ) and consistent with other studies [89] . Unlike CD4+ T cells , among death-ligands , TRAIL and FasL were the most potent ligands to promote apoptosis of HLA-DR+CD3−CD20− at day 14 ( Figure 6B , C and D ) . We then demonstrated that early after infection both monocytes ( HLA-DR+CD14+ ) and DCs ( Lin−HLA-DR+CD11c+CD123− ) are more prone to undergo apoptosis spontaneously ( Figure 6E ) . Thereafter , the levels of apoptosis decreased to reach those observed before infection ( Figure 6E ) . In non pathogenic SIV-infected African green monkeys ( AGM ) , apoptosis of CD4 and of HLA-DR+CD3−CD20− cells at day 14 was similar to the level observed from healthy monkeys ( Figure 6F ) consistent with the absence of apoptosis reported in this non pathogenic primate model , despite a similar level of viral replication comparable to RMs [23] , [70] , [88] . The biologically active forms of death ligands include both a soluble and a membrane bound form . Therefore , we quantified the presence of death ligands in the sera of SIV-infected monkeys . We found , concomitant with the increase of cell death in RMs , higher levels of FasL two weeks post-infection ( Figure 6G ) . In contrast , we did not observe any increase in the levels of FasL in SIV-infected AGM ( Figure 6G ) . We have reported during the acute phase the absence of TNF-α detection in the sera of both SIV-infected species [90] , [91] . Although , we were unable to detect soluble TRAIL in the sera of SIV-infected monkeys due to the unavailability of appropriate reagents for its detection in non-human primates ( data not shown ) , it has been reported that there is increased expression of Trail mRNA in SIV-infected RMs [92] . To assess the impact of soluble and membrane forms of death ligands , we investigated whether apoptosis of monocytes and DCs from SIV-infected RM may be modulated by antagonists to death ligands using decoy receptors . We demonstrated that decoy receptors of TNF ( TNF-R1 ) and TRAIL ( TRAIL-R2 but not TRAIL-R1 ) , and to a lesser extent decoy receptor of Fas ( Fas-Fc ) , reduced monocyte cell death , whereas decoys receptors of Fas and TNF ( TNF-R1 ) reduced DCs cell death ( Figure 6H ) . Interestingly , despite the fact that soluble TNF-α has no effect , antagonist antibodies partially inhibited death suggesting that TNF-α at the cell surface may participate in the death of APCs [93] . These results suggest that apoptosis of mononuclear phagocytes involved death-receptors and their counterparts . In order to analyze the apoptotic pathways in monocytes , positive selection of CD14+ cells was performed from healthy and SIV-infected RMs . Western blots probed with specific antibodies to FLIP revealed that monocytes from SIV-infected RMs displayed lower amounts of FLIP ( Figure 7A ) , as compared to healthy RMs . Thus , the absence of FLIP is consistent with the increase sensitivity of these cells to undergo apoptosis after ligation of death receptors . Moreover , we found that monocytes from SIV-infected RMs had lower amounts of Mcl-1 ( Figure 7A ) . In one SIV-infected RM , we also detected an increased amount of the proapoptotic form of Mcl-1Exon-1 . To assess the expression of active form of Bax and Bak proteins in APCs from healthy and SIV+RMs , we used specific antibodies that detect conformational changes as previously described [25] . In comparison to CD4+ T cells , we found that 20%±6 and 30%±11 of monocytes from SIV-infected RMs at day 14 express the active form of the pro-apoptotic Bax and Bak molecules respectively as compared to monocytes from non-infected RMs ( less than 11%±4 ) . Similar data were observed in DCs although to a lesser extent ( Figure 7B and 7C ) . Thus , our results indicate that monocyte and DCs are engaged in a process leading to mitochondria damage supporting our observation that these cells are more prone to undergo apoptosis during the acute phase . Furthermore , we used a broad caspase inhibitor and demonstrated that by blocking caspase activation , cell death of APCs was also prevented ( Figure 7D ) . We also demonstrated that the addition of caspase inhibitor led to an increase in the number of cells expressing TNF-α after stimulation with LPS + IFN-γ stimulation ( Figure 7E ) . Altogether , our data demonstrated a critical role of both the intrinsic and extrinsic apoptotic pathways in controlling APC death during the acute phase of SIV-infection . We demonstrate that monocytes and DCs are more prone to undergo apoptosis in response to death-receptor ligation after in vitro infection with HIV or ex vivo from SIV-infected RMs . In addition , our data show that HIV/SIV infection is associated with an increase in the active forms of the pro-apoptotic molecules Bax and Bak and with a decrease in the anti-apoptotic Mcl-1 and FLIP proteins in both cell types . Thus , these results suggest that both the extrinsic and intrinsic pathways are involved in the death of APCs during HIV/SIV infection . Broad inhibition of caspase activation using a synthetic peptide prevented this death and increased the number of TNF-α productive mononuclear cells . Circulating monocytes are essential not only to replenish the pool of tissue macrophage populations but also may differentiate into inflammatory DCs in the tissues following microbial infection . Because peripheral monocytes and DCs represent crucial populations for the control of pathogens , this enhanced susceptibility to die by apoptosis in the presence of death ligands could have a major impact on the establishment of the adaptative immune response early after infection . Interestingly , other persistent viral infections such as lymphocytic choriomeningitis virus ( LCMV ) and measles virus ( MV ) , which are associated with a generalized immune suppression in their natural hosts , also induce death of accessory cells early after infection [94] , [95] . Our results also demonstrated in vitro that incubation of monocyte-derived MØ and DCs with HIV during differentiation not only increased the susceptibility of these cells to undergo apoptosis but also impaired their maturation and their capacity to produce inflammatory cytokines after stimulation . Their down modulation could have an impact on the hosts' ability to mount an effective SIV-specific immune response . Our results showed abnormal early death of APCs was associated with AIDS . The low level of infection of DCs suggests that apoptosis is not necessarily associated with productive infection . Moreover , during the acute phase , the percentage of monocytes prone to undergo apoptosis ( and expressing active form of Bax and Bak ) was higher than the frequency of SIV DNA+ cells . Our data revealed that also in vitro HIV primes both monocytes and DCs to undergo apoptosis in response to death ligands despite the presence of an inhibitor of viral replication , ddI . In a similar manner , the non pathogenic-primate model suggests that despite intense viral replication during the acute phase [70] , APCs are not prone to undergo apoptosis . Altogether , these results point to the involvement of indirect mechanisms leading to cell death . This may suggest that triggering of TLRs or other pattern recognition receptors such as a mannose C-type lectin receptor , by HIV could lead to the observed changes in the sensitivity of these cells to undergo apoptosis without active replication [96] . We and others have previously reported the critical role of cytokines determining the sensitivity of monocytes to undergo apoptosis [28] , [29] , [97] , [98] . Among them IL-10 has been shown to be a potent cytokine to induce monocyte death [98] but also increases membrane-bound TNF-α[99] , and the expression of CCR5 , a co-receptor for SIV [100] . Recently , it has been reported that IL-10 results in the rapid elimination of mature DCs by NK cells but is associated with the accumulation of DCs having an immature phenotype [101] . Blockade of IL-10 , in addition to blockade of PD-1 signaling has been suggested as a means to restore anti-viral T cell responses in chronic LCMV infection [102] and to prevent apoptosis [16] , [103] , [104] , [105] , [106] . Therefore , whether a therapy based on neutralizing IL-10 antibody would be able to prevent monocyte cell death as well DCs in vivo remains an open question . During inflammation , or in the presence of microbial antigens , monocytes become resistant to death associated with increased expression of anti-apoptotic molecules [28] , [29] , [31] , [32] , [107] , [108] , but resistance to death is counteracted by interferons ( IFNs ) . Indeed , type I IFN production associated with bacterial pathogens such as Listeria monocytogenes [109] or in combination with LPS [110] induced apoptosis of APCs . We found that in vitro stimulation with LPS + IFN-γ induced the death of HIV-infected APCs as compared to uninfected cells . In HIV-infected patients , a recent study has reported increased levels of monocyte apoptosis after IFN-γ stimulation [66] . Interestingly , bacterial translocation associated with AIDS has been correlated with activation of innate immunity and especially with increased plasma levels of IFNα[111] . Moreover , in pathogenic primate models of SIV infection , increased levels of type I IFN related to the recruitment of pDCs in the lymph nodes ( LN ) have been reported [91] and associated with disease progression [112] . We found that mononuclear cells were abnormally sensitive to die through apoptosis concomitant with the peak of type I IFN production [91] . Thus , the presence of type I/II IFN may result in increased sensitivity of APCs to undergo apoptosis during the acute phase . After the peaks of viral replication and type I IFN , our data revealed a decrease in the susceptibility of these cells to undergo apoptosis . In chronically HIV-infected persons , a resistance to undergo apoptosis was reported [67] . Therefore , these results together reinforce the idea that death of APCs early after infection contributes to immune deficiency and further progression to AIDS . Our data clearly demonstrated that in vitro and ex vivo , APCs were more sensitive to undergo apoptosis in response to specific death-ligands . Monocytes were more prone to die after TRAIL binding than FasL , whereas FasL was more efficacious to induce death in DCs . This increased propensity to undergo apoptosis after death-receptor ligation was not related to an increased expression of the death-receptors at the surface of APC's , but was associated with increased levels of FasL in the sera of SIV-infected RMs and not in non-pathogenic SIV-infected AGMs . Of note , FasL levels in plasma of HIV-positive individuals have been reported to be elevated , and correlated with HIV RNA burden [113] , [114] . Elevated levels of TRAIL have also been reported in HIV-infected individuals early after infection [115] , [116] . However , our attempts to measure TRAIL in the sera were unsuccessful due to the absence of available reagents for its detection in monkeys . Whereas the incubation of soluble TNF-α had no effect on the death of APCs from RMs , neutralization of TNF-α reduced death . Biologically active forms of death-ligands include both membrane bound and soluble forms , suggesting that TNF-α can be a co-factor for death-receptor sensitization at the cell surface [93] . Taken together , these results suggest that peripheral blood monocytes and DCs from pathogenic SIV-infected macaques are exposed to death-ligands during the acute phase . Cell death via death receptors can be regulated at different levels , including altered expression of death-ligands or by inhibition of intracellular signaling events . In this context , our results showed that despite death-receptor expression and the presence of death-ligands in the culture , uninfected monocytes and macrophages were resistant to apoptosis indicating that death-ligands and receptors were not sufficient to induce apoptosis . These data are consistent with a model in which infection induced changes in the susceptibility of monocyte and DC populations to undergo apoptosis . The susceptibility of the cells to undergo apoptosis depends on the balance between pro- and anti-apoptotic molecules . We observed a downregulation of FLIP , an inhibitor of the DISC and caspase activation , in HIV-infected MØ- and DCs-derived monocytes . In purified CD14+ monocytes from monkeys , we also found a downregulation of FLIP in SIV-infected RMs as compared to healthy RMs . Moreover , the susceptibility of these cells to undergo apoptosis was also associated with increased expression of the active forms of the pro-apoptotic molecules Bax and Bak . Finally , we demonstrated a reduction in the expression of the anti-apoptotic Mcl-1 proteins but its pro-apoptotic form , Mcl-1Exon-1 , was increased . Thus , our results demonstrated a dysregulation in the balance of pro- and anti-apoptotic molecules , which could contribute to mononuclear phagocyte death . Our results indicated therefore that both the extrinsic and the intrinsic pathways could be closely linked in determining mononuclear cell apoptosis outcome after HIV/SIV infection . In this sense a broad caspase inhibitor prevented cell death . Since monocytes are a heterogeneous population [117] , it remains to be determined whether CD14dimCD16+ monocytes display similar susceptibility to die as CD14+ monocytes during HIV/SIV infection . In conclusion , our findings demonstrate that HIV/SIV infection primes mononuclear cells to undergo apoptosis . Since circulating blood monocytes and DCs extravasate into tissues in response to pathogens , such sensitization to death-receptor mediated apoptosis may be a major factor leading to the defective immune response observed during the acute phase . Taken together , our results highlight the confounding role of apoptosis induction in the physiopathology of HIV/SIV infection associated with the death of mononuclear cells during the acute phase of SIV infection . Thus a strategy aimed at blocking their death could be beneficial in restoring an effective anti-viral response in HIV-infected persons . Ten RMs ( Macaca mulatta ) seronegative for STLV-1 ( Simian T Leukemia Virus type-1 ) , SRV-1 ( type D retrovirus ) , herpes-B viruses , and SIVmac were utilized . RMs were inoculated intravenously with ten 50% animal-infectious doses of the SIVmac251 strain ( provided by AM . Aubertin , INSERM U74 , Strasbourg , France ) . Four AGMs of sabaeus species were experimentally infected with 300 TCID50 of SIVagm . sab92018 strain [70] . All the animal experiments described in the present study were conducted at the Institut Pasteur according to the European Union guidelines for the handling of laboratory animals ( http://ec . europa . eu/environment/chemicals/lab_animals/home_en . htm ) . The protocol was approved by the committee on the ethics of animal experiments of Ile de France ( PARIS 1 , #20080007 ) . All surgery was performed under sodium pentobarbital anesthesia , and all efforts were made to minimize suffering . The frequency of SIV-infected cells was measured by limiting dilution PCR . Cells were isolated from blood and stained with mAbs ( CD3 , CD4 , HLA-DR and CD14 mAbs ) ( BD Biosciences , San Jose , CA ) . Cells were purified by cell sorting ( FACS Vantage , BD Bioscences ) on the basis of their size , granularity and phenotype ( CD14+HLA-DR+CD3−CD20−; CD14−HLA-DR+CD3−CD20− versus CD3+CD4+ ) ; purity exceeded 98% . Purified cells were counted and serially diluted in a constant number of carrier CEMX174 cells as previously described [22] . The proportion of SIV DNA+ cells in purified cells was determined using Poisson law . The limiting-dilution PCR method detected one SIV DNA+ cell in 10 , 000 uninfected cells ( CEMX174 ) validated with SIV-1C cells ( provided by F . Villinger ) , that contain a single provirus of SIVmac251 per cell . Fresh PBMC were isolated by density gradient centrifugation from blood of healthy donors . The blood samples were obtained from the Institut National de la Transfusion Sanguine . Monocytes were obtained by plastic adherence after extensive washing with media to remove non-adherent cells as described [98] . The adherent monocytes were carefully removed from the culture by incubating the plate 30 min at 4°C and use cold PBS and pipetting ( not scraping ) . The purity of the monocytes exceed 90–95% as determined by flow cytometry after cell staining with mAbs CD14 , CD3 , CD20 and HLA-DR . The cells were then incubated in RPMI-1640 supplemented with 10% FCS , 1% glutamine , 1% pyruvate , and 1% antibiotics . Macrophages were derived from monocytes in the presence of GM-CSF ( 10 ng/ml ) and IL-6 ( 5 ng/ml ) ( R&D system ) while dendritic cells were derived in the presence of GM-CSF and IL-4 ( 10 ng/ml ) . At day one , the cells were incubated in the presence of the R5 HIV-1BaL strain ( 100 pg/ml of p24 ) . At day 5 , the cells were stimulated overnight with LPS ( 10 ng/ml ) and IFN-γ ( 103 U/ml ) . Cells were also incubated in the presence or absence of TNF-α , TRAIL and FasL ( 200 ng/ml ) . Fresh PBMC from Non Human primates were isolated by density gradient centrifugation from blood and use to perform the different assays [21] , [25] , [88] . Infections of monocyte-derived MØ and DCs , respectively , were measured by flow cytometry based on the detection of intracellular p24 antigen ( RD1-labeled mAb anti-p24 antigen , KC-57 , Beckman coulter ) after fixation and permeabilization of the cells ( Intraprep permeabilization reagent , Coulter Coultronics ) . Productive HIV infection was also visualized by western blotting that allows detection of the presence of viral antigens in cell extracts . The immunoblots were incubated with sera obtained from a pool of HIV+ infected patients ( kindly provided by F Mamano , Institut Pasteur ) . After treatment with horseradish peroxidase-linked goat anti-human secondary antibodies ( Amersham Biosciences ) , immunoreactive proteins were detected using enhanced chemiluminescence ( ECL+ from GE Healthcare ) using a CCD camera ( GBOX , SYNGENE ) . The frequencies of SIV-infected CD4+ T cells , CD14+ and DCs were measured by limiting-dilution PCR [22] of purified cells by cell sorting ( FACS Vantage; Becton Dickinson Biosciences , Le Pont de Claix , France ) using the positive selection of cells stained with specific antibodies . Purified cells were counted and diluted in series in a constant number of carrier CEM X 174 cells . Cells were directly lysed with TPK buffer ( 10 mM Tris-HCl pH 8 . 3 , 50 mM potassium chloride , 2 . 5 mM magnesium chloride , 0 . 5% Nonidet P-40 , 0 . 5% Tween 20 , 100 µg/ml of proteinase K ) . After 1 h at 56°C , proteinase K was inactivated at 95°C for 10 min . Twenty replicates of limiting dilutions were submitted to a nested PCR . SIV proviral DNA was amplified by nested PCR with SIV251-specific primers surrounding the nef region . After 35 cycles ( 95°C for 30 s , 60°C for 30 s , 72°C for 1 min . ) with the first set of primers , Preco ( 59-CAG AGG CTC TCT GCG ACC CTA C ) and K3 ( 59-GAC TGA ATA CAG AGC GAA ATG C ) , amplified a fragment of 961 base pairs , 10 µl of product was re-amplified ( 30 cycles 95°C for 30 s , 55°C for 30 s , 72°C for 1 min ) with primers K1 ( 59-TGG AAG ATG GAT CCT CGC AAT CC ) and A2 ( 59-GGA CTA ATT TCC ATA GCC AGC CA ) . Nested PCR products were electrophoresed through a 1 . 8% agarose gel . The proportion of infected cells was determined using Poisson law . The limiting-dilution PCR method was able to detect one infected cell in 10 000 uninfected cells ( CEM X 174 ) demonstrated with SIV-1C cells ( provided by F . Villinger ) , which contain a single provirus of SIVmac251 per cell . Supernatants were collected after overnight stimulation and 6 days of culture . IL-1ß , IL-6 , IL-8 , and TNF-α were detected simultaneously by using the human inflammatory cytokine cytometric bead array ( CBA ) kit ( BD Bioscience ) [90] . The CBA working range was 20–5000 pg/ml for each cytokine . Cytokine levels were quantified by flow cytometry according to the manufacturer's directions . For intracellular TNF-α staining , the cells were incubated in the absence or presence of a broad caspase inhibitor Q-VD ( OMe ) -OPH ( 10 µM , MBL biomedical ) , and stimulated with LPS and IFN-γ . After 8 h , the cells were first stained with HLA-DR , CD3 , and CD20 mAbs , washed and then permeabilized , before staining with PE-TNF-α mAbs ( BD Biosciences ) . The number of HLA-DR+CD3−CD20− cells expressing TNF-α was measured by flow cytometry . FasL in the serum was measured using a solid-phase immunoassay ( MBL ) . The assay uses anti-FasL mAbs ( clones , 4H9 and 4A5 ) . The peroxidase substrate was used to quantify FasL and the optical density measured at 450 nm . The concentration was determined using a standard curve based on recombinant FasL . Three distinct ELISA specific for human TRAIL purchased from R&D system , Diaclone and Kamiya Biomedical Company , however , were unable to detect monkey Trail in the sera/plasma . Monocyte-derived MØ and DCs , respectively , cultured in the absence or presence of the R5 HIV-1Bal strain , were then incubated in the absence ( medium ) or presence of LPS ( 10 ng/ml ) plus IFN-γ ( 103 U/ml ) . Cells were then stained with FITC-CD14 , APC-CD11c , PerCP-HLA-DR , and PE-conjugated antibodies to either CD83 ( HB15e ) or CD86 molecules ( FUN-1 ) ( BD Biosciences ) . Five hundred thousand events corresponding to mononuclear cells were acquired using a FACScalibur instrument ( BD Biosciences ) . Fresh PBMC from SIV-infected RMs at different days post-infection were isolated by density gradient centrifugation; apoptosis of monocytes and dendritic cells was determined at 24 h of culture by cell surface staining and with FITC-labeled annexin-V which is an early marker of dying cells detecting both caspase-dependent and -independent cell death programs [118] . The level of apoptosis was determined by flow cytometry as previously described [98] . We also used decoy receptors of Fas ( Fas-Fc ) , TRAIL ( TRAIL-R1-Fc and TRAIL-R2-Fc ) and TNF-α ( TNF-R1-Fc ) at a dose of 10 µg/ml ( Alexis corporation ) as previously described [21] . Cells from SIV-infected RMs and healthy RMs were first labeled for cell surface markers ( APC-HLA-DR , PE-CD14 , Lineage PerCP-CD3/CD20 versus APC-CD11c , PE-HLA-DR and Lineage PerCP-CD3/CD20 ) and then fixed and permeabilized . Cells were then incubated with anti-Bax ( BD Biosciences ) or anti-Bak Abs ( Calbiochem ) as previously described for primates [25] . After washing , FITC-labeled goat anti-rabbit IgG Ab ( Molecular probes ) was added for 30 min at 4°C in the presence of mouse immunoglobulins . Cells were then washed and analyzed by flow cytometry . Pellets of 3×106 monocyte-derived MØ and DCs , respectively , were lysed in Nonidet P-40 buffer ( 1% NP-40 , 50 mM Tris-HCl ( pH 7 . 4 ) , 150 mM NaCl ) containing protease and phosphatase inhibitors . Total lysates were resolved by SDS-PAGE ( 10–20% Tricine gels , Novex ) and transferred to nitrocellulose membranes ( Amersham Biosciences ) . After blocking nonspecific sites for 1 hour at room temperature with 5% nonfat milk and 0 . 2% Tween 20 in phosphate-buffered saline ( pH 7 . 4 ) , the membrane was incubated with rabbit anti-Bak ( Calbiochem , clone 2–14 ) , rabbit polyclonal anti-Bax ( Santa-Cruz , N-20 ) , rabbit anti-Mcl-1 ( S19 , Santa-Cruz ) , or rat anti-FLIP ( DAVE-2 , Alexis Corporation ) . To confirm equal protein loading and transfer , membranes were reprobed with anti-actin monoclonal antibodies ( Sigma ) . After treatment with horseradish peroxidase-linked goat anti-mouse or anti-rabbit secondary antibodies ( Amersham Biosciences ) , immunoreactive proteins were detected using enhanced chemiluminescence ( ECL+ from GE Healthcare ) using a CCD camera ( GBOX , SYNGENE ) . Data are reported as means ± SEM , and groups were compared using Mann-Whitney test ( Prism software , GraphPad , San Diego CA ) . A p value <0 . 05 was considered significant .
Antigen-presenting cells ( APCs ) are critical for both innate and adaptive immunity . They have a profound impact on the hosts' ability to combat microbes . Dysfunction and premature death by apoptosis of APCs may contribute to an abnormal immune response unable to clear pathogens . Circulating blood monocytes exhibit developmental plasticity , with the capability of differentiating into either macrophages or dendritic cells ( DCs ) , and they represent important cellular targets for HIV-1 . We report that HIV infection renders monocytes/macrophages and DCs in vitro more prone to undergo apoptosis and this heightened susceptibility is associated with changes in the expression of anti- and pro-apoptotic molecules . Our results show that during the acute phase of SIV-infection of rhesus macaques , monocytes and DCs are more prone to die by apoptosis . They express lower levels of Mcl-1 and FLIP proteins , two anti-apoptotic molecules , but higher expression of the active form of Bax and Bak , the gatekeepers of the mitochondria , major sensor of the apoptotic machinery . Because the early events are important in the pathogenesis of this disease , early death of APCs should play a major role leading to the defective immune response . Strategies aimed at preventing death of APCs could be beneficial in helping the immune response to fight HIV-1 .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biology" ]
2011
HIV/SIV Infection Primes Monocytes and Dendritic Cells for Apoptosis
Recent computational models of sign tracking ( ST ) and goal tracking ( GT ) have accounted for observations that dopamine ( DA ) is not necessary for all forms of learning and have provided a set of predictions to further their validity . Among these , a central prediction is that manipulating the intertrial interval ( ITI ) during autoshaping should change the relative ST-GT proportion as well as DA phasic responses . Here , we tested these predictions and found that lengthening the ITI increased ST , i . e . , behavioral engagement with conditioned stimuli ( CS ) and cue-induced phasic DA release . Importantly , DA release was also present at the time of reward delivery , even after learning , and DA release was correlated with time spent in the food cup during the ITI . During conditioning with shorter ITIs , GT was prominent ( i . e . , engagement with food cup ) , and DA release responded to the CS while being absent at the time of reward delivery after learning . Hence , shorter ITIs restored the classical DA reward prediction error ( RPE ) pattern . These results validate the computational hypotheses , opening new perspectives on the understanding of individual differences in Pavlovian conditioning and DA signaling . Lesaint and colleagues [1] recently proposed a new computational model—the “STGT model” ( for sign tracking and goal tracking ) —which accounts for a large set of behavioral , physiological , and pharmacological data obtained from studies investigating individual variation in Pavlovian conditioned approach behavior [2–8] . Most notably , the model can account for recent work by Flagel and colleagues ( 2011 ) that has shown that phasic dopamine ( DA ) release does not always correspond to a reward prediction error ( RPE ) signal arising from a classical model-free ( MF ) system [9] . In their experiments , Flagel and colleagues trained rats on a classical autoshaping procedure , in which the presentation of a retractable-lever conditioned stimulus ( CS; 8 s ) was followed immediately by delivery of a food pellet ( unconditioned stimulus [US] ) into an adjacent food cup . In procedures like this , some rats , known as sign trackers ( STs ) , learn to rapidly approach and engage the CS lever , whereas other rats , known as goal trackers ( GTs ) , learn to approach and enter the food cup upon presentation of the CS lever . Although both sign and goal trackers learn the CS-US relationship equally well , it was elegantly shown that phasic DA release in the nucleus accumbens core ( NAc ) matched RPE signals only in STs [4] . Specifically , during learning in ST rats , DA release to reward decreased , while DA release to the CS increased . In contrast , even though GTs acquired a Pavlovian conditioned approach response , DA release to reward did not decline , and CS-evoked DA was weaker . Furthermore , administration of a DA antagonist blocked acquisition of the ST conditioned response but did not impact the GT conditioned response [4 , 10] . Several computational propositions have argued that these data could be interpreted in terms of different contributions of model-based ( MB ) —with an explicit internal model of the consequences of actions in the task—and MF—without any internal model—reinforcement learning ( RL ) in GTs and STs during conditioning [1 , 11] . Nevertheless , only the STGT model predicted that manipulating the intertrial interval ( ITI ) should change DA signaling in these animals: the model suggests that GTs revise the food cup value multiple times during and in between trials during the 90-s ITI . During the trial , the food cup gains value because reward is delivered; however , visits to the food cup during the ITI do not produce reward , thus reducing the value assigned to the food cup . This mechanism prevents the progressive transfer of reward value signal in the model from US time to CS time and hence explains the absence of DA RPE pattern in goal trackers . This aspect of the model predicts that decreasing the ITI should reduce the amplitude of US DA burst ( i . e . , less time to negatively revise the value of the food cup and reduce the size of the RPE ) and that higher food cup value should lead to an increase in the tendency to GT in the overall population . In contrast , increasing the ITI should have the opposite effect . That is , lengthening the ITI and therefore increasing the number of nonrewarded food cup entries should increase the amplitude of US DA burst ( i . e . , more time to negatively revise the value of the food cup during the ITI and increase the size of the RPE ) and lower the value of the food cup , leading to a decreased tendency to GT and an increase tendency to ST . The latter would be accompanied by a large phasic DA response to the highly salient lever CS , as previously observed in STs [4] . Here , we tested these predictions by recording DA release in the NAc using fast-scan cyclic voltammetry ( FSCV ) during 10 d of Pavlovian conditioning in rats that had either a short ITI of 60 s or a long ITI of 120 s . DA release was recorded from NAc ( S1B–S1E Fig ) during a standard Pavlovian conditioned approach behavior task ( S1A Fig ) for 10 d . Each trial began with the presentation of a lever ( CS ) located to the left or right side of a food cup ( counterbalanced ) for 8 s . Upon the lever’s retraction , a 45-mg sucrose pellet was delivered into the food cup , independent of any interaction with the lever . Each behavioral session consisted of 25 trials presented at a random time interval of either 60 s ( n = 7 rats ) or 120 s ( n = 12 rats ) . To quantify the degree to which rats engaged in sign- versus goal-tracking behavior , we used the Pavlovian Conditioned Approach ( PCA ) index [12] , which comprised the average of three ratios: ( 1 ) the response bias , which is ( Lever Presses − Food Cup Entries ) / ( Lever Presses + Food Cup Entries ) , ( 2 ) the probability ( P ) difference , which is ( Plever − Preceptacle ) , and ( 3 ) the latency index , which is ( x¯ Cup Entry Latency − x¯ Lever Press Latency ) / 8 . All of these ratios range from −1 . 0 to +1 . 0 ( similarly for PCA index ) and are more positive and negative for animals that sign track and goal track , respectively . All behavioral indices were derived from sessions during which DA was recorded . For the initial analysis described in this section , behavior and DA were examined across all sessions; the development of behavior and DA over training is examined in later sections . The distributions of behavioral session scores are shown in Fig 1A–1D for each group . As predicted , rats with the 120-s ITI tended to sign track more , whereas rats with the 60-s ITI tended to goal track more . Across all behavioral indices ( i . e . , response bias , probability , latency , PCA ) , the mean distributions were positive ( biased toward sign tracking ) and significant from sessions for rats in the 120-s ITI group ( Fig 1A–1D , left; Wilcoxon; μ’s > 0 . 17 , p < 0 . 05 ) . Opposite trends were observed in the 60-s ITI group in that all distributions were negatively shifted from zero ( Fig 1A–1D , right; Wilcoxon; response bias: μ = −0 . 06 , p = 0 . 06; lever probability: μ = −0 . 03 , p = 0 . 58; PCA index: μ = −0 . 11 , p = 0 . 097 ) ; however , only the shift in the latency difference distribution reached significance ( Fig 1C , right; Wilcoxon; μ = −0 . 10; p < 0 . 05 ) . Direct comparisons between 60-s and 120-s ITI groups produced significant differences across all four measures ( Wilcoxons; p < 0 . 01 ) . Thus , we conclude that lengthening the ITI increased sign-tracking behavior , as predicted by the STGT model [1 , 13] . Notably , the degree of sign/goal tracking within the 60-s ITI group was highly dependent on when behavior was examined during the 8-s CS period . This is illustrated in Fig 1G and Fig 1H , which show percent beam breaks in the food cup ( solid lines ) and lever pressing ( dashed lines ) over the time of the trial . Consistent with the ratio analysis described above ( Fig 1A–1D ) , rats in the 120-s ITI group ( red ) showed sustained pressing ( red dashed ) that started shortly after lever extension and persisted throughout the 8-s CS period , while showing no increase in food cup entries ( red solid ) after CS presentation ( Fig 1G , red solid versus dashed ) . Although it is clear that rats in the 120-s ITI group sign track more than goal track during the CS period , the relationship between lever pressing and food cup entry was far more dynamic during sessions with 60-s ITIs ( Fig 1G; blue ) . During 60-s ITI sessions , rats would briefly enter the food cup for approximately 2 s immediately upon CS presentation ( Fig 1G , solid blue ) , before engaging with the lever ( Fig 1G , dashed blue ) . As a result , lever pressing was delayed in the 60-s ITI group relative to the 120-s ITI group ( Fig 1G and 1H; blue versus red dashed ) . This suggests that the goal-tracking tendencies described above during the entire 8-s CS period were largely due to the distribution of behaviors observed early in the CS period . To quantify this observation , we recomputed the PCA index using either the first or the last 4 s of the 8-s CS period . For the 120-s ITI group , the PCA index was significantly shifted in the positive direction during both the first and last 4 s of the cue period ( i . e . , more sign tracking; Fig 1E and 1F , left; Wilcoxon; μ’s > 0 . 16; p < 0 . 05 ) . For the 60-s ITI group , the PCA index was significantly shifted in the negative direction during the first 4 s ( i . e . , more goal tracking; Fig 1E , right; Wilcoxon; μ = −0 . 16; p < 0 . 05 ) but not significantly shifted during the last 4 s ( Fig 1F , Wilcoxon; μ = 0 . 01; p = 0 . 81 ) . Interestingly , this part of the results goes beyond the STGT model , which simplifies time by considering a single behavior/action during that period . To further demonstrate sign- and goal-tracking tendencies over the 8-s cue period and the differences between groups , we simply subtracted 60-s ITI lever pressing and food cup entries from 120-s ITI lever pressing ( Fig 1I; orange ) and food cup entries ( Fig 1I; green ) , respectively . Shortly after cue onset , the green line representing the difference between 120-s and 60-s ITI food cup entries dropped significantly below zero . Throughout the cue period ( 8 s ) , there were more contacts with the food cup in sessions with a 60-s ITI compared with the 120-s ITI group ( green tick marks represent differences between 120-s and 60-s ITI across sliding 100-ms bins; t test; p < 0 . 05 ) . For lever pressing ( orange ) , values were constantly higher shortly after the cue for the first half of the cue period ( orange tick marks represent differences between 120-s and 60-s ITI across sliding 100-ms bins; t test; p < 0 . 05 ) , indicating that there were more contacts with the lever in sessions with a 120-s ITI compared with the 60-s ITI group early in the cue period . The behavioral data described above globally support model predictions that increasing and decreasing the ITI would produce more and less sign tracking , respectively . Nevertheless , they also pave the way for improvements of the model by showing a rich temporal dynamic of behavior during the trial , rather than the single behavioral response per trial simulated in the model . By plotting lever presses and food cup entries over time , we see that sometimes rats initially go to the lever and then go to the food cup , or vice versa . In contrast , the model was designed to account only for the initial action performed by rats . This was sufficient to account for the main results of the present study . Nevertheless , it would be interesting to extend the model to enable it to account for different decisions made sequentially by the same animal during a given trial . Next , we tested the prediction that longer ITIs would elevate DA release to the US , while shorter ITIs would reduce DA release to the US . The average DA release over all sessions for the 60-s and 120-s groups is shown in Fig 2A . Rats in the 120-s ITI group exhibited significantly higher DA release to the CS and the US relative to rats in the 60-s ITI group ( CS t test: t = 2 . 99 , df = 178 , p < 0 . 05; US t test: t = 3 . 07 , df = 178 , p < 0 . 05 ) . In the 120-s ITI group , DA release to both the CS and the US was significantly higher than baseline ( CS t test: t = 14 . 77 , df = 119 , p < 0 . 05; US t test: t = 4 . 79 , df = 119 , p < 0 . 05 ) ; however , in the 60-s ITI group , this was only true during CS presentation ( t test: t = 7 . 34 , df = 59 , p < 0 . 05 ) ; DA release at the US was not different than baseline ( t test: t = 0 . 99 , df = 59 , p = 0 . 33 ) . Similar results were obtained when averaging across sessions within each rat and then averaging across rats ( Fig 2B ) ; DA release was higher during the CS and US for rats in the 120-s ITI group ( CS t test: t = 1 . 87 , df = 17 , p < 0 . 05; US t test: t = 1 . 83 , df = 17 , p < 0 . 05 ) and was higher than baseline for both periods ( CS t test: t = 6 . 15 , df = 11 , p < 0 . 05; US t test: t = 2 . 16 , df = 11 , p < 0 . 05 ) , whereas DA release was only significantly higher during the CS period for rats in the 60-s ITI group ( CS t test: t = 6 . 68 , df = 6 , p < 0 . 05; US t test: t = 0 . 70 , df = 6 , p = 0 . 26 ) . These results are in line with the STGT model , which predicted that reducing ITI duration would prevent the downward revision of the food cup value and hence would permit the high predictive value associated with the food cup to produce a DA response at CS but not US , consistent with the DA RPE hypothesis [9] . Conversely and also consistent with model predictions , DA release during sessions with the longer ITI was significantly higher during US delivery because there were more positive RPEs , which may result from the positive surprise associated with being rewarded in a food cup whose value has been more strongly decreased during multiple visits to the food cup during long ITIs . Nevertheless , at the CS time , the increased DA burst at CS indicates an even more complex process that goes beyond model predictions . All of this suggests that DA release should be positively correlated with the time spent breaking the beam in the food cup during the ITI . To test this hypothesis , we computed how much time was spent in the food cup during the ITI for each session . This was done by determining the total number of beam breaks within each ITI ( 10-ms resolution ) and then averaging over trials to determine each session mean . Importantly , the ITI time did not vary across sessions within each group , and the analysis was performed separately for the two groups ( 60-s group and 120-s group ) . Thus , any correlation between DA and food cup interaction time during the ITI cannot reflect a correlation between DA and ITI time . As expected , rats in the 120-s ITI group spent significantly more time in the food cup than did rats in the 60-s ITI group ( 120-s ITI group = 15 . 1 s; 60-s ITI group = 6 . 8 s; t test: t = 4 . 91 , df = 178 , p < 0 . 05 ) . For both groups , there was a significant positive correlation between average time spent in the food cup during the ITI and DA release during the reward period ( Fig 2C , 120-s ITI: r2 = 0 . 12 , p < 0 . 05; Fig 2D , 60-s ITI: r2 = 0 . 08 , p < 0 . 05 ) . During the cue period for the 120-s ITI group , but not the 60-s ITI group , there was also positive correlation ( Fig 2E , 120-s ITI: r2 = 0 . 04 , p < 0 . 05; Fig 2F , 60-s ITI: r2 = 0 . 01 , p = 0 . 36 ) . Finally , when examining with data collapsed across both groups , there was a significant positive correlation during both cue and reward epochs ( Cue: r2 = 0 . 05 , p < 0 . 05; Reward: r2 = 0 . 14 , p < 0 . 05 ) . Thus , we conclude that DA release to the CS and US tended to be higher the longer rats visited the food cup during the ITI . In the analysis above , we averaged DA release and behavior from all recording sessions . Next , we asked how behavior and DA release patterns evolved with training . As a first step to addressing this issue , we recomputed the PCA analysis for the first and last 5 d of training . For the 60-s ITI group , the PCA index distribution was significantly shifted in the negative direction ( i . e . , goal tracking ) during the first five sessions ( Wilcoxon; μ = −0 . 38 , p < 0 . 05 ) but not in the last five sessions ( Wilcoxon; μ = 0 . 15 , p = 0 . 07 ) . Thus , early in training , rats with the 60-s ITI exhibited goal tracking more than sign tracking but did not fully transition to sign tracking , at least when we averaged over the last five sessions . For the 120-s ITI group , the PCA index was significantly shifted in the positive direction ( i . e . , sign tracking ) during the last five sessions ( Wilcoxon; μ = 0 . 28 , p < 0 . 05 ) but was not during the first five sessions ( Wilcoxon; μ = 0 . 10 , p = 0 . 11 ) . Thus , when the ITI was long ( 120 s ) , rats sign and goal tracked in roughly equal proportions during the first five sessions but tended to sign track significantly more during later sessions . To more accurately pinpoint when during training rats in the 120-s group shift toward sign tracking , we examined the four distributions individually for each session . Sign tracking became apparent during session 4 , when the latency and lever probability distributions first became significant ( Wilcoxon; latency: μ = 0 . 28 , p < 0 . 05; lever probability: μ = 0 . 40 , p < 0 . 05 ) . To visualize changes in behavior and DA release that occurred before and after session 4 , we plotted food cup beam breaks , lever pressing , and DA release averaged across the first 3 d of training and across days 4–10 ( Fig 3; for visualization of behavior during each of the 10 sessions , please see S4 Fig ) . Consistent with the distributions of behavioral indices described above , the 120-s ITI group showed roughly equal food cup entries and lever pressing during the CS period in the first 3 d of training ( Fig 3A , thin pink solid versus thin pink dashed ) , whereas later in training ( days 4–10; red ) , there was a strong preference for the lever ( Fig 3A; thick red dashed versus thick red solid ) . Indeed , the distribution of PCA indices averaged during days 4–10 were significantly shifted in the positive direction ( Wilcoxon; μ = 0 . 27 , p < 0 . 05 ) . These results suggest that in sessions in which the ITI was set at 120 s , sign-tracking tendencies developed relatively quickly during the first several recording sessions ( Fig 3A and 3C ) . This is consistent with the STGT model , which predicted that increasing the ITI duration would increase the global tendency to sign track within the population and would thus speed up the acquisition of lever pressing behavior [1 , 13] . In contrast , the model also predicted that reducing the ITI duration would increase the global tendency to goal track and would thus slow down the acquisition of lever pressing behavior . Interestingly , the behavior of the 60-s ITI group was far more complicated than behavior of the 120-s group , with changes in goal and sign tracking occurring over training and CS presentation time . Early in training , rats in the 60-s ITI group clearly visited the food cup ( Fig 3B , solid turquoise ) more than they pressed the lever ( Fig 3B , dashed turquoise ) ; food cup entries increased shortly after presentation of the CS and continued throughout the CS period ( Fig 3B , solid turquoise ) . During later sessions ( i . e . , 4–10 ) , rats in the 60-s ITI group still entered the food cup upon CS presentation—which corresponds to the goal-tracking behavior predicted by the model in this case—but this only lasted about 2 s , at which point they transitioned to the lever ( Fig 3B and 3D ) . In sessions 4–10 , none of the distributions of behavioral indices were significantly shifted from zero when examining the CS period as a whole ( Wilcoxons; Response bias: μ = 0 . 27 , p = 0 . 83; Latency: μ = −0 . 05 , p = 0 . 13; Probability: μ = 0 . 08 , p = 0 . 16; PCA: μ = 0 . 02 , p = 0 . 82 ) or during the first half of the CS period ( Response bias: μ = −0 . 11 , p = 0 . 027; Probability: μ = −0 . 04 , p = 0 . 18; PCA: μ = −0 . 07 , p = 0 . 25 ) ; however , when examining the last 4 s of the CS period , distributions were significantly shifted in the positive direction ( Wilcoxons; Response bias: μ = 0 . 32 , p < 0 . 05; Probability: μ = 0 . 28 , p < 0 . 05; PCA: μ = 0 . 24 , p < 0 . 05 ) . Together , this suggests that rats in the 60-s groups were largely goal tracking early in training and that over the course of training , goal-tracking tendencies did not disappear but became focused to early portions of the CS period , while sign-tracking behavior developed toward the end of the CS period , later in training ( Fig 3B and 3D; S4 Fig ) . Interestingly , these results go again beyond the computational model and suggest that it should be extended to account for within-trial behavioral variations . Behavioral analyses clearly demonstrate that manipulation of the ITI impacts sign- and goal-tracking behavior and that both groups learned that the CS predicted reward ( Fig 3; S4 Fig ) . Next , we determined how DA patterns changed during training . Fig 3E and 3F illustrate DA release averaged across the first 3 d and days 4–10 of sessions with 120-s and 60-s ITIs , respectively , and DA release for each session is plotted in Fig 3G and 3H . As shown previously , both groups started with modest DA release to both the CS and US during the first session ( Fig 3G and 3H; trial 1 ) . For the 120-s ITI group , DA release was significantly higher to CS presentation later ( red ) compared to earlier ( pink ) in learning ( Fig 3E; t test: t = 2 . 51 , df = 119 , p < 0 . 05 ) . DA release during US delivery did not significantly differ between early and late phases of training ( t test: t = 1 . 27 , df = 119 , p = 0 . 21 ) . Hence , similarly to the sign trackers in the original study of Flagel and colleagues ( 2011 ) , the increase of DA response to the CS is consistent with the RPE hypothesis . The difference is that here , the increase in the time available to down-regulate the value associated with the food cup during the ITI may have resulted in a remaining positive surprise at the time of reward delivery , hence preventing the progressive decrease of response to the US across training , in accordance with the model predictions . In the 60-s ITI group ( Fig 3F and 3H ) , DA release to the US was initially high during the first 3 d ( turquoise ) but declined during days 4–10 ( blue ) . Directly comparing DA release during the first 3 d with the remaining days revealed significant differences during the US period ( t test: t = 1 . 14 , df = 59 , p < 0 . 05 ) but not the CS period ( t test: t = 0 . 08 , df = 59 , p = 0 . 93 ) . As a consequence , their post-training DA pattern—with a high response to the CS but no response to the US ( Fig 3F , blue ) —now resembles the traditional RPE pattern ( i . e . , high CS DA and low US DA after learning ) . This is a clear demonstration that the DA RPE signal can be observed in goal trackers with a manipulation of the ITI , as predicted by the STGT model . In a final analysis , we examined DA patterns during pure sign and goal tracking within each ITI group . For this analysis , we examined only sessions during which either the lever was pressed or the food cup was entered during the cue period . As shown previously [4] , phasic DA responses were apparent during both the CS and US during sessions with goal tracking ( Fig 3I and 3J , GT = orange ) . In addition to replicating previous results , the figure also illustrates modulation of the DA pattern in line with model predictions . Specifically , it shows that the DA response to the US was higher in the 120-s group than in the 60-s group during both sign- and goal-tracking sessions ( sign-tracking: t test , t = 3 . 66 , df = 25 , p < 0 . 05; goal-tracking: t test , t = 1 . 44 , df = 29 , p = 0 . 16 ) and that the DA response to the US was significantly lower than the DA response to the CS in GTs of the 60-s group ( t = 3 . 87 , df = 17 , p < 0 . 05 ) , suggesting that even though there is still a DA response to the US , shortening the ITI reduced the US-evoked DA response compared with what has been previously reported [4] . The results reported here support the STGT model’s predictions that manipulating the ITI would impact the proportion of sign-tracking ( STs ) and goal-tracking ( GTs ) behaviors as well as DA release . It predicted that shortening the ITI would result in fewer negative revisions of the food cup value and reduce the US DA burst . It also predicted that the resulting higher food cup value would lead to an increase in the tendency to GT across sessions [1 , 13] , which it did . The model also predicted that lengthening the ITI would have the opposite effect . We found that there were significantly more food cup entries during the ITI for the 120-s ITI group and that they showed an increased tendency to sign track . Furthermore , we show that the time spent in the food cup during the ITI was positively correlated with the amplitude of the CS and US DA bursts for the 120-s ITI group , which is consistent with the hypothesis that lengthening the ITI to allow for more time to decrease the value of the food cup would result in stronger positive RPEs during the trial . Consistent with the model , we claim that increased sign tracking and DA release result from the additional time spent in the food cup during the ITI . Indeed , these were positively correlated . Importantly , this impact of ITI manipulations had not been predicted by other computational models of sign trackers and goal trackers [11 , 14] . However , several alternative explanations should be considered , which may have also contributed to observed changes in behavior and DA release . For example , it has been shown that rewards delivered after longer delays yield higher DA responses to the US [15–17] and that uncertain reward increases sign tracking [18] . Although the reward was highly predictable in our study ( i . e . , always delivered 8 s after cue onset ) , it is possible that uncertainty associated with US delivery impacted behavior and DA release . Notably , it is likely that these factors are intertwined in that manipulating delays and certainty impact the number of visits to the food cup that are not rewarded , thus leading to a negative revision of the food cup , as predicted by the model . Future work that modifies food cup entries without manipulating ITI length and rewards uncertainty is necessary to determine the unique contributions that these factors play in goal-/sign-tracking behavior and associated DA release . Another explanation for increased sign tracking and DA release in the rats in the 120-s ITI group is the possibility that they learned faster than rats in the 60-s ITI group because of differing ratios between US presentations and the interval between the CS and US in that , the shorter the CS-US interval relative to the ITI , the faster the learning [19] . In the context of our study it is difficult to determine which group learned faster . Although rats in the 120-s ITI group did lever press more often early in training , rats in the 60-s ITI group made more anticipatory food cup entries during the cue period prior to reward delivery . Furthermore , both food cup entries and lever pressing were present in the first behavioral session ( S4 Fig ) . Thus , both groups appear to learn the CS-US relationship at similar speeds , but it is just that the behavior readout of learning differs across groups , making it difficult to determine which group learned the association faster . In our opinion , our results suggest that rats in both groups learned at similar rates , much like sign and goal trackers do; however , future experiments and iterations of the model are necessary to determine what role the US-US/CS-US ratio plays in sign/goal tracking and corresponding DA release . Standard RL [20] is a widely used normative framework for modelling learning experiments [21 , 22] . To account for a variety of observations suggesting that multiple valuation processes coexist within the brain , two main classes of models have been proposed: MB and MF models [23 , 24] . MB systems employ an explicit , although approximate , internal model of the consequences of actions , which makes it possible to evaluate situations by forward inference . Such systems best explain goal-directed behaviors and rapid adaptation to novel or changing environments [25–28] . In contrast , MF systems do not rely on internal models but directly associate stored ( cached ) values with actions or states based on experience , such that higher valued situations are favored . Such systems best explain habits and persistent behaviors [28–30] . Learning in MF systems relies on a computed reinforcement signal , the RPE ( actual minus predicted reward ) . This signal has been shown to correlate with the phasic response of midbrain DA neurons that increase and decrease firing to unexpected appetitive and aversive events , respectively [9 , 31] . Recent work by Flagel and colleagues [4] has questioned the validity of classical MF RL methods in Pavlovian conditioning experiments . Their autoshaping procedure reported in that article was nearly identical to the one presented here in that a retractable-lever CS was presented for 8 s , followed immediately by delivery of a food pellet into an adjacent food cup . The only major difference was that the length of the ITI in their study was 90 s . In their study , they showed that in STs , phasic DA release in the NAc matched RPE signaling . That is , the DA burst to reward that was present early in learning transferred to the cue after learning . They also showed that DA transmission was necessary for the acquisition of sign tracking . In contrast , despite the fact that GTs acquired a Pavlovian conditioned approach response , this was not accompanied by the expected RPE-like DA signal , nor was the acquisition of the goal-tracking conditioned response blocked by administration of a DA antagonist ( see also Danna and Elmer [10] ) . To account for these and other results , Khamassi and colleagues [1] proposed a new computational model—the STGT model—that explains a large set of behavioral , physiological , and pharmacological data obtained from studies on individual variation in Pavlovian conditioned approach [2–8] . Importantly , the model can reproduce previous experimental data by postulating that both MF and MB learning mechanisms occur during behavior , with simulated interindividual variability resulting from a different weight associated with the contribution of each system . The model accounts for the full spectrum of observed behaviors ranging from one extreme—from sign tracking associated with a small contribution of the MB system in the model—to the other—goal tracking associated with a high contribution of the MB system in the model [12] . Above all , by allowing the MF system to learn different values associated with different stimuli , depending on the level of interaction with those stimuli , the model potentially explains why the lever CS and the food cup might acquire different motivational values in different individuals , even when they undergo the same training in the same task [26] . The STGT model explains why the RPE-like dopaminergic response was observed in STs but not GTs—the proposition being that GTs would focus on the reward-predictive value of the food cup , which would have been down-regulated during the ITI . Furthermore , the STGT explains why inactivating DA in the core of the nucleus accumbens or in the entire brain results in blocking specific components and not others . Here , the model proposes that learning in GTs relies more heavily on the DA-independent MB system , and thus DA blockade would not impair learning in these individuals [4 , 8] . More importantly , the model has led to a series of new experimentally testable predictions that assess and strengthen the proposed computational theory and allow for a better understanding of the DA-dependent and DA-independent mechanisms underlying interindividual differences in learning [1 , 13] . The key computational mechanism in the model is that both the approach and the consumption-like engagement observed in sign trackers ( STs ) on the lever and in goal trackers ( GTs ) on the food cup result from the acquisition of incentive salience by these reward-predicting stimuli . Acquired incentive salience is stimulus specific: stimuli most predictive of reward will be the most “wanted” by the animal . The MF system attributes accumulating salience to the lever or the food cup as a function of the simulated DA phasic signals . In the model simulations , because the food cup is accessible but not rewarding during the ITI , a simulated negative DA error signal occurs each time the animal visits the food cup and does not find a reward . The food cup therefore acquires less incentive salience compared with the lever , which is only presented prior to reward delivery . In simulated STs , behavior is highly subject to incentive salience because of a higher weight attributed to the MF system than to the MB system . As a consequence , they are more attracted by the lever than by the food cup . By contrast , simulated GTs are controlled by the MB system with a higher weight than the MF system . This makes them prefer the food cup , which is the shortest path to reward in the MB system . Moreover , because the food cup has a lower incentive salience , simulated GTs engage with the food cup less than STs do with the lever , as observed experimentally . The STGT model also led to specific predictions about what would happen if rats had more exposure to the food cup in the absence of reward . The key prediction of this aspect of the model was that increased access to the food cup during the ITI should decrease the incentive salience associated with it and , conversely , increase the strength of engagement with the lever . This , in turn , would increase the relative proportion of ST conditioned responses compared to GT conditioned responses . In addition , the model predicts that DA release to the CS would be higher than DA to the US because of the predictive power of the CS , and DA release to the US would remain high after conditioning because of the persistent positive surprise associated with reward delivery in the food cup . Both of these predictions were confirmed in our current study; in sessions from rats in the 120-s ITI group , the tendency to sign track was more prominent , DA release was significantly higher during CS presentation , and US-evoked DA remained after learning . Conversely , the model also predicted that decreased access to the food cup during the ITI would increase the incentive salience associated with the food cup , resulting in more goal-tracking behavior associated with a DA signal better resembling the classic RPE pattern ( i . e . , cue but not reward firing after learning ) . These predictions were partially confirmed in our current study; rats in the 60-s ITI group were more likely to be goal trackers if they were classified based on their initial approach to the food cup in response to the CS [4] . The post-learning DA pattern of the 60-s ITI group showed a high DA response to the CS , but not the US . Taken together , these results validate the STGT model . However , it is worth noting that the observed behavior of the 60-s ITI group goes beyond the predictions of the STGT model . The 60-s ITI group indeed showed more complex behavior in response to lever CS presentation: an initial food cup approach during the first 2 s after the CS—consistent with goal-tracking behavior—followed by a more ST-like behavioral engagement with the lever ( Fig 1G and 1H; Fig 3B and 3D; S4 Fig ) . The late engagement with the lever is not predicted by the computational model , which only attempts to model the initial behavioral response of the animals to the CS [1] . This is compatible with the way sign trackers and goal trackers were classified based on their initial response to the CS in the original study [4] . This simplification in the model still accounts for a full spectrum of interindividual variability , even animals originally classified in the “intermediate group , ” exhibiting both ST and GT behaviors . Nevertheless , the present results highlight that the STGT model should be extended to account for temporal variability of the animal’s behavior within each trial . Twenty-nine male Sprague-Dawley rats were obtained from Charles River Labs at 250–275 g ( 90–120 d old ) . Animals were individually housed in a temperature- and humidity-controlled environment and kept on a 12-h light/dark cycle ( 0700–1900 in light ) ; all tests were run during the light phase . Animals had access to water ad libitum and body weight was maintained at 85% of baseline weight by food restriction ( 15 g standard rat chow was provided daily , in addition to approximately 1 g sucrose pellets during experimental trials ) . All procedures were performed in concordance with the University of Maryland , College Park Institutional Animal Care and Use Committee ( protocol number R-15-34 ) . Electrodes were constructed according to the methods of Clark and colleagues ( 2010 ) [32] . A single carbon fiber ( Goodfellow Corporation , Coraopolis , PA ) was inserted into a 15-mm cut segment of fused silica ( Polymicro Technologies , Phoenix , AZ ) while submerged in isopropyl alcohol . One end of the silica tubing was sealed with a two-part epoxy ( T-QS12 Epoxy , Super Glue ) and left to dry overnight , leaving untouched carbon fiber extending past the seal . The protruding carbon fiber was cut to a length of 150 μm . A silver connector ( Newark , Chicago , IL ) was secured to the carbon fiber at the opposing end of the silica tubing using silver epoxy ( MG Chemicals , British Columbia , Canada ) and was allowed to dry . A final coat of two-part epoxy was then applied to the pin connection to provide insulation and structural support for the electrode and was allowed to dry overnight . All animals were anesthetized using isoflurane in O2 ( 5% induction , 1% maintenance ) and implanted with a chronic voltammetry microelectrode aimed at the NAc core ( +1 . 3 AP , +1 . 8 ML , −6 . 6 DV ) , an ipsilateral bipolar stimulating electrode ( Plastics One , Roanoke , VA ) in the medial forebrain bundle ( −2 . 8 AP , +1 . 7 ML , −8 . 5 DV ) , and a contralateral Ag/AgCl reference electrode ( Sigma-Aldrich , Allentown , PA ) . The reference electrode and anchoring screws were stabilized using a thin layer of dental cement ( Dentsply , York , PA ) , leaving the holes for the stimulating and recording electrodes unobstructed . The stimulating and recording electrodes were attached to a constant current isolator ( A-M Systems , Carlsborg , WA ) and voltammetric amplifier , respectively , and lowered to the most dorsal point of the target region ( −6 . 6 DV for the working electrode and −8 . 5 DV for the stimulating electrode ) . At this depth , a triangular voltammetric input waveform ( −0 . 4 to +1 . 3 V versus Ag/AgCl , 400 V/s; Heien and colleagues , 2003 ) was applied to the recording electrode at 60 Hz for 30 min and then reduced to 10 Hz for the remainder of the surgery . Electrical stimulation ( 24 biphasic pulses , 60 Hz , 120 μA ) was applied to the stimulating electrode in order to evoke DA release , which was monitored at increasing depths by the recording electrode . If neither an evoked change in DA nor a physical response ( whisker movement or blinking ) was observed , the stimulating electrode was lowered by 0 . 05 mm until a response was achieved or to a maximum depth of 8 . 8 mm . The working electrode was then lowered by 0 . 05 mm until DA release was observed or to a maximum depth of 6 . 9 mm . Once electrically evoked DA release was detected in the NAc core , a thin layer of dental cement was used to secure the stimulating and recording electrodes in place . A Ginder implant ( Ginder Scientific [Nepean , Ontario , Canada]; constructed in house ) was connected to the reference , stimulating , and recording electrodes and fully insulated using dental cement , leaving only the screw-top connector exposed , in order to reduce noise and prevent loss of connectivity during behavioral training . Animals then received postoperative care: subcutaneous injection of 5 mL saline containing 0 . 04 mL carprofen ( Rimadyl ) , topical application of lidocaine cream to the surgical area , and placement on a heating pad until full consciousness was regained . Animals were also given antibiotic treatment of Cephlexin orally twice daily post-surgery for 1 wk to prevent infection of the surgical site . All subjects were allowed a month for full recovery and stabilization of the electrode before experimentation . All behavioral procedures were conducted in Med Associates test chambers equipped with a food cup and a retractable lever located to the left or right of the food cup ( counterbalanced ) . Head entries into the food cup were time-stamped during disruption of the photobeam located inside the receptacle . Similarly , time stamps were generated during downward deflection of the lever . Three pretraining sessions were conducted that consisted of the delivery of 25 sucrose pellets , which were randomly delivered on a variable-interval 30 ± 15-s schedule . Following pretraining , rats began Pavlovian training sessions , which consisted of the presentation of the lever ( CS ) for 8 s , which was immediately followed with delivery of a sucrose pellet upon its retraction . The CS was presented on a random interval of either 60 ± 30 s ( i . e . , 30 , 40 , 50 , 60 , 70 , 80 , or 90 s ) or 120 ± 30 s ( i . e . , 90 , 100 , 110 , 120 , 130 , 140 , or 150 s ) , and each Pavlovian session consisted of 25 trials . Pavlovian training continued for 10 sessions , which were accompanied with FSCV recording . For recordings , animals were connected to a head-mounted voltammetric amplifier ( current to voltage converter ) and a commutator ( Crist Instruments , Hagerstown , MD ) mounted above the recording chamber . During each session , an electrical potential was applied to the recording electrode in the same manner as described above ( see “Intracranial surgical procedures” ) . In order to detect changes in dopaminergic concentration over time , the current at its peak oxidation potential was plotted for successive voltammetric scans , and background signal was subtracted . Two PC-based systems , fitted with PCI multifunction data acquisition cards and software written in LabVIEW ( National Instruments , Austin , TX ) , were used for waveform generation , data collection , and analysis . The signal was low-pass filtered at 2 , 000 Hz . Event time stamps from Med Associates were recorded in order to analyze behaviorally relevant changes in DA release . DA was identified by its stereotypical and specific cyclic voltammogram signature . Behaviorally evoked DA signals met electrochemical criterion if the cyclic voltammogram was highly correlated with that of the DA templates produced during training sets , as described below . The training set is a template extracted from individual animals that contains six each of background-subtracted cyclic voltammograms and corresponding calibrated concentrations for both DA and pH acquired during electrical stimulations that are known to evoke DA release ( stimulation at 1 V: 30 Hz , 6 pulses; 30 Hz , 12 pulses; 30 Hz , 24 pulses; 60 Hz , 6 pulses; 60 Hz , 12 pulses; 60 Hz , 24 pulses ) . The data collected during a session were not analyzed if DA release did not satisfy these chemical verification criteria ( e . g . , Fig 1D and 1E ) . Voltammetric data were analyzed using software written in LabView and Matlab . A principal component regression ( Tar Heel CV chemometrics software ) was used to extract the DA component from the raw voltammetric data [33 , 34] . Eigenvalues ( principal components ) are calculated that describe relevant components of the training set , and we perform multivariate regression analysis to determine a correlation coefficient to describe our recorded behavioral data versus the training set . The number of factors we select to keep in our PCA analysis accounts for >99% of the variance ( at least three , but usually four to five factors are kept ) . Factor selection is a very important step , as retaining more factors than we need would add noise to our data , but retaining too few could mean discarding potentially meaningful information [35] . Importantly , the exact same method was applied to both groups , allowing for fair comparisons . We also use the residual to examine the quality of the fit . In general , the residual is the difference between the experimental observation and the predicted value derived from a model/template ( our regression values ) and is a measure of the unknown portion of the signal , which is not accounted for by the principal components of the regression . This is important when considering the accuracy and the applicability of the model and is important for identifying possible interfering molecules or noise ( such as drift ) . The sum of squares of the difference between the template and the experimental data is the residual value ( Q ) and the threshold , Qa , establishes whether the retained principal components provide a satisfactory description of the experimental data; the discarded principal components should provide a measure of noise [33–35] . We use this Qa measure in combination with our regression analysis to establish our concentration corrections . Chemometrics is a widely used analytical method that separates changes in current that are caused by DA release from those caused by pH shift or other electrochemical “noise” by comparing eigenvalues derived from stimulated DA release and changes in pH with those derived from behavioral release [4 , 33–38] . Once converted to concentrations , DA release was examined over three analysis epochs: ( 1 ) Baseline = 3 s before CS onset , ( 2 ) CS epoch = 3 s starting 1 s after CS onset , and ( 3 ) US epoch = 3 s starting 1 s after reward delivery ( i . e . , lever in ) . In our final data set , there were 12 rats with 10 sessions per rat for the 120-s ITI group . In the 60-s ITI group , there were 5 rats with 10 sessions , 1 rat with 6 sessions ( days 4–9 ) , and 1 rat with 3 sessions ( days 4–6 ) . Following the completion of the study , animals were terminally anesthetized with an overdose of isoflurane ( 5% ) and transcardially perfused with saline and 4% paraformaldehyde . Brain tissue was removed and postfixed with paraformaldehyde . Brains were then placed in 30% sucrose solution for 72 h and sectioned coronally ( 50 μm ) using a microtome . Tissue slices were mounted onto slides and stained with thionin for histological reconstruction . Disclaimer: The opinions expressed in this article are the authors’ own and do not reflect the view of the NIH/DHHS .
In classical or Pavlovian conditioning , subjects learn to associate a previously neutral stimulus ( called “conditioned” stimulus; for example , a bell ) with a biologically potent stimulus ( called “unconditioned” stimulus; for example , a food reward ) . In some animals , the incentive salience of the conditioned stimuli is so strong that the conditioned response is to engage the conditioned stimuli instead of immediately approaching the food cup , where the predicted food will be delivered . These animals are referred to as “sign trackers . ” Other animals , referred to as “goal trackers , ” proceed directly to the food cup upon presentation of the conditioned stimulus to obtain reward . Understanding the mechanisms by which these divergent behaviors develop under identical environmental conditions will provide powerful insight into the neurobiological substrates underlying learning . Here , we test predictions made by a recent computational model that accounts for a large set of studies examining goal-/sign-tracking behavior and the role that dopamine plays in learning . We show that increasing the duration of the time between trials leads more to the development of a sign-tracking response and to the release of dopamine in the nucleus accumbens . During conditioning with shorter intertrial intervals , goal tracking was more prominent , and dopamine was released upon presentation of the conditioned stimulus but not during the time of reward delivery after training . Thus , shorter intertrial intervals restored the classical dopamine reward prediction error pattern . Our results validate the computational hypothesis and open the door for understanding individual differences to classical conditioning .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "learning", "medicine", "and", "health", "sciences", "neurochemistry", "chemical", "compounds", "classical", "conditioning", "vertebrates", "social", "sciences", "conditioned", "response", "neuroscience", "animals", "mammals", "learning", "and", "memory", "organic", "compounds", "hormones", "animal", "models", "surgical", "and", "invasive", "medical", "procedures", "model", "organisms", "cognitive", "psychology", "mathematics", "functional", "electrical", "stimulation", "probability", "distribution", "membrane", "electrophysiology", "experimental", "organism", "systems", "amines", "neurotransmitters", "bioassays", "and", "physiological", "analysis", "catecholamines", "dopamine", "research", "and", "analysis", "methods", "animal", "studies", "behavior", "chemistry", "electrophysiological", "techniques", "short", "reports", "probability", "theory", "biochemistry", "behavioral", "conditioning", "rodents", "psychology", "eukaryota", "electrode", "recording", "organic", "chemistry", "biogenic", "amines", "biology", "and", "life", "sciences", "physical", "sciences", "cognitive", "science", "amniotes", "organisms", "rats" ]
2018
Manipulating the revision of reward value during the intertrial interval increases sign tracking and dopamine release
In some recent studies , a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment . We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation . In contrast to population-based expression data , single-cell gene expression data revealed a high cell-to-cell variability , which was masked by averaging . We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker ( DNB ) theory . In addition , we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation . In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time , we used Shannon entropy as a measure of the heterogeneity . Entropy values showed a significant increase in the first 8 h of the differentiation process , reaching a peak between 8 and 24 h , before decreasing to significantly lower values . Moreover , we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h . In conclusion , when analyzed at the single cell level , the differentiation process looks very different from its classical population average view . New observables ( like entropy ) can be computed , the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network . The classical view of a linear differentiation process driven by the sequential activation of master regulators [1] has been increasingly challenged in the last few years both by experimental findings and theoretical considerations . Thanks to the recent development in single-cell profiling technologies , researchers are now able to investigate qualitatively and quantitatively the cell-to-cell variability in gene expression in more detail . In this context , several experimental studies at single-cell level involving the regulation of self-renewal and differentiation processes in embryonic stem cells [2–8] and the generation of induced pluripotent stem cells [9] have shown that gene expression variability might be involved in cell differentiation . To support this claim , recent researches on hematopoietic stem cells highlighted the role of molecular heterogeneity in differentiation [10 , 11] . Further evidence was also obtained during an ex vivo differentiation process [12] , and in the generation of cells of the immune system [13–18] . The overt cell-to-cell variability is deeply rooted in the inherent stochasticity of the gene expression process [19–23] . Numerous explanations have been put forward regarding the molecular and cellular sources for such variability ( see [24] and references therein ) . Some of those causes involve biophysical processes ( e . g . , the random partitioning during mitosis , as discussed in [25] ) , whereas others are more related to biochemical regulation ( e . g . , the dynamical functioning of the intracellular network [26] or the chromatin dynamics [27] ) . At least three models of cell differentiation based on stochastic gene expression have been proposed , in which a peak in the gene expression variability is expected to occur . In the first model , stochastic gene expression is the driving force of cell differentiation that generates cell type diversity , on which a selective constraint is then exerted [28] . In the second model , noise in gene expression causes bifurcations in the dynamics of gene regulatory networks [21] . In the third model , cell differentiation is viewed as a dynamical process in which differentiating cells are thought of as particles moving around in a state space [29 , 30] . This formal space can be used to display gene expression patterns . Hence , when some parameters that describe gene regulatory interactions change , the cell particle “moves” in the state space . In this view , discrete identified cell states ( e . g . , self-renewing , differentiated ) correspond to different regions of this space that could be seen as different attractor states . The transition process between attractors therefore first requires the exit from the original state that may be fueled by an increase in gene expression stochasticity [31] . Regardless of the differences between these models , they all assume that the differentiation process is represented by cell trajectories leading from one state to another through a phase of biased random walk in gene expression . This phase is followed by stabilization ( convergence ) toward a particular pattern of gene expression corresponding to a stable attractor state , the differentiated final state , in which noisy fluctuations of gene expression is minimized by the stabilizing effect of the attractor . Therefore , changes in the extent of cell-cell variability could be a new observable metric to characterize the cell differentiation process . The purpose of the present study was then to assess whether gene expression variability changes during the differentiation process , as suggested by the above-quoted models , and whether such variation concurs with any physiological cellular change . We investigated the extent of gene expression variability at the single-cell level , both before and during the cell differentiation process . To do this , we analyzed the differentiation process of T2EC , which is an original cellular system consisting of non-genetically modified avian erythrocytic progenitor cells grown from a primary culture [32] . These cells can be maintained ex vivo in a self-renewal state under a combination of growth factors ( TGF-α , TGF-β , and dexamethasone ) and can also be induced to differentiate exclusively toward erythrocytes by changing the combination of the external factors present in the medium . The primary cause for differentiation is therefore known and relies upon change in the information carried by the extracellular environment . The differentiation process in those cells has been previously analyzed at the population level [33–35] . We first selected a pool of 110 relevant genes on the basis of RNA-Seq analysis performed on populations of T2EC in self-renewal state or induced to differentiate for 48 h . Multivariate statistical analysis of the data allowed us to select 92 genes for further analysis . We then performed high-throughput reverse transcription followed by reverse transcription quantitative PCR ( RT-qPCR ) of the 92 selected genes on single-cells collected at six time-points of differentiation . Several dimensionality reduction algorithms were used to visualize trends in the datasets . In agreement with the above hypothesis , cell heterogeneity , as measured by entropy , significantly increased during the first hours of the differentiation process and reached a maximal value at 8 to 24 h before decreasing toward the end of the process . The peak in entropy preceded an increase in cell size variability at 48 h . These observations suggested that 24 h is a crucial turning point in the erythrocytic differentiation process , which was experimentally verified by showing that T2EC committed irreversibly to the differentiation process between 24 h and 48 h . In order to identify a pool of genes potentially relevant in the differentiation process , we analyzed the transcriptome of self-renewing and differentiating primary chicken erythrocytic progenitor cells ( T2EC ) using RNA-Seq . We sequenced two independent libraries from self-renewing T2EC and two independent libraries from T2EC induced to differentiate for 48 h . For each condition , we first verified that read counts between replicates were reproducible ( S3A and S3B Fig ) . We then identified 424 significantly differentially expressed genes ( p-value < 0 . 05 , S3C Fig ) . Gene ontology analysis using the DAVID database [60] revealed a clear over-representation of genes involved in sterol biosynthesis in this list ( not shown ) . This finding was in line with our previous analysis showing that the oxydosqualene cyclase ( OSC ) , which is involved in cholesterol synthesis , is required to maintain self-renewal in T2EC [35] . However , no other over-represented function emerged from the present analysis . To identify a smaller subset of relevant genes for further analysis by RT-qPCR using the Fluidigm array ( see below ) , we tested 56 down-regulated and 77 up-regulated genes among the above 424 genes differentially expressed in self-renewing versus differentiating cells , which had the smallest set of p-values . We also included 32 non-regulated genes , selected among the most invariant ones . We then measured the expression of these 165 genes first using RNA from bulk cell populations taken at five time-points during differentiation ( 0 , 8 , 24 , 48 , and 72 h ) . Based on qPCR primer efficiency , 55 genes were removed ( see Materials and Methods ) , which left a total of 110 genes for the subsequent analysis . A principal component analysis ( PCA ) on the bulk gene expression levels ( Fig 1A ) showed a clear separation of the time-point 0 h ( self-renewal ) from the differentiation time-points . Samples along the differentiation process were well ordered according to the first principal component ( PC1 ) . PC1 explained 56 . 2% of the data variability suggesting that the differentiation process is the main source of variability at the population level for the selected genes . We also performed a hierarchical cluster analysis ( HCA ) , which again showed a clear arrangement of the samples according to their position along the differentiation process ( Fig 1B ) . We further noticed that the gene expression patterns at 0 , 8 , and 24 h time-points were more similar to each other , while those at 48 h and 72 h time-points were also more similar to each other . Thus , the 110 selected genes allowed us to clearly distinguish cell populations according to their progression along the differentiation sequence , indicating that they were relevant for analyzing this process . However , since the single-cell measurement technology used in this study could only accommodate 92 genes ( not including two spikes and two repeats for the RPL22L1 gene ) , we further refined our gene choice by performing a K-means clustering on the above data . The algorithm grouped genes based on their expression profile , and identified seven different gene clusters with respect to expression kinetics ( S4 Fig ) . The patterns mainly showed decreasing or increasing gene expressions during the differentiation process , while one cluster displayed a more complex dynamic ( cluster 4 ) . The latter was composed of genes whose expression decreased during the first 8 h , then increased and stabilized between 24 h and 48 h , before decreasing again until 72 h . Interestingly , all genes belonging to this cluster were linked by their involvement in sterol biosynthesis , reinforcing the previously noted role of this pathway in erythroid differentiation . Based on the result of K-means clustering , we selected around thirteen genes per group to represent each cluster equally . This left us with 92 genes for further analysis ( S1 Table ) . We then used STRING database to search for known connections among these genes . The result confirmed the existence of a strongly connected subnetwork associated with sterol synthesis ( S5B Fig ) . Moreover , this analysis also revealed the presence of another highly connected subnetwork mostly composed of genes involved in signaling cascades and two transcription factors ( BATF and RUNX2 ) . Those two main networks are linked by the gene HSP90AA1 which encodes the molecular chaperone HSP90alpha . Its activity is not only involved in stress response but also in many different molecular and biological processes because of its important interactome . HSP90alpha represents 1%–2% of total cellular protein in unstressed cells . Interestingly , HSP90alpha level is up-regulated and correlated with poor disease prognosis in leukemia [61] . HSP90alpha has also been shown to be involved in the survival of cancer cells in hypoxic conditions [62] . We measured the expression level of the selected 92 genes by single-cell RT-qPCR using 96 cells isolated from the most informative time-points of the differentiation sequence . Based upon preliminary experiments , we decided to analyze cells from six time-points during differentiation . After data cleaning ( see Materials and Methods ) , we obtained the expression level of 90 genes in 55 , 73 , 72 , 70 , 68 , and 51 single cells from 0 , 8 , 24 , 33 , 48 , and 72 h of differentiation , respectively . One should note that the variability we observed at the single-cell level originates from two types of sources: biological sources and experimental sources . We therefore tested the technical reproducibility of different RT-qPCR steps liable to generate such experimental noise ( see Materials and Methods ) . As expected , reverse transcription ( RT ) was the main source of experimental variability , since pre-amplification and qPCR steps brought negligible amount of variability ( S1 Fig ) . Moreover , using external RNA spikes controls whose Cq value depends only on the experimental procedure , we noted that technical variability was negligible compared to the biological variability ( see Materials and Methods ) . Quality control ( see Materials and Methods ) led to the elimination of 2 genes , letting us with 90 genes for subsequent analysis . We first used PCA on the single-cell expression of these 90 genes ( Fig 2A ) . In contrast to the whole-population data , the single-cell data did not immediately demarcate into well-separated clusters . The differentiation process was most apparent by looking at the second principal component ( PC2 ) , which explained 9 . 9% of the variability in the dataset . Hence , unlike in the population-averaged data , the differentiation process did not represent the main source of variability at the single-cell level . The application of HCA further confirmed that the classification became more complex for single-cell data ( Fig 2B ) . Contrary to bulk analysis , individual cells from the same time-point were not necessarily more similar to each other than to cells from neighboring time-points . Consequently , the clustering of individual cells into groups became complicated . The picture of cell differentiation process that emerged from the single-cell analysis thus far was more complex than the one obtained from the population level analysis . This difference between single-cell and population-level analysis arises from the unraveling of cell-to-cell heterogeneity in the single-cell data , which could have been hidden by the averaging effect of the population ( see below ) . PCA is a linear method for dimensionality reduction of single-cell data . In view of non-linear relationships of cell states in state space , recently nonlinear techniques like t-SNE [55] or diffusion maps [63] have been applied in single-cell data analysis . t-SNE is a variation of Stochastic Neighbor Embedding deemed capable of capturing more local structures than classical PCA , while also revealing global structure such as the presence of clusters at several scales . Diffusion maps use a non-linear distance metric ( referred to as diffusion distance ) , which is deemed conceptually relevant in view of noisy diffusion-like dynamics during differentiation [63] . We therefore applied these algorithms on our datasets , as well as another non-linear version of PCA , called Kernel PCA [64] , not previously applied to single-cell gene expression data ( Fig 2C to 2E ) . The general conclusions obtained by PCA did not appreciably change when using these non-linear dimensionality reduction techniques . There was again an obvious trend reflecting the differentiation process , as well as a significant amount of intermingling of cells from different time-points . In order to assess to what extent the differentiation process was still visible in the single-cell data , we performed PCA on datasets from the two extreme time-points , 0 and 72 h ( Fig 3A ) . The result showed a clear separation of both time-points with only a few cells intermingled . We also performed HCA on datasets from the same time-points ( Fig 3B ) . Again , the segregation of the cells was still not perfect , but cells were not as mixed as before . Here , there exist two clusters of self-renewing and differentiating cells . When compared to the analysis of the entire time series , the separation between cells from the two extreme time-points looked clearer . Therefore , the analysis of single-cell data confirmed that part of the information present in the single-cell data is linked to the differentiation process . The idea that shared information was present in single-cell and population-based data was reinforced by the analysis of the correlation matrices within and between the two datasets ( S6 Fig ) . It was apparent that ( 1 ) the global intensity of the correlations was higher with population-based data and ( 2 ) there existed a co-structure between the two datasets . At the population level , we showed that the set of genes selected was relevant to analyze the differentiation process ( Fig 1 ) . The cross-correlation analysis strengthened this view and demonstrated that when looking at the single-cell scale , the information held by these genes was not totally erased by cell-to-cell variability . We then looked at the genes that contributed the most to the PCA outcome ( Fig 3C ) . Among the genes that discriminate the most self-renewing cells , one could highlight LDHA ( Lactate deshydrogenase A ) , CRIP2 , and Sca2 . Sca2 is a gene that we previously have shown to be associated with the self-renewal of erythroid progenitors [34] . LDHA is less expected and will be discussed below . Among the genes that contributed the most to discriminating differentiated cells , one could highlight RHPN2 and betaglobin . Since betaglobin is a part of hemoglobin , the most abundant protein in erythrocytes , it was expected to be associated with differentiating cells . Given that the analysis of single-cell gene expression did not produce a clear separation of the temporal stages , in contrast to whole populations , we hypothesized that by averaging over a population of individual cells , we should be able to reproduce the bulk results . For this purpose , we generated three pseudo-populations ( sub-populations ) of about one-third of cells from the single-cell data and computed their average gene expressions for each time-point . By performing PCA on the mean gene expressions of these pseudo-populations , we noticed that the averaged data showed more organization and , importantly , that the differentiation progression materialized along the PC1 dimension ( Fig 4A ) . The PCA result of the pseudo-population therefore looked much more like the population than the single-cell results . Similarly , HCA generated a clustering that was not quite as clear as the analysis of bulk RNA data , but much better than the single-cell analysis ( Fig 4B ) . The HCA results showed for example similarities between gene expressions from time-points 48 and 72 h . Together the pseudo-population analysis obtained by statistical averaging of single-cell data mostly recapitulated , albeit not entirely , the population-based results , suggesting that the clear-cut classification of bulk-cell-based data is due to the ( physical ) averaging effect in populations , in line with a previous account [65] . Single-cell data offers access to the patterns of the relationship of genes with respect to both their marginal ( S7 Fig ) , as well as their full joint distribution ( not shown ) . This provides us with a new observable that we used to characterize the progression of the differentiation process in finer details . For each time-point , we computed a correlation matrix to evaluate how correlated the expression of any pair of genes was , across all cells at a given time . Since data were log-normally distributed , we employed the Spearman correlation coefficient . We then calculated the significance of the correlation and used a p-value below 0 . 05 as a cutoff . Two genes ( the nodes of a graph ) that exhibited a significant correlation were connected by an edge . Finally , we sub-sampled 85% of the cells for 10 , 000 iterations , so as to obtain robust correlation networks that will not depend upon the sampling process . We then constructed a gene correlation network for each time-point . Although both positive and negative correlations were computed , negative correlations proved much less robust and were eliminated by the sub-sampling process , in which we only kept significant correlations that appeared in all of the 10 , 000 subsampling . As shown in ( Fig 5A ) , the density of the resulting networks ( number of significant correlations ) was clearly varying along the differentiation process . One observed a sudden drop in the number of correlations by 8 h that then steadily increased to reach a maximum value at 72 h much higher than the initial value . Interestingly , this global behavior resulted from both an increase and a decrease in gene-to-gene correlation values ( Fig 5B ) . Even between 48 and 72 h , some gene pair correlation decreased while the overall net balance resulted in a global increase . This fast-changing density of the networks was also accompanied by a progressive change in the identity of the most highly correlated nodes ( Fig 5C ) . Both Sca2 and LDHA that were previously identified by the PCA also appeared as prominent among the correlation network from 8 to 24 h , while later time-points were characterized by the appearance of other genes as TBC1D7 and BCL11A . One should note that such correlation networks are to be seen as resulting from the behavior of the underlying mechanistic gene interaction networks , but can not be taken per se as a faithful representation of such dynamical interaction networks . Contrary to previous accounts [12 , 66] , we observed a global decrease in the correlation intensity between 0 and 8 h . Nevertheless , we noticed that some gene pairs showed an increased correlation coefficient . We therefore reasoned that those genes could represent a putative dynamical network biomarker ( DNB ) , a subgroup of genes involved in the critical transition phase of a dynamical system [51] . To qualify for a DNB , three conditions have to be fulfilled: ( 1 ) the coefficent of variation ( CV ) of each variable in the DNB should increase , ( 2 ) the correlation ( PCCin ) within the DNB should increase , and ( 3 ) the correlation ( PCCout ) between the DNB and outside genes should decrease . All three conditions can be simultaneously quantified using the I score ( see Materials and Methods ) . We therefore first selected a group of 12 genes by a two-stage process: ( 1 ) we first selected all of the genes that participated in at least one pair that showed an increased correlation of at least 0 . 5 between 0 and 8 h and ( 2 ) among those genes , we selected the genes that showed an increase in their CV value between 0 and 8 h . We then computed the I score of that group of genes at each time-point ( Fig 6 ) . Although PCCin slightly decreased with time , this group of genes nevertheless might still qualify for a DNB since they matched two out of the three criteria used to identify DNBs . Their I value first sharply increased before returning to lower values . This rise is mostly due to a sharp decrease in PCCout between 0 and 8 h , accompanied by a more modest increase in CV . As mentioned , the internal correlation value PCCin decreased , and therefore was not driving the I value . One must note that we computed a Pearson correlation coefficient as advocated [51] . We also tried a Spearman correlation value , which showed a slightly different behavior with a modest increase in PCCin between 8 and 24 h and continued to increase steadily up to 72 h , not affecting the global surge in I value ( not shown ) . Since we observed major changes after 8 h of differentiation , one asked how early changes in gene expression could be detected . For this we performed a second single-cell kinetic experiment , where we obtained the expression level of 90 genes in 48 , 48 , 39 , and 41 single cells from 0 , 2 , 4 , and 8 h of differentiation , respectively . We then defined the first wave of response as genes that showed a significant difference between 0 and 2 h . Two genes satisfied this criterion ( Fig 7 ) , establishing that the transcriptional response to the medium change was a very fast process , but concerned only a very limited number of genes . The second wave was defined as genes not belonging to wave 1 and showing a significant difference between 2 and 4 h of the response . Five genes satisfied this criterion ( Fig 7 ) . It was remarkable that six out of the seven genes from waves 1 and 2 belonged to the same functional group , that is the group of genes associated with sterol synthesis . This proved to be highly statistically significant ( p = 1 . 8 × 10−6 ) . We therefore can propose that the sterol synthesis pathway could act as one of the drivers of the changes that will update the internal network from the changes in external conditions . This would be in line with our previous demonstration for the role of cholesterol synthesis in the decision making process in our cells [35] . A critical novel opportunity provided by single-cell analysis is to study cell-to-cell variability of gene expression as an observable per se and also to add new insight to characterize the temporal progression of differentiation . The question as to what may be the best metrics for quantifying gene expression variability is still open . An aggregated measure called the Jensen-Shannon divergence has been proposed previously as a measure for gene expression noise [9] . One of the main drawbacks of this metric is that it was not possible to assess whether or not the differences observed were statistically significant . We therefore decided to use a simpler Shannon measure of the heterogeneity among the cells for their gene expression profile ( see Materials and Methods and S2 Fig ) . Such a measure provided a distribution of entropy values per gene per time-point , allowing to perform statistical tests . We observed that this entropy increased gradually along the differentiation process , reaching its maximal value at 8 to 24 h , before declining toward 72 h ( Fig 8A ) . Such an increase of entropy between 0 and 8h resulted from a global increase of each gene entropy , except for a few ( Fig 8B ) . The observed rise in entropy value was highly significant as early as 8 h when compared to 0 h of differentiation . Furthermore , decrease in entropy also became significant between 24 and 33 h of differentiation ( Fig 8C ) . Consequently , since entropy can be defined as a measure of the disorder of a system , this result suggested that a maximal heterogeneity was achieved at 8–24 h of the differentiation process in the expression of our 90 genes , before significantly decreasing to a much lower level of heterogeneity . Different potential causes can be envisioned to explain this increase in entropy , including cell size and cell-cycle stage variations , asynchrony in the differentiation process , and more dynamical causes . As suggested in some previous works , cell size and cell-cycle stage variations could influence gene expression , and become confounding factors [67–69] . Nevertheless , variability due to variations in cell cycle has been shown to be quantitatively negligible in erythroid precursors [70] . We also added in our gene list the CTCF gene , known to be cell-cycle regulated in chicken cells [71] . Almost no correlation was detected between this gene and any of the 91 other genes ( Fig 9A ) demonstrating that our gene list contained virtually no other cell-cyle-regulated gene . Furthermore , we assessed whether or not the repartition of our cells within the different phases of the cell cycle could have been modified at a time where entropy was peaking . No significant difference in cell cycle repartition could be seen at 8 h of differentiation ( Fig 9B ) . Altogether , those results demonstrate that a potential effect of cell cycle variation would only marginally explain our data . Regarding cell size , it is important to note that in our system the peak in gene expression variability at 8–24 h occurs at a time where cell size is not affected ( Fig 10B ) . If anything , we observed a slight increase in cell size , which could be responsible for a decrease , and not an increase , in noise [72] . We then assessed a potential effect of asynchrony in the differentiation process . For this , we first employed the following algorithms: SCUBA [52] , WANDERLUST [53] and TSCAN [54] to reorder the cells according to the calculated pseudotimes . However , SCUBA led to a cell re-ordering that was highly inconsistent with the actual time-points , where all self-renewing cells ( time 0 h ) were placed in the middle of the SCUBA order ( not shown ) . WANDERLUST and TSCAN produced a more reasonable cell ordering . However , the trajectories of the gene expression profiles following this ordering were quite erratic ( not shown ) . Nevertheless , the entropy of sub-populations of cells , grouped according to either their WANDERLUST pseudotimes or TSCAN clusters , showed the same rise-then-fall profile as with the original single cell data ( Fig 9C and 9D ) . In theory , these algorithms are supposed to reconstruct a posteriori the “hidden” order along the differentiation pathway . Within this frame , the behavior of entropy in re-ordered cells tends to support the idea that asynchrony in the differentiation process is not the leading cause of our observed increase in entropy . However the intrinsic burstiness of the gene expression process [24 , 73–75] might cause some issues in the use of cell re-ordering algorithms . We therefore examined this question by using a more formal approach . We reasoned that a modeling strategy might be useful in establishing the role asynchrony might play , especially since forcing a synchronous differentiation is not accessible in vitro , but can be done in silico . We used a two-state model of gene expression [27 , 39–41 , 56] , for which we could learn the parameters from the data ( see Materials and Methods ) . In the synchronous case , we obtained a variation in entropy resembling the one we calculated from the data ( Fig 9E ) . The introduction of asynchrony induced a flatter time profile of the entropy ( Fig 9F ) . This finding did not , however , prove that our cells are synchronously differentiating , but only demonstrated the effect of asynchrony: in the background of bursty gene transcriptional process , asynchrony will tend to smoothen ( and not augment ) the entropy of the system . Therefore the observed surge in entropy can not be attributed to the asynchrony of the process . The rise-and-fall of entropy in our data is in line was examined in a different setting , namely a reprogramming process [58] . The authors stated , “The initial transcriptional response is relatively homogeneous , ” offering the opportunity to examine the entropy time profile in such a homogeneous process . Our analysis of this dataset produced a similar behavior for entropy which significantly increased initially , before returning to lower values ( S8 Fig ) . Altogether our analysis is compatible with the notion that the rise and fall in entropy is the consequence of the dynamical behavior of the underlying gene regulatory network . The above analysis of single-cell transcript profiles displays the following pattern: Altogether , those results point toward the 8 and 24 h time-points as being a possible decision point , hence , a “point-of-no-return” in the differentiation process , beyond which cells are irreversibly committed toward erythrocytic differentiation . Consequently , we hypothesized that committed cells would be unable to revert back to a self-renewal process after 24 h of differentiation . To test this hypothesis we induced T2EC to differentiate for 24 h or 48 h , after which cells were transferred back into the self-renewal medium , in order to determine whether or not cells could revert back to the undifferentiated state after they had received differentiation signals for a given period of time . We observed that T2EC induced to differentiate for 24 h were still able to self-renew upon change of medium , while cells induced for 48 h could not do so ( Fig 10A ) . T2EC induced for 48 h seemed to stay in a quiescent state until they died . We therefore concluded that the physiological point of no return is located between 24 h and 48 h of our differentiation process , as suggested by our in silico analysis . Finally we determined whether cell size , a phenotypic integrated variable that has historically been used to monitor erythroid maturation [76 , 77] would manifest the behavior of the underlying molecular network with respect to cell-cell variability . We therefore assessed cell size variation during the differentiation process . As expected [32] , mean cell size started to decrease during differentiation to reach a minimum by 72 h ( Fig 9B ) . Interestingly , cell size variability significantly peaked at 48 h before dropping precipitously by 72 h . Thus the high variability of gene expression observed at 24 h preceded a significant peak in cell size variability 1 d later . One question deals with the possible identification of important genes that can be seen as “drivers” of the process . At least three list of genes were generated during the course of this work that may qualify: Restricting only to the most densely correlated genes at 0 and 8 h ( since the two other lists were validated on those time-points ) , one observed a partial overlap between the three lists ( S9 Fig ) , with no gene being common to all three lists . One possible explanation is simply that the three lists were obtained through different approaches , not supposed to identify the same set of genes . This result nevertheless suggests that although all of those genes might be functionally important for the differentiation process , they might be involved in the global response at different levels . The early drivers might be more important for informing the whole network at early time points , whereas the two other genes sets might be involved in a more global reconfiguration of the network at later time-points . In any case those gene lists are to be seen as traces resulting from the behavior of the underlying dynamical network , and should not be mistaken for the dynamical network itself . It would therefore be of utmost importance to be able to correctly infer such a network . We are actively pursuing this goal in our group . We discuss below possible functions of some of those genes , a full discussion for all genes being out of the scope of the present paper . As previously mentioned , Sca2 is a gene which we have previously shown to be associated with the self-renewal of erythroid progenitors [34] . LDHA encodes an enzyme that catalyzes the conversion of pyruvate to lactate , and has been involved in the Warburg effect ( or anaerobic glycolysis ) , which is the propensity of cancer cells to take up glucose avidly and convert it to lactate [78] . Furthermore , deletion of LDHA has been shown to significantly inhibit the function of both hematopoietic stem and progenitor cells during murine hematopoiesis [79] . Since LDHA expression is under the control of HIF1α transcription factor [79] , it could be involved in the response of immature erythroid progenitors to anemia . Those cells have to show a significant amount of self-renewal for recovering from a strong anemia , implying low oxygen condition [80] . It makes perfect sense that in this case the metabolism of self-renewing progenitors would rely upon an anaerobic pathway . Moreover , HIF1alpha has also been shown to be an upstream regulator of HSP90alpha secretion in cancer cells in a protective way against the hypoxic tumoral environment [81] . Therefore , our results are in line with other findings showing that anaerobic glycolysis is favored in hypoxic conditions , such as the bone marrow environment , and required for stem cell maintenance [82] . Otherwise , since LDHA and HSP90alpha form part of the lists of potentially important genes between 0 and 8 h , our finding suggests that erythroid differentiation might be accompanied by a change from anaerobic glycolysis toward mitochondrial oxidative phosphorylation , as recently proposed [83] . Finally , our analysis highlighted the importance of the sterol synthesis pathway in the self renewal process since: These observations support the importance of sterol synthesis in the maintenance of cellular self renewal state and the necessity of a decrease of some sterol associated genes expression to allow the differentiation . The question as to why this group of genes act as the early sensors of change in environmental conditions remains elusive . In line with our previous results [35] , one could hypothesize that cholesterol synthesis is a barrier toward differentiation/apoptosis that has to be lowered for differentiation to proceed . On a more global perspective , the importance of cell-to-cell heterogeneity as a “biological observable” at the single-cell level , even among cells classified as belonging to the same “cell type” [85] , is increasingly recognized [86] . But to what extent and when is such heterogeneity functionally important ? Most single-cell transcript profile analyses of cell populations have so far focused mostly on computational descriptive analysis to identify clusters , and temporal progression , or to test dimensionality reduction and visualization tools , but less so to test a biological hypothesis . Here we used the single-cell granularity of gene expression analysis to test the long-standing hypothesis that stochastic cell-cell variability is not simply the byproduct of molecular noise but that such randomness of cell state plays a key role in differentiation [28] . In this Darwinian view , differentiation starts with an unstable gene expression pattern , generating cell type diversity . Therefore , one testable prediction was that an increase in gene expression heterogeneity should be observed during the critical phase of cell differentiation whenever the irreversible decision to commit is made . Our main contribution is a demonstration that the increase in molecular variability precedes critical functional variations in cellular parameters , most importantly including the commitment status of the cells . Taken together , the timing of three observables achieved at single-cell resolution provides a coherent picture of a temporal structure of differentiation that would be invisible to traditional whole-population averaging techniques: ( i ) the surge in cell-to-cell variability of gene expression patterns of individual cells at 8–24 h; ( ii ) a sudden drop in the overall correlation , concomitant with the emergence of a DNB; and ( iii ) followed by the phenotypic marker of differentiation , the decrease of cell size , for which variability peaks at 48 h . An important question is the relevance of that peak in variability . We demonstrated experimentally that no cell was able to return to a self-renewal state after 48 h in a differentiation medium . A similar timing for point-of-no return has previously been suggested in FDPC-mix cells [87] . Such an irreversible commitment to differentiation preceded by a highly significant increase in cell-to-cell variability is consistent with the explanation that cells differentiate by passing through two phases [87]: a first phase in which the self-renewing state is destabilized and primed by perturbation of their extracellular environment , followed by a second phase of a stochastic commitment to differentiation . These observables ( emergence of a DNB , drop in correlation , significant increase in entropy , surge in cellular parameters variations ) jointly suggest a critical state transition , a class of dynamical behaviors that has been proposed to explain the qualitative , almost discrete and noise-driven “switching” into a new cell state as embodied by differentiation [88] . This conceptual framework naturally explains the irreversibility of fate commitment [89] . Indeed the maximum of the above three observables coincided with the functionally demonstrated point-of-no return to the self-renewal state in T2EC differentiation process , which was located between 24 and 48 h . From a more biological perspective , we can view differentiation induction as a process of adaptation in which the cell’s internal molecular network , adapted for growth in self-renewal conditions , has to adjust to the new external conditions when differentiation is induced by the change in external conditions . For example , in yeast , it has been shown that a nonspecific transcriptional response reflecting the natural plasticity of the regulatory network supports adaptation of cells to novel challenges [90] . The underlying mechanisms are yet to be discovered , but one would expect global mechanisms to be involved . Modifications of the chromatin dynamics [27] under the possible control of metabolic changes [91] are obvious candidates for such a role . Fluctuation in important transcription factor level has also been proposed to be involved [92] . The surge of non-specific variability would allow exploration of new regions in the gene expression space . Preventing such an increase in variability has been associated to trapping cells in an undifferentiated state [93] . This increase would lead to a reconfiguration of the gene expression network into a state which is compatible with differentiation conditions and which is robust and consistent with a new attractor state in the network [29] . Then the decrease of molecular variability might reflect the implementation of the fully differentiated phenotype as cells settle down in the next stable state . In this study , we exploited the wealth of information available in single-cell data by highlighting the critical molecular changes occurring along the differentiation sequence . First , the initial gene expression waves might represent a very early signal that happens between 0 and 8 h , followed by a pre-transition warning signal revealed by the DNB analysis , concomitant with the drop in gene correlations and the rise in cell-to-cell variability . Such a pattern are thought to reflect the underlying dynamical molecular mechanisms that drives the evolution of cells through the differentiation process . The first signals could be seen as an adaptative response to environmental changes , as suggested above , whereas the last warning signal , before irreversible commitment , could be seen as the point of cell decision making . At that stage it is hard to really be sure that the DNB genes actually drives the critical transition , but at the very least they represent a clear signal that our cells are experiencing such a transition . Until 24 h , at least , cells would still be able to functionally respond to self-renewal signals . This implies that at that stage the state of the network would be compatible with both a differentiation and a self-renewal process . One of the remaining challenging questions is what makes the cell takes the irreversible decision to differentiate at a point when the system seems to be totally disorganized . We strongly believe that this will be an emerging properties from the behavior of dynamical high-dimensional molecular network . While the current study offers a single-cell resolution view on gene expression , it does so only through snapshots at strategically selected time-points . In the future it would therefore be of great importance to obtain a continuous measurement of the underlying gene expression network in order to explain the state changes in individual cells and to reconstruct the entire trajectory of each cell in gene expression state space . This information would expose the actual process of diversification that leads to the maximal heterogeneity marking the point of no return of differentiation . NOTE ADDED IN PROOF: During the submission of this manuscript we became aware of the work of Mojtahedi , et al . , 2016 ( doi: 10 . 1371/journal . pbio . 2000640 ) which arrived at a similar conclusion , and we cite that work in our discussion . T2EC were extracted from bone marrow of 19-d-old SPAFAS white leghorn chickens embryos ( INRA , Tours , France ) . These primary cells were maintained in self-renewal in LM1 medium ( α-MEM , 10% Foetal bovine serum ( FBS ) , 1 mM HEPES , 100 nM β-mercaptoethanol , 100 U/mL penicillin and streptomycin , 5 ng/mL TGF-α , 1 ng/mL TGF-β and 1 mM dexamethasone ) as previously described [32] . T2EC were induced to differentiate by removing the LM1 medium and placing cells into the DM17 medium ( α-MEM , 10% foetal bovine serum ( FBS ) , 1 mM Hepes , 100 nM β-mercaptoethanol , 100 U/mL penicillin and streptomycin , 10 ng/mL insulin and 5% anemic chicken serum ( ACS ) ) . Differentiation kinetics were obtained by collecting cells at different times after the induction in differentiation . Cell population growth was evaluated by counting living cells using a Malassez cell and Trypan blue staining . T2EC in self-renewal medium and T2EC induced to differentiate during 8 h were incubated for 30 min on ice with 100% cold ethanol , and then 30 min at 37°C with 1 mg/mL RNase A ( Invitrogen ) . Propidium Iodide ( SIGMA ) was added at 50 μg/mL 2 min prior to analysis and fluorescence was measured with the BD FacsCalibur 4-color flow cytometer , using the FL-2 channel . Data files were then extracted and analyzed using the bioconductor flowCore package . T2EC were collected individually in a 96-well plate using a flow cytometer ( Facs ARIA I ) . Each individual cell was immediately gathered into a lysis buffer ( Vilo [Invitrogen] , 6U SUPERase-In [Ambion] , 2 . 5% NP40 [ThermoScientific] ) , containing also Arraycontrol RNA spikes ( Ambion ) . After collection , single-cells were immediately frozen on dry ice and stored at -80°C . Cell cultures were centrifuged and washed with 1X phosphate-buffered saline ( PBS ) . Total RNA were extracted and purified using the RNeasy Plus Mini kit ( Qiagen ) . Then , RNA were treated with DNAse ( Ambion ) and quantified using the Nanodrop 2000 spectrophotometer ( Thermoscientific ) . RNA-Seq libraries were prepared according to Illumina technology , using NEBNext mRNA library Prep Master Mix Set kit ( New England Biolabs ) . Libraries were performed according to manufacturer’s protocol . mRNA were purified using NEBNext Oligo d ( T ) 25 magnetic beads and fragmented into 200 nucleotides RNA fragments by heating at 94°C for 5 min , in the presence of RNA fragmentation Reaction Buffer . Fragmented mRNA were cleaned using RNeasy MinElute Spin Columns ( Qiagen ) . Double strand cDNA were obtained by two-step RNA reverse transcription ( RT ) with random primers and purified using Magnetic Agencourt AMPure XP beads . To produce blunt ends , purified cDNA were incubated with NEBNext End Repair reaction buffer and NEBNext End Repair enzyme mix for 30 min at 20°C . cDNA were purified again using Agencourt AMPure XP beads , and dA-tail were added to these cDNA fragments by incubating them with NEBNext dA-Tailing reaction buffer and klenow fragment for 30 min at 37°C . After purification of the dA-tailed DNA , illumina adaptators were ligated to cDNA in the presence of NEBNext quick ligation reaction buffer , quick T4 DNA ligase , and USER enzyme . After size selection , purified adaptor-ligated cDNA were enriched by PCR with NEBNext High-fidelity 2X PCR Master mix , universal PCR primers and Index primers , and using thermal cycling conditions recommended by manufacturer’s procedure . Finally , enriched cDNA were purified and sequenced by the Genoscope institute ( Evry , France ) . Sequencing files were loaded onto Galaxy ( https://usegalaxy . org/ ) . Quality was checked using FastQC . Groomed sequences were aligned on the galGal4 version of the chicken genome , using TopHat [36] . The resulting . BAM files were transformed into . SAM files using SAM Tools . The gene counts table was generated using HTSeq [37] and the chr_M_Gallus_gallus . Galgal4 . 72 . gtf annotated genome version . Differential gene expression was computed using EdgeR and plotted with the plotSmear function [38] . Every experiment related to high-throughput microfluidic-based RT-qPCR was performed according to Fluidigm’s protocol ( PN 68000088 K1 , p . 157–172 ) and recommendations . Since RT-qPCR experimental procedure introduces unavoidable technical noise , we decided to explore which steps were the main sources of this variability ( S1 Fig ) . We first assessed the reproducibility of the cDNA pre-amplification step by amplifying four cDNA samples from the same RT before analyzing it by qPCR . Gene expression levels differences between pre-amplification replicates were found to be negligible ( S1A and S1B Fig ) . We then checked the RT-qPCR amplification step by analyzing the RPL22L1 gene three times per chip . Expression levels between RPL22L1 triplicates were quantitatively extremely similar ( S1C to S1E Fig ) , confirming that amplification brings a negligible amount of variability as previously shown [42 , 43] . We also tested the experimental variability induced by the RT reaction . We observed significant gene expression level differences between three RT from the same sample ( S1A and S1F Fig ) , contrary to replicates from other critical steps . Indeed , it has been demonstrated and discussed that the RT reaction is the main source of technical noise , since it introduces biases through priming efficiency , RNA integrity and secondary structures and reverse transcriptase dynamic range [42 , 44 , 45] . In order to estimate the amount of variation introduced in our experiments by this step , we used external RNA spikes . The variation affecting those spikes spanned 5 . 8 Cqs ( mean of Cqmax−Cqmin across the spikes ) whereas the variability affecting the genes spanned a much larger region of 22 . 9 Cqs ( mean of Cqmax−Cqmin across the genes ) , showing that the biological variability was much larger than the variability introduced by the RT step .
The differentiation process has classically been seen as a stereotyped program leading from one progenitor toward a functional cell . This vision was based upon cell population-based analyses averaged over millions of cells . However , new methods have recently emerged that allow interrogation of the molecular content at the single-cell level , challenging this view with a new model suggesting that cell-to-cell gene expression stochasticity could play a key role in differentiation . We took advantage of a physiologically relevant avian cellular model to analyze the expression level of 92 genes in individual cells collected at several time-points during differentiation . We first observed that the process analyzed at the single-cell level is very different and much less well ordered than the population-based average view . Furthermore , we showed that cell-to-cell variability in gene expression peaks transiently before strongly decreasing . This rise in variability precedes two key events: an irreversible commitment to differentiation , followed by a significant increase in cell size variability . Altogether , our results support the idea that differentiation is not a “simple” series of well-ordered molecular events executed identically by all cells in a population but likely results from dynamical behavior of the underlying molecular network .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genetic", "networks", "rna", "extraction", "cell", "differentiation", "multivariate", "analysis", "developmental", "biology", "mathematics", "statistics", "(mathematics)", "network", "analysis", "forms", "of", "dna", "dna", "thermodynamics", "extraction", "techniques", "research", "and", "analysis", "methods", "computer", "and", "information", "sciences", "lipids", "entropy", "mathematical", "and", "statistical", "techniques", "gene", "expression", "principal", "component", "analysis", "sterols", "complementary", "dna", "physics", "biochemistry", "nucleic", "acids", "gene", "identification", "and", "analysis", "genetics", "biology", "and", "life", "sciences", "physical", "sciences", "statistical", "methods" ]
2016
Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process
Prion infections cause neurodegeneration , which often goes along with oxidative stress . However , the cellular source of reactive oxygen species ( ROS ) and their pathogenetic significance are unclear . Here we analyzed the contribution of NOX2 , a prominent NADPH oxidase , to prion diseases . We found that NOX2 is markedly upregulated in microglia within affected brain regions of patients with Creutzfeldt-Jakob disease ( CJD ) . Similarly , NOX2 expression was upregulated in prion-inoculated mouse brains and in murine cerebellar organotypic cultured slices ( COCS ) . We then removed microglia from COCS using a ganciclovir-dependent lineage ablation strategy . NOX2 became undetectable in ganciclovir-treated COCS , confirming its microglial origin . Upon challenge with prions , NOX2-deficient mice showed delayed onset of motor deficits and a modest , but significant prolongation of survival . Dihydroethidium assays demonstrated a conspicuous ROS burst at the terminal stage of disease in wild-type mice , but not in NOX2-ablated mice . Interestingly , the improved motor performance in NOX2 deficient mice was already measurable at earlier stages of the disease , between 13 and 16 weeks post-inoculation . We conclude that NOX2 is a major source of ROS in prion diseases and can affect prion pathogenesis . Prion infections cause the deposition of misfolded , aggregated prion protein ( PrPSc ) in the brain , and lead to progressive , lethal neurodegeneration . These diseases are also known as transmissible spongiform encephalopathies because their main neuropathological hallmark is the presence of vacuoles in affected brain regions [1] . Some of the molecular mechanisms underlying these processes are beginning to be understood , but it is still impossible to arrest the progression of the disease . Expression of prion protein on neuronal cell membranes is a prerequisite to neurodegeneration [2] , [3] , and only the genetic ablation of prion protein has conferred complete resistance to the disease [4] . In contrast , pharmacological and genetic approaches targeting mediators of prion-dependent neurotoxicity pathways have been found to modify the course of the disease , but never to reverse it [5]–[7] . We posit that the identification of additional molecular components involved in prion neurotoxicity will be instrumental in designing effective therapeutic approaches . Signs of oxidative damage have been described in patients affected by CJD and in experimental models of prion disease [8]–[11] . Also , an accelerated course of the disease has been recently reported in mice devoid of proteins involved in oxidant defense mechanisms ( SOD1 , OGG1 and MUTYH ) , suggesting a deleterious effect of increased oxidative stress levels [12] , [13] . However , the source of excessive ROS production has not been yet described , and the impact of reduced oxidative stress levels on the course of the disease remains unclear . The NADPH oxidase enzyme NOX2 is an electron transporter whose only known physiological function is the production of ROS [14] . NOX2 produces ROS by the interaction with the transmembrane protein , p22phox , the cytosolic subunits , p47phox , p67phox , p40phox , and one of the small Rho GTP-binding proteins , Rac1 or Rac2 . This enzymatic complex plays an important role in phagocytes , where production of ROS is necessary for effective host defense [14] . However , in certain pathological situations , an excessive activation of NOX2 can lead to oxidative imbalance and contribute to disease progression [14] , [15] . We have recently reported that NOX2 is involved in the neurotoxicity of ligands targeting the prion protein , PrPC [16] . Antibodies to the globular domain of PrPC , but not to other epitopes , elicited rapid neurotoxicity in vivo and in vitro . After administration of such neurotoxic antibodies , NOX2-deficient mice developed smaller lesions than wild-type controls , suggesting a role of NOX2 in PrPC-dependent neurotoxicity processes . Such mechanisms could also be involved in the pathobiology of prion diseases . We therefore investigated the role of NOX2 in bona fide prion disorders . We found that NOX2 is mainly expressed in microglia , particularly in the cells surrounding spongiform vacuoles in brains of CJD patients . NOX2-deficiency in mice resulted in decreased ROS production and reduced spongiform changes at the terminal phase of the disease . These effects were associated with an increase in survival and , more importantly , with improved motor function during the clinical phase of the disease . Hence NOX2 is a major contributor to the excessive production of ROS detected in prion disorders , and therefore influences prion pathogenesis . We first investigated the expression and localization of NOX2 in brain samples of patients affected by CJD . Immunohistochemistry was performed on sections of cerebellum and frontal cortex from ten CJD patients with a balanced distribution of PrP types 1 and 2 as reported on Western blots of PK-treated brain homogenates ( S1 Table ) . Samples of three patients affected by Alzheimer's disease ( AD ) were used as controls ( CERAD definite and Braak & Braak stage V ) ; the first patient also presented with the cortical type of diffuse Lewy body disease . The specificity of the anti-human NOX2 antibody was confirmed by the detection of the appropriate band in Western blotting of PLB-985 human myeloid cells and concomitant absence of signal in human NOX2-deficient PLB-985 cells [17] , human NOX1-overexpressing CHO cells and HEK293 cells overexpressing human NOX3 , 4 , 5 , DUOX1 and DUOX2 ( personal communication , Dr . Vincent Jaquet , University of Geneva ) . As indicated in representative images ( Fig . 1A–H ) , conspicuous NOX2 staining was detected in affected brain regions of CJD patients . Increased expression of NOX2 in CJD , as compared to AD brain sections , was confirmed by quantitative analysis ( Fig . 1K ) . The morphology of NOX2-positive cells suggested that they consisted mainly , if not exclusively , of microglia . In all CJD brains we noticed a particular strong expression of NOX2 around a subset of vacuoles ( Fig . 1I–J ) . In order to clarify the cellular localization of NOX2 in the brain of CJD patients , we performed multicolor immunofluorescent analyses using astrocytic ( glial fibrillary acidic protein; GFAP ) , neuronal ( microtubule-associated protein 2 ( MAP2 ) and neurofilament heavy 200 kD subunit ( NF ) ) as well as microglial markers ( ionized calcium-binding adapter molecule 1; IBA1 ) . Confocal imaging revealed no colocalization between NOX2 and either GFAP , MAP2 or NF ( Fig . 2A–C ) . NF was also detected around a subset of vacuoles ( Fig . 2C , lower set of panels ) , but the vacuoles strongly stained with NF antibodies were not superimposable with those stained for NOX2 . Instead , cellular colocalization was detected between NOX2 and the microglial marker IBA1 ( Fig . 2D ) . Strikingly , strong NOX2 immunoreactivity was present in microglial cells surrounding spongiform vacuoles ( Fig . 2D , lower set ) . These data indicate that microglial NOX2 was significantly upregulated in brains of CJD patients , suggesting its involvement in the neuropathological changes developing in human prion diseases . We next analyzed by Western blotting the expression of NOX2 in mice inoculated with prions and sacrificed at the terminal stage of disease , and compared it with mice injected with non-infectious brain homogenate ( NBH ) . NOX2 expression was significantly increased . The specificity of the signal was confirmed by absence of the relevant bands from brain homogenates of prion-inoculated , terminally sick Nox2 deficient mice ( Fig . 3A ) . Also in prion-infected organotypic cerebellar slices , we found that both NOX2 mRNA and protein levels were significantly increased over those of NBH-exposed slices ( Fig . 3B–C ) . Hence NOX2 is significantly induced upon prion infection both in vivo and in cerebellar slices . As a powerful tool to clarify the cellular localization of NOX2 also in mice , we took advantage of CD11b-HSVTK transgenic mice , which express the Herpes simplex thymidine kinase ( HSVTK ) under the transcriptional control of the Itgam promoter , active in macrophages and microglia . Administration of ganciclovir to these mice leads to selective microglia depletion [18] . Efficient microglia depletion , induced by ganciclovir treatment and confirmed by absence of IBA1 signal ( Fig . 3C ) , led to complete suppression of Nox2 transcript expression ( Fig . 3B ) and complete disappearance of all NOX2 protein ( as assessed by Western blotting ) from both NBH and prion-treated slices ( Fig . 3C ) . These data indicate that NOX2 expression is linked to the presence of microglial cells . Having assigned the expression of NOX2 to microglial cells , we investigated whether there would be a difference in microglial proliferation between wild-type and NOX2-deficient animals after prion inoculation . Since Nox2 gene targeting was originally performed in 129-derived embryonic stem cells ( CCE . 1 line ) , with the resulting mice being backcrossed to the C57BL/6J genetic background [19] , we assessed the extent and distribution of 129-derived genomic material in NOX2-deficient mice . Genome-wide single nucleotide polymorphism ( SNP ) analysis indicated that 99 . 86% of the analyzed SNPs were of C57BL/6 J type , with 129-derived SNPs clustering exclusively on the X chromosome in a region spanning <28 . 6 million base pairs comprising the Nox2 locus . Extensive mapping studies on different combinations of mouse and prion strains failed to identify quantitative trait loci on the X chromosome significantly impacting prion incubation time [20]–[24] . Therefore , the 129-derived genomic region on NOX2-deficient mice is unlikely to represent a significant genetic confounder for our study [25] . We first verified that NOX2 deficiency did not affect PrPC expression levels ( S1 A-B Figure ) and that partially proteinase-resistant prion protein accumulation occurred in both wild-type and Nox2 knock-out animals ( S1 C–D Figure ) . The extent of microglial reactions was analyzed by immunohistochemistry and Western blotting using the IBA1 antibody in male Nox2+/Y and Nox2-/Y littermates inoculated with 7 log LD50 units of the 22 L strain of prions . In agreement with previous reports [26] , microglia immunostaining increased during disease incubation and became markedly prominent at the terminal stage ( Fig . 4A ) . Quantification of IBA1 staining did not show a significant difference between Nox2+/Y and Nox2-/Y mice at any time point analyzed ( Fig . 4B and S2A Figure ) . This observation was confirmed by Western blotting analysis ( S3A Figure ) . Similarly , we could not see any effect on astrocytic response ( S4A and B Figure ) . Although NOX2 deficiency had no discernible influence onto the extent of microglia proliferation , it might still impact the production of ROS . We therefore investigated possible differences in oxidative stress levels by using in vivo injection of the dihydroethidium ( DHE ) probe . This molecule reacts with ROS and is converted into fluorescent adducts which can be measured in brain sample homogenates [27] . As expected from previous investigations , signs of oxidative stress production were identified in prion-infected , terminally scrapie-sick mice , but not in mice injected with normal brain homogenate . Excessive ROS production was only detected at the most advanced stages of disease , and was completely absent from NOX2-deficient mice ( S3B Figure; Fig . 4C ) . In addition , we found fewer spongiform changes in Nox2-deficient mice ( Fig . 4D–E and S2B Figure ) . These results point to NOX2 as a major source of ROS in prion disease and a mediator of prion-induced neuronal toxicity . In order to assess the neurological deficits induced by prion disease , we used the rotarod test , which primarily measures motor coordination and balance abilities [28] . Rotarod performance was similar in wild-type and NOX2-deficient mice at the early stage of the disease and up to 12 weeks following prion inoculation ( Fig . 5A ) . Also , control mice injected with NBH did not display any difference during the entire test period , up to 20 weeks post-injection ( S5 Figure ) , confirming previous reports that absence of NOX2 does not alter motor capacities [29] . In contrast , starting from 13 weeks post prion inoculation , we noticed a clear difference between the two groups . Wild-type animals displayed reduced motor capacities , being able to remain on the rotating rod for significantly shorter periods of time than NOX2-deficient mice ( Fig . 5A ) . However , this improvement was transient , and was no longer detectable during the late stages of the disease ( 17–18 weeks post-inoculation ) . Nevertheless , NOX2 deficient mice enjoyed modest yet significantly increased survival ( Fig . 5B–C ) . The median survival for Nox2+/Y vs . Nox2-/Y mice was , respectively , 150 . 5 vs . 157 days post inoculation ( dpi ) after injection with 7 log LD50 units of prions and 180 vs . 188 dpi after inoculation with 3 log LD50 units ( P = 0 . 0052 and 0 . 2176 respectively , log-rank test ) . Similar to a previous report [30] , we detected a difference in incubation time between males and females with both prion titers . Upon exposure to the 22 L strain of prions , wild-type females displayed accelerated progression of the disease as compared with wild-type males ( 7 log LD50 units = median survival males 150 . 5 dpi , females 145 dpi; P<0 . 0001; 3 log LD50 units = males 180 dpi , females 164 dpi; P = 0 . 0003 , log-rank test ) . Possibly due to this accentuated effect on females , we only noticed a difference between wild-type and NOX2-deficient females after inoculation with lower doses of prions ( Fig . 5D–E ) : the median survival for Nox2+/+ vs . Nox2 -/- females was , respectively , 164 vs . 179 . 5 dpi after inoculation with 3 log LD50 units of prions , while was 145 dpi for both groups after inoculation with 7 log LD50 units ( P = 0 . 0030 and P = 0 . 7289 respectively , log-rank test ) . We have analyzed the role of NOX2 in a mouse model of prion disease . Our results indicate that NOX2 , expressed in microglial cells , is a relevant source of oxidative stress in this context , and contributes to prion-induced functional alterations . Prion inoculation of mice faithfully reproduces the neuropathological and clinical manifestations of the corresponding human pathology , and indeed , a marked microglial NOX2 staining was present in brain sections of patients affected by CJD . In light of the recently recognized differences between human and murine microglia [31] , the consistency of our findings in both species supports the validity of our results across multiple species including humans . It has been reported that CJD patients experience higher levels of microglia proliferation and increased oxidative stress than patients suffering from Alzheimer's disease ( AD ) [10] . Analogously , we found stronger NOX2 staining in brain sections of CJD patients than in those of AD patients . Formation and accumulation of misfolded proteins is the main pathogenic event in several phenotypically diverse neurodegenerative diseases [32] . Such aggregates trigger a number of toxic and reparative responses , such as microglia activation , impaired neurotransmission and neuronal damage [33] . Signs of oxidative stress have been consistently detected among these processes , yet were mainly attributed to mitochondrial dysfunctions [34] . Instead , our data support a role for NOX2 enzyme as possible major source of ROS in protein misfolding diseases [15] . Therefore , beyond their relevance to the understanding of prion pathogenesis , our findings corroborate the idea that NOX2 inactivation is broadly implicated in neurodegenerative diseases . Moreover , immunohistochemistry for NOX2 proved to be a robust and reliable tool to visualize microglia , and might be the best among the available immunohistochemical markers for this cell type . Intriguingly , we found a very striking pattern of NOX2 expression around neuronal vacuoles . Spongiform vacuolation is a highly characteristic sign of prion disease pathology , and vacuoles represent distended intracellular compartments mostly located within neuronal processes . While the mechanisms underlying the development of vacuoles in prion diseases have not been identified , the intracellular localization of vacuoles in prion diseases sets them apart from those observed in other neurological pathologies , such as AD or brain edema [35] , [36] . Neurofilament proteins can abnormally accumulate around spongiform vacuoles [36] , but it has also been reported that microglia can surround the rim of such vacuoles [37] , [38] . The intimate topographic relationship between vacuoles and microglial processes suggest that the latter may respond to activating signals emanating directly from the vacuolated structures . The cellular localization of NOX2 has been long debated . It has been suggested that NOX2 is expressed by neurons , yet most such evidence derives from in vitro studies or from immunostaining performed in absence of pertinent controls [15] , [39] . Confocal imaging of both human brain tissues , as well as microglia depletion of murine organotypic slice cultures , indicates that within the brain , NOX2 expression is mainly restricted to microglial cells . Targeting NOX2 in microglial cells may selectively control deleterious functions exerted by microglia [40] . Moreover , NOX2 may be involved in the recently described microglia-regulated neuronal differentiation and circuitry remodeling during neurogenesis and synapse formation [41]-[43] . Differentiation of neural stem cells and synaptic plasticity can be indeed influenced by NOX2-dependent ROS production [15] , which could therefore depend on NOX2 microglial rather than neuronal expression . As previously reported for other pathologies [44] , [45] , NOX2 deficiency does not affect proliferation of microglia cells or accumulation of misfolded protein aggregates . Microglia-mediated phagocytosis is a crucial mechanism of defense against PrPSc deposition and prion-induced damage [46] , [47] . Indeed , microglia removal by ganciclovir in CD11b-HSVTK slices led to increased levels of PK-resistant PrPSc [46] . Similarly , genetic ablation of the gene encoding for the milk fat globule–epidermal growth factor 8 ( Mfge8 ) , impaired the engulfment of apoptotic cells and was associated with augmented PrPSc accumulation . Since Mfg8 is secreted by astrocytes , while its receptors are expressed by microglia , it is possible that microglia-mediated phagocytosis serves to limit prion deposition . However , microglia overactivation can transform them in “saboteurs” , further contributing to the progression of the disease [48] . One of the mechanisms associated with this transformation can be the excessive production of NOX2-dependent ROS [49] . At the terminal stage of disease , NOX2 ablation completely prevented ROS production in prion-infected brains , which may represent a plausible explanation for the observed reduced spongiform changes and improved survival . In the early preclinical stages of the disease ( 4 to 12 weeks post-inoculation ) , we did not observe any difference between wild-type and NOX2-deficient animals in terms of ROS production and motor performance . However , starting from 13 weeks post inoculation , rotarod analysis revealed a significantly attenuated decline in locomotor abilities in NOX2-deficient mice , lasting up to 16 weeks post-inoculation . Interestingly , when ROS levels were analyzed at this time point , they were still indistinguishable from wild-type and NOX2-ablated mice . One possible explanation is that even very small amounts of ROS , below the detection threshold of the dihydroethidium assay , may play a role in neurological degradation following prion infections . Accordingly , increased levels of oxidative stress in the cerebellum were only found at the terminal stage of mouse scrapie [11] . Although NOX2 ablation does not ultimately prevent the development of prion disease , the results presented above show that NOX2 is a relevant constituent of the neurotoxic cascade in these diseases . Ablation or overexpression of superoxide dismutase , SOD1 , activity can decrease or increase prion incubation time , respectively [7] , [12] . Together with these previous findings , our data support the crucial impact of superoxide production in prion diseases . Moreover , they suggest that NOX2 , expressed in microglial cells , is the major source of this superoxide production . The use of antioxidants as possible therapeutic approach for CNS diseases has been favored by promising results of rodent studies; however , disappointing and incongruous outcomes have been observed in clinical trials [50] , [51] . Lack of specificity of antioxidant treatments could be one of the reasons that explain such a failure in clinical translation . Having identified NOX2 as a possible specific target may offer an opportunity to reduce the occurrence of oxidative stress insults in CJD patients . In particular , our data suggest that inhibition of NOX2 may attenuate , at least temporarily , the neurological dysfunctions associated with prion disease , thereby enhancing the quality of life – a legitimate and important goal even if the overall life expectancy may not be dramatically improved . All human tissue samples used in this study dated from before the year 2005 , and were irreversibly anonymized . Approval by an institutional review board is not mandatory for irreversibly anonymized samples collected before the approval of the Swiss Medical-ethical guidelines and recommendations ( Senate of the Swiss Academy of Medical Sciences , Basel , Switzerland , 23 May 2006 ) . Animal care and experimental protocols were in accordance with the “Swiss Ethical Principles and Guidelines for Experiments on Animals” , and approved by the Veterinary office of the Canton of Zurich ( permits 130/2008 and 41/2012 ) . Prion inoculations were performed under isoflurane anesthesia , and every effort was made to minimize animal discomfort . Samples were obtained from the tissue bank of the Swiss National Reference Centre of Prion Diseases ( Zurich , Switzerland ) . Samples from patients affected by dementia ( CJD and AD ) were used to quantify the extent of NOX2 expression . Samples from patients not affected by dementia were used as controls ( S6 Figure ) . A subset of tissue specimens collected and analyzed according to biosafety guidelines outlined in our previous study [52] was used for this analysis . Congenic NOX2 knock-out mice [19] on a C57BL/6 J background were purchased from the Jackson Laboratory ( B6 . 129S-Cybbtm1Din/J ) . For prion inoculations , littermates were obtained by breeding heterozygous Nox2+/- females with Nox2+/Y or Nox2-/Y males . For organotypic cerebellar slice cultures and microglia depletion experiments , tga20/TK pups were obtained by breeding tga20tg/tg Prnpo/o males on a B6129 mixed background to heterozygous congenic CD11b-HSVTK females on a C57BL/6 background [18] . For titration experiments , ICR ( CD-1 ) and C57BL/6 mice were purchased from Harlan laboratories . Mice were bred in high hygienic grade facilities and housed in groups of 3–5 , under a 12 h light/12 h dark cycle ( from 7 am to 7 pm ) at 21±1°C , with sterilized food ( Kliba No . 3431 , Provimi Kliba , Kaiseraugst , Switzerland ) and water ad libitum . Genomic DNA was purified from tail biopsies using the Gentra Puregene Mouse Tail Kit ( Qiagen ) according to manufacturer's instructions . Whole-genome SNP analysis was performed using the Illumina Mouse MD Linkage Panel array ( Taconic Laboratories ) and results were compared with data from reference strains ( 129S6/SvEvTac , C57BL/6JBomTac , C57BL/6NTac ) . Inoculum of the 22 L strain of mouse-adapted scrapie prion was prepared from pooled 10% w/v brain homogenates of 22 L terminally sick CD-1 mice . Titration experiments were then performed by inoculating intracerebrally C57BL/6 recipients with serial dilutions of the 22 L inoculum . Infectivity titer ( S2 Table ) was calculated using the statistical method of Karber [53] . Wild-type and NOX2-deficient mice ( 8–10 weeks old ) were injected intracerebrally with 30 µl of brain homogenate prepared in a solution of PBS/5% BSA , containing 7 log LD50 units or 3 log LD50 units of the 22L strain . Control mice received 30 µl of NBH derived from healthy CD-1 mice . Different sessions of inoculations were performed using aliquots of the same diluted inoculum depending on mouse availability . In each session littermates from both genotypes were used and allocation to experimental groups was performed before inoculation , in a randomized way . Prion-infected mice were sacrificed at 4 , 8 , 12 and 16 weeks post-inoculation ( wpi ) or at terminal stage , when they displayed typical clinical signs of the disease . The operator was blind to the genotypes . The rotarod test was used to assess motor coordination and balance at different time points after prion inoculations . The rotarod apparatus ( Ugo Basile ) consisted of five cylinders ( 3 cm diameter ) separated by dividers ( 25 cm diameter ) in five lanes , each 57 mm wide . During the habituation phase , mice were placed on the rotating drum ( 4 rpm lowest speed ) for 3 sessions lasting 1–2 minutes each and separated by 10-minute intervals . Test phase started 30 minutes after the last habituation session , and consisted of 3 trials separated by 15-minute inter-trial intervals . Each test session lasted for a maximum of 5 minutes while the rod accelerated from 5 to 40 rpm . Latency to fall was determined when the mouse was no longer able to ride on the accelerating rod because slipping from the drum or clinging to the rod and rotating with it . Experiments were always performed at the same time of the day ( between 10 am and 12 am ) , mice were tested in a randomized way and the operator was blind to the genotypes . Western blotting analyses were performed on brain tissue samples or COCS as previously described [46] . For specific detection of partially protease-resistant prion proteins PrPSc , proteinase K ( PK; Roche ) digestion was performed ( 25 µg ml−1 PK for 20 µg protein lysate in a total volume of 20 µl ) . The following primary antibodies were used: NOX2 ( 1∶300 , BD Bioscience ) , IBA1 ( 1: 5000; Wako ) ; POM1 ( 200 ng ml−1; [54] ) : Actin ( 1∶15000 , Millipore ) . Total RNA was extracted using the RNeasy Universal Plus Mini kit ( QIAGEN ) according to manufacturer's instructions . Genomic DNA was removed with the gDNA eliminator solution ( provided in the same kit ) . cDNA was synthesized using 1 µg of RNA with the PrimeScript RT Reagent Kit with gDNA eraser ( Takara Bio Inc . ) . Real-time PCR was performed in optical 384-well plates , in triplicates , using a Prism 7900 HT sequence detection system ( Applied Biosystems ) and the SYBR green master mix ( Applied Biosystems ) . Raw Ct values were used to calculate relative expression levels of target genes , normalized according to geNorm analysis [55] to the housekeeping genes Gapdh , Rps9 and Eef1a1 . The following primers were used: Nox2 forward 5′-CAGGAACCTCACTTTCCATAAGATG-3′; Nox2 reverse 5′-AACGTTGAAGAGATGTGCAATTGT-3′; Prnp forward 5′-GCTGGCCCTCTTTGTGACTA-3′; Prnp reverse 5′-CTGGGCTTGTTCCACTGATT-3′; Gapdh forward 5′-TCCATGACAACTTTGGCATTG-3′; Gapdh reverse 5′-CAGTCTTCTGGGTGGCAGTGA-3′; Rps9 forward 5′-GACCAGGAGCTAAAGTTGATTGGA-3′; Rps9 reverse 5′-TCTTGGCCAGGGTAAACTTGA-3′; Eef1a1 forward 5′-TCCACTTGGTCGCTTTGCT-3′; Eef1a1 reverse 5′-CTTCTTGTCCACAGCTTTGATGA-3′ . Cerebellar organotypic slices were prepared from 10–11-days-old tga20/TK pups , treated with prions or NBH , cultured and processed for Western blotting or quantitative Real-Time PCR as previously described [46] . Microglia were depleted from slice cultures by adding ganciclovir from 0 to 21 days in vitro [18] , [46] . Slices were harvested at 42 days post-inoculation for Western blotting or qPCR analyses ( described above ) . PrPC was quantified in brain tissue homogenate by sandwich ELISA using POM1 and POM2 antibodies as described previously [54] . Stainings were performed on sections from brain tissues fixed in formalin , treated with concentrated formic acid to inactivate prions , and embedded in paraffin . After deparaffinization through graded alcohols and heat-induced antigen retrieval in citrate buffer ( 0 . 01 M; pH 6 ) , sections were incubated with the following antibodies: anti-human NOX2 ( 1∶250 , Clone 48 , Sanquin ) , GFAP ( 1∶1000 , Millipore ) , IBA1 ( 1∶2500 , WAKO ) , MAP2 ( 1∶500 , Abcam ) , NF ( 1∶1000; Abcam ) . Single stainings were visualized using DAB ( Sigma-Aldrich ) and H2O2 ( Sigma-Aldrich ) , after incubation with a biotinylated secondary antibody ( Vector Laboratories ) and the ABC complex solution ( Vector laboratories ) . Hematoxylin counterstain was subsequently applied . Double stainings were performed with fluorescently-labeled secondary antibodies ( 1∶1000 , Alexa Fluor 488 or 555; Invitrogen ) , followed by DAPI ( Life technologies ) nuclear staining . Partially protease-resistant prion protein deposits were visualized by staining brain sections with the SAF84 antibody ( 1∶200 , SPI bio ) , on a NEXES immunohistochemistry robot ( Ventana instruments ) using an IVIEW DAB Detection Kit ( Ventana ) , after preceding incubation with protease 1 ( Ventana ) . Images of DAB stained sections were acquired using the NanoZoomer scanner ( Hamamatsu Photonics ) and NanoZoomer digital pathology software ( NDPview; Hamamatsu Photonics ) . Quantifications of NOX2 staining in patient sections or IBA1 , GFAP and vacuoles in mouse sections were performed on acquired images , where regions of interest were drawn on a Digital Image Hub ( Leica Biosystems ) . The percentage of brown/white staining and the number of brown/white objects s over the total area were quantified using in-house–developed software . For the analyses , the computational algorithms were implemented using the C++ programming language and the OpenCV library ( source code is available upon request ) . Operators were blind to the pathology and to the genotype of the analyzed sections . Images of fluorescent stainings were acquired with the confocal CLSM Leica SP5 ( Leica Microsystems ) . Images were analyzed using the following image-processing softwares: Imaris ( Bitplane ) , Adobe Photoshop and Adobe Illustrator . In order to measure the production of ROS in vivo , we used the DHE probe ( Sigma-Aldrich ) following a previously published protocol [27] with minor modifications . Mice were injected i . p . with 200 µl DHE ( 3 mM ) solution . After 30 minutes of incubation , brain tissues were harvested , snap frozen in liquid nitrogen and stored at −80°C . Brain samples were homogenized in a buffer containing 50 mM KH2PO4 , 1 mM EGTA and 150 mM sucrose . For quantification of DHE oxidation products , fluorescence was detected in 250 µl 2% ( w/v ) tissue sample homogenates using a fluorimeter ( Ex/Em 485/585 , cutoff: 570 ) . Relative fluorescence units were normalized to protein concentration , determined by bicinchoninic acid assay ( Pierce ) . Comparison between two groups was assessed with the two-tailed unpaired Student's t test , whereas multiple comparisons were assessed with the one-way ANOVA or two-way ANOVA followed by Bonferroni's post-hoc test . General linear mixed model was used to analyse rotarod data . Kaplan-Meier method was used to analyze incubation times and comparison between groups was made with the log-rank test . GraphPad and IBM SPSS Softwares were used for analysis and p-values <0 . 05 were considered statistically significant . For statistical analysis , logarithm transformation was performed of numerical data in fig . 1K , and square root transformation of numerical data in fig . 3B . The details of each analysis ( statistical test , p-values , n ) are indicated in the figure legends .
The deposition of misfolded , aggregated prion protein in the brain causes transmissible spongiform encephalopathies ( TSE ) , a group of disorders including Creutzfeldt–Jakob disease and mad cow disease . TSE are characterized by neurodegeneration and progressive , lethal neurological dysfunction . Signs of oxidative damage are found in TSE , implying excessive production of reactive oxygen species ( ROS ) , yet their source is unclear . Here , we analyzed the role of the NADPH oxidase enzyme , NOX2 , in prion pathogenesis . NOX2 is a membrane-bound electrochemical pump that generates ROS . We found that NOX2 is upregulated in the brains of patients with Creutzfeldt-Jakob disease and of prion-infected mice . Interestingly , NOX2 ablation led to abrogation of ROS production in mice inoculated with prions , and was associated with a milder clinical course of the disease and increased life expectancy . We conclude that NOX2 is a relevant contributor to the excessive production of ROS . This study spawns the possibility that inhibiting NOX2 activation might help attenuate prion disease progression – a legitimate and important goal even if there is little reason to expect anti-NOX2 therapies to be curative .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "and", "health", "sciences", "oxidative", "stress", "neurodegenerative", "diseases", "microglial", "cells", "animal", "models", "model", "organisms", "veterinary", "science", "research", "and", "analysis", "methods", "veterinary", "diseases", "zoonoses", "animal", "cells", "mouse", "models", "glial", "cells", "cell", "biology", "neurology", "biology", "and", "life", "sciences", "creutzfeldt-jakob", "disease", "cellular", "types", "prion", "diseases" ]
2014
The Role of the NADPH Oxidase NOX2 in Prion Pathogenesis
Herpes simplex virus type 2 ( HSV-2 ) increases the risk of HIV-1 infection and , although several reports describe the interaction between these two viruses , the exact mechanism for this increased susceptibility remains unclear . Dendritic cells ( DCs ) at the site of entry of HSV-2 and HIV-1 contribute to viral spread in the mucosa . Specialized DCs present in the gut-associated lymphoid tissues produce retinoic acid ( RA ) , an important immunomodulator , able to influence HIV-1 replication and a key mediator of integrin α4β7 on lymphocytes . α4β7 can be engaged by HIV-1 on the cell-surface and CD4+ T cells expressing high levels of this integrin ( α4β7high ) are particularly susceptible to HIV-1 infection . Herein we provide in-vivo data in macaques showing an increased percentage of α4β7high CD4+ T cells in rectal mucosa , iliac lymph nodes and blood within 6 days of rectal exposure to live ( n = 11 ) , but not UV-treated ( n = 8 ) , HSV-2 . We found that CD11c+ DCs are a major target of HSV-2 infection in in-vitro exposed PBMCs . We determined that immature monocyte-derived DCs ( moDCs ) express aldehyde dehydrogenase ALDH1A1 , an enzyme essential for RA production , which increases upon HSV-2 infection . Moreover , HSV-2-infected moDCs significantly increase α4β7 expression on CD4+ T lymphocytes and HIV-1 infection in DC-T cell mixtures in a RA-dependent manner . Thus , we propose that HSV-2 modulates its microenviroment , influencing DC function , increasing RA production capability and amplifying a α4β7highCD4+ T cells . These factors may play a role in increasing the susceptibility to HIV-1 . Herpes Simplex Virus Type 2 ( HSV-2 ) infects genital and perianal mucosa and its infection is associated with a three-fold increased risk of HIV-1 acquisition among both men and women [1] . Although active HSV-2 shedding , inflammation and ulcers during primary infections and virus reactivation certainly contribute , their resolution by suppressive therapy with acyclovir is not effective in reducing HIV-1 acquisition in HSV-2 seropositive individuals [2] . One possible explanation for the HSV-2-driven increased risk of HIV-1 acquisition is the persistence of HSV-2-reactive CD4+ T cells long after HSV-2 replication abates [3] . Likewise , plasmacytoid and myeloid dendritic cells ( DCs ) , which infiltrate areas of skin infected with HSV-2 , persist after lesion healing also in the context of acyclovir therapy [3] and may contribute to the increased risk of HIV-1 acquisition associated with HSV-2 infection . Epithelial cells are primary targets of HSV-2 infection . Nonetheless , DCs , which orchestrate the immunological response to HSV-2 at its portal of entry , can also be infected in-vitro . In fact immature monocyte-derived DCs ( moDCs ) and langerhans cells found at the epithelial surfaces are highly susceptible to HSV-2 [4] , [5] , [6] , [7] . Importantly , HSV-2 infection of DCs in-vitro has been shown to inhibit their maturation and immunostimulatory functions [5] , [6] , [8] , [9] and in-vivo HSV-2 infection reduces HIV-1 specific T cell responses [6] , [10] , [11] . Cellular microenvironment is vital to conditioning cell function and , in particular , the expression of receptors that affect cell trafficking . Specialized DCs in mesenteric lymph nodes ( MLNs ) and Peyer's patches ( PPs ) convert vitamin A to retinoic acid ( RA ) [12] , a key factor in the control of lymphocyte trafficking and immune responses and able to influence HIV-1 replication [13] , [14] , [15] . In particular , RA has the unique capacity to imprint a “gut-phenotype” on T cells , which includes increased expression of integrin α4β7 [12] . The mucosal homing receptor α4β7 is the signature molecule that allows lymphocytes to gain access to the gut tissue [16] , [17] , a major site of HIV-1 replication [18] . A recent study in macaques has shown that pre-treatment with an anti-α4β7 antibody significantly reduces and delays peak plasma SIV load , increases the percentage of CD4+ T cells both in peripheral blood and in gut tissues and reduces proviral DNA in blood and gut tissues mononuclear cells [19] . A specific interaction between α4β7 and the HIV-1 envelope protein , gp120 , has been described [20] and additional evidence shows that α4β7 co-localizes with the two main HIV-1 entry receptors CD4 and CCR5 [21] , [22] . The site of gp120 binding to α4β7 is conserved across gp120s from the four major HIV-1 subtypes [20] . The conserved nature of this interaction suggests that engaging α4β7 provides a selective advantage to HIV-1 . Indeed , α4β7 is expressed at high levels on a subset of CD4+ T cells that are particularly susceptible to infection and it has been proposed that the specific affinity of HIV-1 gp120 for α4β7 provides a way for HIV-1 to target susceptible cells at an early stage of transmission [21] . Notably , very high reactivity for α4β7 is a characteristic shared by early transmitted isolates , in contrast with the poor reactivity of viruses isolated longer after transmission [23] . Once HIV-1 crosses the epithelium , they have to replicate at a reproductive rate R0>1 [24] . Expansion of the virus within the mucosa is necessary to disseminate infection to draining LNs and blood in order to establish a productive systemic infection . The relevance of the HIV-α4β7 interaction in the context of mucosal transmission has yet to be elucidated . The synthesis of RA includes two main steps . During the first step vitamin A ( retinol ) is converted to retinaldehyde . This reaction is catalyzed by a subfamily of alcohol dehydrogenases that are expressed in most cells including DCs or by the short-chain dehydrogenase/reductase family [12] , [25] , [26] . The second , limiting step , is catalyzed specifically by aldehyde dehydrogenase 1A ( ALDH1A ) [retinal dehydrogenase] which converts retinaldehyde to RA . ALDH1A-expression in-vivo does not appear to be restricted to intestinal DCs and intestinal epithelial cells as previously suggested [25] , [27] , [28] . ALDH1A can be expressed by LN stromal cells [29] , [30] and ALDH1A expressing-RA-producing DCs are present in skin , lung and in their draining LNs [31] . Moreover , RA production can be induced in-vitro in splenic and bone marrow-derived DCs ( BM-DCs ) [32] . In this regard , the granulocyte-macrophage colony-stimulating factor ( GM-CSF ) and stimulation with toll-like receptor ( TLR ) ligands appear to play an important role [32] , [33] . This raises the possibility that ALDH1A can be expressed and induced in DCs in various tissues outside of the intestine . The present work shows that rectal HSV-2 infection of macaques increases the percentage of α4β7highCD4+ T cells in rectal tissue and draining LNs , as well as systemically . We found that immature moDCs express ALDH1A and this is upregulated by HSV-2 infection . Therefore , HSV-2 increases DC's ability to produce RA . In turn HSV-2 infected moDCs , induce α4β7 expression expanding the α4β7high CD4+ T subset through an RA-dependent mechanism . Importantly , HSV-2 infected moDCs increase HIV-1 replication in DC-T cell co-cultures in an RA-dependent manner . Herein , we describe a mechanism that HSV-2 could exploit to condition its environment , influencing not only its own replication but , possibly , that of a co-pathogen such as HIV-1 . Non-human primate models constitute crucial tools to explore mucosal infection with HIV-1/SIV , elucidate the early events after HIV-1 transmission and how these events are impacted by other sexually transmitted infections ( STIs ) . We recently developed a unique model of vaginal HSV-2 infection in rhesus macaques in which HSV-2-infected macaques exhibited increased susceptibility to immunodeficiency virus ( simian-human immunodeficiency virus , SHIV-RT ) infection , even in absence of obvious lesions [10] . Building on this , we established a macaque model of HSV-2 rectal infection and we used this model to investigate early events after HSV-2 infection across the mucosa . Clinically stable SHIV-RT-infected animals were challenged intra-rectally with 2×108 pfu of replication competent ( LIVE; n = 11 ) or UV-inactivated ( UV-HSV-2; n = 8 ) HSV-2 . UV inactivated HSV-2 ( matched to the input infectious virus dose prior to inactivation ) was used to distinguish effects due to exposure to viral proteins and nucleic acids from the effects due to viral replication . Baseline CD4 counts and plasma SHIV RNA levels are listed for each animal in ( Table S1 ) . Blood and rectal fluids were collected before ( BL ) , 3 and 6 days after challenge . Axillary , mesenteric , inguinal and iliac LNs , as well as rectal tissue were collected following euthanization 6 days after challenge . HSV-2 DNA levels were measured in the rectal fluids at BL ( 4 days and 24 h prior to HSV-2 challenge . 24 h is shown in Table S1 ) versus 3 and 6 days post-challenge by a sensitive nested HSV-2 PCR [10] . HSV-2 shedding was detected in 9 of the 11 animals challenged with live HSV-2 on days 3 and 6 post-challenge ( Table S1 ) . One animal was negative on day 6 and unable to be tested on day 3 and one was negative on day 3 and unable to be tested at day 6 . As a result , these animals were excluded from subsequent analyses since their HSV-2 status was unclear . No DNA shedding was detected in the animals treated with UV-HSV-2 , nor in any animals prior to challenge . Not surprisingly , CD4 counts and plasma SHIV RNA did not show significant changes from baseline 6 days after exposure to live or UV-inactivated HSV-2 ( Table S1 ) . Previous studies have shown that the α4β7highCD4+ T cells constitute a subset of central memory cells [21] , [22] and this was similarly observed in the present study ( Figure 1A ) . In blood of macaques infected intra-rectally with HSV-2 we detected a significantly higher percentage of α4β7high T cells within the CD4+CD95+ memory cell subset than before challenge and than in macaques challenged with UV-HSV-2 ( Figure 1B ) . The frequency of CD4+CD95+α4β7high T cells was also higher in the rectal mucosa of the HSV-2 infected macaques than in the UV-HSV-2 treated ones . ( Figure 1C; S1 shows the gating strategy ) . The percentage of α4β7high cells in the CD4+ T cell memory subset was also significantly increased in the draining iliac LNs of HSV-2 infected macaques ( Figure 1D ) . As expected , the gut-draining MLNs had the highest percentage of α4β7highCD4+ T cells and , together with the low levels in the distal axillary LNs , they were unaffected by HSV-2 infection ( Figure 1D ) . Of note , the inguinal LNs of infected macaques also had a higher frequency of α4β7high cells than the UV-HSV-2 treated animals . Although this difference was not significant , finding that inguinal LNs of UV-HSV-2-treated macaques had a significantly lower percentage of α4β7high cells than the MLNs while this different was not significant in the live-HSV-2 treated ones , suggests that inguinal LNs of the HSV-2 infected macaques are also enriched in α4β7highCD4+ T cells ( Figure 1D ) . All together , these data suggest that HSV-2 infection is either recruiting α4β7high T cells to the infected mucosa and in draining LNs , or it is driving an up-regulation of α4β7 on T cells resident at the site of infection . In mucosal tissues α4β7 is up-regulated on T cells by RA produced by local DCs , therefore we set out to explore the possible involvement of DCs in the HSV-2-driven up-regulation of α4β7 in the rectally challenged macaques . While epithelial cells are the primary targets of HSV-2 infection , human and macaque moDCs are susceptible to HSV-2 in-vitro [4] , [5] , [6] , [7] . Rationalizing that HSV-2 is interacting with a mixed population of leukocytes in-vivo , we used peripheral blood cells to examine which cells become infected by HSV-2 upon exposure in-vitro . Using a flow cytometric assay able to detect the HSV-2 early DNA binding protein ICP-8 intracellularly in infected cells , we determined that 24 h after exposure to HSV-2 ( 5 MOI ) , on average , 0 . 15% [range 0 . 08–0 . 39%] of total live cells were ICP-8+ , 91 . 3% [range 82–99%] of the ICP-8+ were Lineage− ( Lin− ) and 71% [range 62–95%] of the Lin−ICP-8+ were HLA-DR+CD11c+ ( Figure 2B ) . Cell viability was always in the range 90–95% in human PBMCs and 50–80% in macaques and was not affected by HSV-2 infection . Although fewer , ICP-8+CD11c+ DCs were detected also after exposure to only 0 . 2 MOI of HSV-2 ( not shown ) . Therefore , CD11c+ myeloid DCs were found to be the cell subset most susceptible to HSV-2 infection in human and macaque peripheral blood mixed leukocyte populations , supporting the possibility that HSV-2 infection of DCs plays a role in-vivo . In order to dissect this biology more extensively , we utilized the moDC system . Prior studies demonstrated that moDCs infected with HSV-2 at a MOI of 5 undergo rapid apoptosis [6] , [34] . In order to explore the possibility that HSV-2 infection of DCs is involved in the up-regulation of α4β7 on CD4+ T on cells , we evaluated the effect of a low-level ( minimally toxic ) HSV-2 infection of DCs and how this influences DC-T cell interplay . We monitored infection of immature moDCs exposed to varying doses of HSV-2 by ICP-8 intracellular staining and we observed a dose-dependent infection that increased over time ( Figure 3A ) . Annexin V/propidioum Iodide ( PI ) and the LIVE/DEAD discriminator marker Aqua were used to determine cell viability [35] . The percentage of Annexin V− cells was similar to the percentage of Aqua negative cells , which represents our viable cell population . Therefore , we chose to use the LIVE/DEAD Aqua throughout the following studies . On average 80% [range 76–85%] and 55% [range 44–58%] of the moDCs were viable after infection with 0 . 2 and 1 MOI of HSV-2 ( respectively ) , but there was little/no death of cells infected with 0 . 04 MOI ( Figure S2 ) . From these data we determined that the 0 . 2 MOI inoculum was lowest amount of virus giving reliable infection while leaving the majority of cells healthy and able to interact with T cells for our DC-T cells experiments . Infections with higher doses of HSV-2 have been shown to have immunosuppressive effects on DCs [5] , [6] . Therefore , changes in DC surface phenotype and cytokine/chemokine ( CK/CC ) profiles were monitored after HSV-2 infection with this lower inoculum . There were no significant differences in the expression of the surface markers and in the concentration of the CCs/CKs released by moDCs 4 h after exposure to infectious ( live ) or UV-HSV-2 ( versus mock infected DCs; data not shown ) . Although the expression of CD80 , CD83 , CD40 and CD25 were comparable between the differently treated groups ( data not shown ) , the expression of HLA-DR , CD86 , CD209 and CD54 were all significantly reduced 24 h after HSV-2 infection ( Figure 3B ) . HLA-DR was significantly lower in the ICP-8+ ( infected ) fraction of the cells exposed to infectious HSV-2 , compared to the ICP-8− ( undetectable uninfected or low-level infected ) subset . CD86 , CD209 , and CD54 were significantly reduced in the ICP-8+ cells compared to ICP-8− cells within the infected population , as well as compared to the UV-HSV-2 and mock-treated controls . Low level HSV-2 infection of human moDCs did not alter the release of IL1β , IL1RA , IL-5 , CXCL8 , IL-10 , IL-12p40 , IL-13 , IL-15 , IL-17 , IFNα , IFNγ , CCL2 , CCL3 , CCL4 , CXCL9 , CCL11 , CCL5 ( data not shown ) . However , the levels of IL-2 , IL-2R , IL-6 , IL-7 , TNFα , and CXCL10 were significantly increased in the HSV-2 infected DC cultures ( Figure 3C ) . Notably , the amount of CXCL10 in the supernatants of HSV-2 infected DCs was , on average , 25 fold [95%CI 5–45] higher than both UV-HSV-2 and mock-infected cells . Overall , these results indicate that the infection of moDCs with 0 . 2 MOI of HSV-2 minimizes apoptosis in the first 24 h post infection ( p . i . ) , retaining the ability of HSV-2 infection to modulate DC phenotype and function . This allowed us to study how the HSV-2 driven changes on DCs influence the DC-T interplay . CD4+ T cells cultured for 5 days with autologous DCs can be divided in 4 subsets on the basis of their expression of α4β7 . While α4β7low T cells ( LOW ) are naïve T cells , α4β7int ( INT ) , α4β7high ( HIGH ) and α4β7neg present a memory phenotype ( Figure 4A and S3 ) . After 5 ( and 7 , not shown ) days of culture , the percentage of α4β7high T cells was significantly increased in HSV-2-infected DC-T cell co-cultures ( Figure 4A and B ) , while there was no significant difference in the α4β7int and α4β7low ( not shown ) . In contrast , CD69 expression was significantly reduced in co-cultures with HSV-2-infected DCs , ( relative to the mock and UV-treated cells; Figure 4A and C ) . It has been shown that the expression of α4β7 on naïve T cells is enhanced upon antigenic stimulation with MLN-DCs and PP-DCs [12] . Therefore , the small , non-significant increase in α4β7 expression seen in the UV-HSV-2 condition could be explained by stimulation of TLRs due to HSV-2 proteins and nucleic acids , the amount of which would be increased in cultures with replicating virus . However , even treatment of moDCs with 25 fold more UV-HSV-2 ( equivalent to an MOI of 5 ) , did not significantly alter the α4β7 expression on the CD4+ T cells , but increased CD69 expression even further ( Figure S4 A and B ) . T cells cultured alongside in the absence of DCs , but in the same amounts of live-HSV-2 used to treat the DCs ( 0 . 2 MOI ) , did not show evidence of infection ( Figure S5 A ) , alteration of viability status ( not shown ) or changes in the expression of α4β7 ( Figure S5 B ) 5 days p . i . However , as previously reported [36] , T cells treated with a higher inoculum are susceptible to HSV-2 infection , as demonstrated by the detection of ICP-8+CD4+ T cells after exposure to 5 MOI of HSV-2 ( Figure S5 A ) . T cell viability and expression of α4β7 remained unchanged after exposure to the higher dose of HSV-2 ( Figure S5 B ) . On the contrary , expression of CD69 was significantly up-regulated on the T cells 5 days post HSV-2 infection both in cells infected with 0 . 2 and 5 MOI ( Figure S5 C ) . Since RA is known to increase α4β7 expression in T cells , a selective RA receptor ( RARα ) antagonist [37] was included in the co-cultures . The RARα antagonist blocked the HSV-2-infected DC-induced up-regulation of α4β7 on the T cells ( Figure 4B ) . The slight increase in α4β7high cells in the UV-HSV-2-treated compared to mock-infected DC-T cell co-cultures was also blocked ( Figure 4B ) . The RARα antagonist reduced α4β7 also on the mock-infected DC-T co-cultures , although its effect was much less pronounced than in the HSV-2 infected and UV-HSV-2 DC-T cell co-cultures ( Figure 4B ) . Of note , CD4+ T cells cultured for 5 days in absence of moDCs , but in the same culturing conditions as the DC-T cell co-cultures , expressed a lower level of α4β7 than in presence of mock , UV-HSV-2 and HSV-2 moDCs and the antagonist had no effect on its expression ( Figure 4B ) . The RARα antagonist did not alter the CD69 expression ( Figure 4C ) , suggesting that its effect was highly specific , did not generically alter the viability status of the cells , and that RA is not involved in the reduced CD69 expression by the T cells . These data demonstrate that RA is at least partially responsible for inducing expression of α4β7 on the CD4+ T cells . The irreversible enzymatic conversion of retinaldehyde to all-trans-RA by ALDH1A [RALDH] constitutes the limiting step in the production of metabolically active RA . There are 3 main isoforms of ALDH1A . ALDH1A1 [RALDH1] is expressed by DCs in PPs and by epithelial cells of the intestine , while ALDH1A2 [RALDH2] is expressed in MLNs [12] . ALDH1A3 is expressed at much lower levels in both PPs and MLNs . Peripheral LNs express ALDH1A2 but at a barely detectable level [12] . Murine BM-DCs , differentiated in GM-CSF and IL-4 , express ALDH1A2 [32] . We investigated whether human moDCs express ALDH1A and if the expression of α4β7 on T cells in the DC-T cell co-cultures could be related to a de-novo production of RA by the DCs . We found that immature moDCs express ALDH1A1 and ALDH1A2 , but not ALDH1A3 ( Figure 5A ) . A relative quantification of the expression levels by RT-qPCR indicated that HSV-2 infection significantly increased the expression of ALDH1A1 compared to the UV-HSV-2- and mock-treated controls ( Figure 5B ) . It has been shown that TLR ligands enhance ALDH1A2 expression in BM-DCs [32] . However , although the UV-HSV-2-treated moDCs expressed higher level of ALDH1A1 compared with the mock-treated cells , this difference was not significant . Moreover , the treatment with 25-fold more UV-HSV-2 did not significantly up-regulate ALDH1A1 in immature moDCs ( Figure S6 A ) . We also found that generic aldehyde dehydrogenase activity ( ALDH ) increases significantly in HSV-2-infected moDCs compared with the UV-HSV-2 treated and mock-treated controls ( Figure 5C and D ) . Because the assay measuring ALDH activity could not be used in combination with ICP-8 intracellular staining we could not distinguish if the increased ALDH activity was restricted to the HSV-2 infected cells , or if there was contribution from bystander non-infected cells . Thus , these data indicate that human moDCs have the potential to produce RA and that replication competent HSV-2 induces increased expression of the rate-limiting enzyme that converts retinaldehyde to RA . Previous studies showed that RA profoundly affects HIV-1 replication in-vitro [13] , [14] , [15] . Having shown that HSV-2-infected DCs increase the percentage of α4β7high T cells through an RA-dependent mechanism , we evaluated the impact of HSV-2 infection of immature moDCs on HIV-1 replication in DC-T cell mixtures . HSV-2-infected ( versus UV-HSV-2- and mock-treated DCs ) were pulsed with the CCR-5 tropic HIV-1 ADA-M , extensively washed and then mixed with autologous CD4+ T cells . HSV-2 infection of DCs significantly increased HIV-1 infection in CD4+ T cells in the DC-T cell co-cultures ( Figure 6A–C ) . Although there was high variability in the level of HIV-1 infection and enhancement from donor to donor , the HSV-2-driven increase was consistent and in 1 out of 15 experiments reached a 100-fold increase compared to the mock condition . We found a modest increase in HIV-1 replication of UV-HSV-2-treated DC-T cell co-cultures compared with the mock condition , but this was not statistically significant when data from multiple donors was evaluated ( Figure 6B ) . However , higher amounts of UV-HSV-2 induced higher HIV-1 replication ( Figure S6 B ) , paralleling the increased CD69 expression seen in these cultures ( Figure 4C and S4 B ) . As previously suggested [21] , [22] , the α4β7highCD4+ T cells are highly susceptible to HIV-1 infection , as evidenced by p24 expression in the various T cell subsets ( Figure 6C ) . Specifically , the percentage of p24+ cells in the α4β7high subset was always higher than in the α4β7int subset [1 . 6 fold , 95%CI: 1 . 1–2 . 1] , than in the α4β7low subset [4 . 8 fold , 95%CI: 1 . 5–8 . 2] and than in the α4β7neg subset [2 . 8 fold , 95%CI: 2 . 4–3 . 2] ( Figure 6C ) . In all experiments , the greater difference between the α4β7high and the other subsets was found in the HSV-2-infected DC-containing cultures . Since T cells can be infected with HSV-2 ( Figure S5 A and [36] ) , we examined the effect of HSV-2 infection of CD4+ T cells on HIV-1 replication ( in absence of DCs ) . We found a small increase in HIV-1 replication in the CD4+ T cells treated with replication competent HSV-2 compared to the mock condition similar to the increase in the UV control ( Figure S7 A ) , coincident with the increased CD69 expression within these cultures ( Figure S5 C ) . Next we tested the effect of the RARα antagonist on the HIV-1 infection in the DC-T cell cultures . Inclusion of the RARα antagonist blocked the increased HIV-1 replication seen in the presence of HSV-2-infected DCs , but had low or no impact on the HIV-1 replication in the mock- and UV-HSV-2-treated DC-T cell mixtures ( Figure 6D ) . With the exception of the experiment exhibiting 100-fold increase in HIV-1 replication , the RARα antagonist was able to inhibit infection to a level similar to that of the mock DC-T co-cultures ( Figure 6D ) . The RARα antagonist had no effect on low-level HIV infection of CD4+ T cells cultured in the absence of DCs ( Figure S7 B ) . These data confirm that HSV-2-infection of DCs augments HIV-1 replication in DC-T cell mixtures via an RA-dependent pathway . HSV-2 enhances HIV-1 acquisition and transmission during symptomatic and asymptomatic stages of HSV-2 infection [2] . However , due to the lack of a suitable animal model for HSV-2 infection that closely relates to humans , the underling mechanism ( s ) that leads to enhanced risk of HIV-1 infection remains unknown . One potential explanation holds that increased presence and persistence of HSV-2-reactive CD4+ T cells facilitate HIV-1 transmission [3] . Herein , we provide in-vivo data collected in a novel non-human primate model of HSV-2 infection and we describe in-vitro experiments that add new insights into HSV-2/HIV-1 interplay . In-vivo we observed an increase in the percentages of α4β7highCD4+ T cells both locally and systemically a few days after rectal HSV-2 challenge . We show that CD11c+ DCs from peripheral blood are susceptible to HSV-2 infection in-vitro and that HSV-2 infection of immature moDCs amplifies the α4β7high CD4+ T subset in autologous DC-T co-cultures . We show that HSV-2 infection increases ALDH1A1 expression in DCs , a phenomenon that enhances their potential to produce RA . The latter mediates the HSV-2-driven up-regulation of α4β7 in our DC-T co-cultures and has a plethora of immunomodulatory effects , including influencing HIV-1 replication [13] , [15] Indeed , we found that blocking the RARα in T cells inhibits HIV-1 replication in HSV-2-infected DC-T cell cultures . Localization , retention , function and survival of antigen-experienced T cells that infiltrate mucosal sites following pathogen invasion , are influenced by the expression of adhesion molecules , substantially modulated by microenvironmental factors [38] . Among such adhesion molecules , the integrin receptor α4β7 mediates lymphocyte migration to the gastrointestinal tract . However , recent findings indicate that STIs can modulate the expression and migration of α4β7+ lymphocytes also in other tissues , such as the endocervix of human females infected with Clamydia trachomatis [39] , [40] . We developed a macaque HSV-2 rectal infection model and show that in macaques the mucosal site of HSV-2 infection , its draining LNs , and blood are enriched in α4β7high T cells within 6 days of HSV-2 exposure . The increased percentages of α4β7high T cells were not observed in animals treated with UV-HSV-2 , suggesting that HSV-2 replication is important to this phenomenon . Several factors could explain the enrichment in α4β7high T cells at the site of HSV-2 infection . Among them is the ability of α4β7high T cells to specifically target mucosal sites , a possible inflammation-driven induction of the α4β7 receptor MadCam [41] , [42] , and specific responses of CM T cells to inflammatory soluble factors . However , DCs are present and persist at the site of HSV-2 infection [3] , they are critical to the immunological response to HSV-2 [43] , [44] , [45] and are able , in determinate circumstances , to induce α4β7 on T cells . Therefore , we explored the possibility of their contribution to the increased percentage of α4β7high T cells in HSV-2-infected macaques . HSV-2 is able to skew DC immunological responses [5] , [6] , [46] . While moDCs and langerhans cells are highly susceptible to HSV in-vitro [4] , [5] , [6] , [7] , plasmacytoid DCs , critical players in the innate response to HSV [47] , seem to be resistant to infection [48] . CD11c+ myeloid DCs are important in antigen presentation and adaptive response to HSV [45] . Mimicking the mixed leukocyte populations potentially encountering HSV-2 in-vivo using blood , we confirmed that ( macaque and human ) myeloid CD11c+ DCs are the primary leukocyte target for HSV-2 infection in-vitro . Due to the variety of CD11c+ DC subsets implicated at different stages of the immune response [44] future studies will need to investigate the precise phenotype of the susceptible population , the differences between HSV-2-infected in-vitro generated moDCs , and infected CD11c+ DCs in their interaction with T cells . Since the primary goal of this study was to explore whether modulation of myeloid DC function by HSV-2 infection was involved in the enrichment of α4β7high T cells observed in-vivo , we were able to use the established moDC-HSV-2 model to dissect this biology . The effect of HSV-2 infection on moDCs has been extensively studied , typically using relatively large amounts of virus [4] , [5] , [6] , [7] . Our work reveals that even a much smaller viral inoculum significantly influences DC biology . We confirmed that low dose HSV-2 infection caused a down-regulation of the maturation receptors HLA-DR , CD86 and CD54 , as seen with higher HSV-2 doses [49] , [50] . We also demonstrated a down-regulation of CD209 , which would be expected in a maturing DC . The latter can be explained by the ability of HSV to bind this receptor [7] , although it could be also the result of a skewed maturation process . We demonstrated that DCs infected with a low HSV-2 inoculum down-modulated CD69 expression on T cells , supporting an earlier report that HSV-infected moDCs inhibit T cell activation . Notably , we found that HSV-2-infected DCs up-regulate the expression of α4β7 and , by blocking the binding of RA to its receptors on the CD4+ T cells , we showed that RA was directly involved in the HSV-2 driven increase in α4β7 expression . RA impacts several immunological mechanisms , in particular it is known to induce a mucosal-type phenotype in DCs [51] , playing an important role in inducing and sustaining the tolerogenic microenvironment of the gut [25] . We provide the first evidence that human immature moDCs express ALDH1A1 ( and ALDH1A2 ) , have the potential to convert serum retinol into RA , and that HSV-2 infection significantly increases this capability . This supports earlier work in mice showing that GM-CSF and IL-4 induce ALDH1A2 expression in BM-DCs [32] . The same study also reported that this gene was up-regulated by TLR ligands in DCs cultured with GM-CSF and IL-4 and matured with LPS . However , the up-regulation of ALDH1A1 expression by HSV-2 infection in human moDCs did not appear to be due a ligand effect of HSV-2 proteins or DNA ( triggering through TLRs ) , since even 25-times more UV-HSV-2 was unable to reproduce these responses . Additional studies are needed in order to ascertain whether other TLR ligands or other pathogens can stimulate human DCs ( like HSV-2 infection ) to up-regulate ALDH1A1 expression and subsequently increase α4β7 expression on CD4+ T cells . The specific mechanism through which HSV-2 infection increases ALDH1A1 expression in moDCs was not a major focus of this work and might be a direct effect of newly synthesized HSV-2 components and/or an indirect effect of CCs/CKs secreted by DCs in response to HSV-2 replication . Given the potentially important role that RA holds in immune responses to pathogens , this subject is worthy of further research . That HSV-2 is able to mediate the up-regulation of an enzyme that serves as a key metabolic checkpoint in the conversion of retinol to RA is noteworthy , because RA has the capacity to modulate immune responses and replication of many pathogens including HIV-1 [15] , [25] , [52] . These studies also revealed that significantly elevated amounts of other soluble factors are released by HSV-2-infected moDCs . In particular , we detected a notable increase in IL-7 , which is known to induce HIV-1 reactivation and replication in T cells [53] , [54] and , as previously reported [55] , of CXCL10 which is responsible of recruiting activated T cells , therefore contributing to viral replication in inflamed tissues [56] . All these factors could cooperate in enhancing HIV-1 infection . However , an RAR antagonist ablated the HSV-2-mediated enhancement of HIV-1 amplification , suggesting that RA is one of the major factors driving this biology . HIV-1 infection of moDCs could also be affected by HSV-2 infection . Though , the apoptotic nature of the HSV-2 infection , suggests little contribution of HIV-1 replication in moDCs to the enhanced HIV-1 replication in the co-cultures . We previously reported that α4β7high T cells are the most susceptible HIV-1 target in T cells cultures supplemented with RA and that blocking α4β7 binding to HIV-1 inhibits HIV-1 replication [20] , [21] . Herein , we show that the α4β7high T cells also constitute the most susceptible HIV-1 target in the DC-T cell co-cultures and that this is independent of the effect of HSV-2 on the DCs . Therefore , being particularly susceptible to HIV seems an intrinsic characteristic of α4β7highCD4+ T and an expansion of this cell-subset likely has a greater impact than the expansion of less susceptible subsets , contributing to fuel infection . This work gives us new insights into HSV-2 modulation of the mucosal microenvironment . A low- level HSV-2 infection of immature myeloid DCs could play a role in increasing the susceptibility to HIV-1 by influencing its surroundings in a way favorable to HIV-1 infection . In Figure 7 we try to integrate our findings in a bigger picture with the new different actors that HSV-2 infected DCs add to the scene . Further studies will have to dissect how these mechanisms interplay in-vivo , the respective role of factors such as RA and α4β7 and their relative importance in transmission across the rectal and genital mucosa . Adult female Chinese rhesus macaques ( Macaca mulatta ) were housed and cared for in compliance with the regulations under the Animal Welfare Act , the Guide for the Care and Use of Laboratory Animals , at Tulane National Primate Research Center ( TNPRC; Covington , LA ) . Animals were monitored continuously by veterinarians to ensure their welfare . Veterinarians at the TNPRC Division of Veterinary Medicine have established procedures to minimize pain and distress through several means . Monkeys were anesthetized with ketamine-HCl ( 10 mg/kg ) or tiletamine/zolazepam ( 6 mg/kg ) prior to all procedures . Preemptive and post procedural analgesia ( buprenorphine 0 . 01 mg/kg ) was required for procedures that would likely cause more than momentary pain or distress in humans undergoing the same procedures . The above listed anesthetics and analgesics were used to minimize pain or distress associated with this study in accordance with the recommendations of the Weatherall Report . Any sick animals were euthanized using methods consistent with recommendations of the American Veterinary Medical Association ( AVMA ) Panel on Euthanasia . All studies were approved by the Animal Care and Use Committee of the TNPRC ( OLAW assurance #A4499-01 ) and in compliance with animal care procedures . TNPRC is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care ( AAALAC#000594 ) . Immature moDCs were generated as previously described [6] . Briefly: Peripheral blood mononuclear cells ( PBMCs ) were isolated from heparinized human leukopacks ( New York Blood Center , New York , NY ) using Ficoll-Hypaque density gradient centrifugation ( Amersham Pharmacia Biotech , Uppsala , Sweden ) . CD14+ monocytes were isolated using the human CD14 magnetic cell sorting ( MACS ) system ( Miltenyi Biotec , Auburn , CA ) and moDCs generated by culturing these cells in 100 U/mL recombinant human interleukin-4 ( IL-4 ) ( R&D Systems , Minneapolis , MN ) and 1000 U/mL recombinant human granulocyte-macrophage colony-stimulating factor ( GM-CSF ) ( Berlex Laboratories , Montville , NJ ) . After 5 days , immature moDCs were collected , an aliquot taken for flow cytometric analysis ( BD FACSCAlibur ) of DC phenotype and maturation [FITC anti–HLA-DR , APC anti-CD25 , PE anti-CD80 , PE anti-CD83 , anti-CD86 , PE anti-CD3 ( see later for clones ) ] . moDC purity was greater than 98% . Cells were negative for CD80 and CD25; less than 1% of moDCs expressed CD83 . The remainder of the cells was used for HSV-2 infections . moDCs were cultured in R1 [RPMI 1640 ( Cellgro; Fisher Scientific , Springfield , NJ ) containing 2 mM L-glutamine ( GIBCO Life Technologies , Grand Island , NY ) , 10 mM HEPES GIBCO Life Technologies ) , 50 µM 2-mercaptoethanol ( Sigma Chemical , St Louis , MO ) , penicillin ( 100 U/mL ) /streptomycin ( 100 µg/mL ) ( GIBCO Life Technologies ) , and 1% heparinized human plasma] . Autologous CD14− cells were cultured 5 days in R10 [RPMI 1640 with 2 mM L-glutamine , 10 mM HEPES , 50 µM 2-mercaptoethanol , penicillin 100 U/mL/streptomycin and 10% of FBS] supplemented with 1 U/ml of IL2 ( Preclinical Repository , National Cancer Institute at Frederick , NCI-Frederick , MD ) at 20×106 cells/ml . The day before starting the DC-T culture , day 5 , CD4+ T cells were isolated using the human CD4 positive MACS system ( Miltenyi ) . CD4+ T cells were cultured overnight in R5 [RPMI 1640 with 2 mM L-glutamine , 10 mM HEPES , 50 µM 2-mercaptoethanol , penicillin 100 U/mL/streptomycin and 5% of human AB serum ( Sigma-Aldrich ) ] supplemented with 1 U/ml of IL2 , at 10×106 cells/ml . Viral stocks were propagated in Vero cells ( American Type Culture Collection [ATCC] Manassas , VA ) , titered by plaque formation on Vero cells , and aliquots stored at −80°C [57] . HSV-2 was inactivated by exposure to UV lamp for 6 h in 6 wells plates without lid . Inactivation was verified by plaque formation on Vero cells . Freshly isolated human and macaque PBMCs were resuspended in cold RPMI 1640 at 50×106 cells/ml and exposed to 0 . 2 or 5 plaque forming units ( pfu ) /cell ( 1 MOI = 1 pfu/cell ) of live or UV-inactivated HSV-2 or to the equivalent volume of medium in which the viral stocks were grown ( mock ) ( Dulbecco modified Eagle medium [DMEM] 2% FBS ) for 2 h at 37°C cells were extensively washed and cultured for 24 h in R10 . 1 U/ml of IL2 was added to the PBMC cultures . Immature moDCs were collected at day 5 , resuspended in cold RPMI 1640 without FBS at 20×106 cells/ml , exposed to live 2 ( 0 . 04 , 0 . 2 or 1 pfu/cell ) or UV-inactivated HSV-2 ( 0 . 2 , 1 or 5 pfu/cell ) or to DMEM ( mock-treated ) for 2 h at 37°C . Cells were extensively washed and cultured for 24 h in R1 ( with 100 U/mL IL-4 and 1000 U/mL GM-CSF ) at 1×106 cells/ml in 6 wells plates . HSV-2 infection was confirmed at 4 and 24 h by flow cytometry ( BD FACSCAlibur ) . Although not a perfect control , 5 pfu/cell of UV-HSV-2 ( 25 fold the live inoculum ) was rationalized from the infection of Vero cells . These cells release a maximum amount of virus corresponding to 16 folds their inoculum after 24 h in culture . HSV-2-infected PBMCs were washed and resuspended in PBS with LIVE/DEAD Fixable Aqua ( Invitrogen , Life Technologies ) for 10 mins at 4°C . Cells were washed with PBS , resuspended in FACS wash buffer ( PBS 5% BSA 0 . 1% Na Azide ) and incubated for 30 mins at 4°C with: Pacific Blue anti-CD3 ( clone SP34-2 ) and anti-CD14 ( clone M5E2 ) , Alexa700 anti-CD20 ( clone 2H7 ) , PCP-Cy5 . 5 anti-HLA-DR ( clone L243 ) , PeCy7 anti-CD11c ( clone 3 . 9 ) . Cells were washed with FACS wash and fixed/permeabilized with Fix/Perm and Wash/Perm buffers ( BD Biosciences ) . Cells were stained with anti-HSV-2 ICP-8 monoclonal antibody ( mAb ) ( IgG2a isotype; Virusys , North Berwick , ME ) 15 mins at room temperature , washed and analyzed within 24 h with BD LSRII . The ICP-8 mAb was directly conjugated with Alexa647 ( Zenon Antibody labeling kit , Invitrogen , Life Technologies ) . Data were analyzed with FlowJo software 8 . 8 . 6 . HSV-2-infected and mock-treated moDCs were washed and resuspended in PBS with LIVE/DEAD Fixable Aqua for 10 mins at 4°C . Cells were washed with PBS , resuspended in FACS wash buffer incubated 30 mins at 4°C with FITC anti–HLA-DR ( clone L243 ) , PE anti-CD25 ( M-A251 ) , PE anti-CD80 ( clone L307 . 4 ) , PE anti-CD86 ( clone ) , PE anti-CD209 ( clone DCN46 ) , PE anti-CD40 ( clone 5C3 ) , PE anti-CD54 ( clone HA58 ) PE anti-CD83 ( clone HB15e ) ( all BD Biosciences ) . Cells were fixed and permeabilized with Fix/Perm and Wash/Perm buffers ( BD Biosciences ) . Cells were stained with anti–HSV-2 ICP-8 mAb 15 mins at room temperature , washed and analyzed within 24 h with BD FACS Calibur or with BD LSRII , when stained with Aqua . HSV-2-infected ( 0 . 2 MOI ) versus UV-HSV-2- and mock-treated DCs were resuspended in PBS 1% BSA at 10×106 cells/ml and exposed to 8×104 TCID50/106 cells of HIV-1 ADA-M ( Lot: P4023 . Sucrose gradient-purified was kindly provided by the AIDS Vaccine Program , SAIC-Frederick , NCI-Frederick ) for 2 h at 37°C ( versus no virus controls as indicated ) . 30 mins before the end of the 2 h , CD4+ T cells were resuspended at 6×106 cells/ml in R5 supplemented with 1 U/ml of IL-2 and plated in 48 well plates . RAR antagonist Ro41-5253 ( Enzo Life Sciences , Zandhoven Belgium ) at the final concentration of 500 nM or the same quantity of dimethyl sulfoxide ( DMSO ) was added to the wells for 10 mins at room temperature . HIV-1-pulsed moDCs were washed 3 times and resuspended at 2×106 cells/ml in R5 ( 1 U/ml IL2 ) . Cells were mixed at a 1∶3 ratio in 48 well plates ( 0 . 5×106 DC: 1 . 5×106 T cells ) and cultured at a final concentration of 4×106 cells/ml . Control CD4+ T cells were cultured at 4×106 cells/ml in R5 ( 1 U/ml IL2 ) , exposed to live , UV HSV-2 or DMEM and/or co-exposed to 8×104 TCID50/106 cells of HIV-1 ADA-M ( Lot: P4023 ) for up to 5 days . Viruses were added directly to the CD4+ T cells cultured in absence of moDCs and not washed out . After 3 , 5 and 7 days pellets and supernatants from the HIV-infected DC-T cell and T cell only cultures were collected and stored at −80°C . HIV-naive DC-T cell and T cell only cultures were stained with LIVE/DEAD Fixable Aqua ( Invitrogen , Life Technologies ) , PerCP-Cy5 . 5 anti-CD4 ( clone SP34-2 ) , Pacific Blue anti-CD3 ( clone L200 ) , Alexa700 anti-CD69 ( Clone FN50 ) , FITC anti-CD45RA ( clone HI100 ) , APC anti-CD45RO ( clone UCHL1 ) , FITC anti-CD62L ( clone SK11 ) , PeCy7 anti-CCR7 ( clone 3D12 ) , PE anti-dimeric α4β7 ( Act-1 Clone , NIH AIDS Research Reference and Reagent Program ) . Act-1 was directly conjugated using LYNX RPE antibody Conjugation KIT ( AbD Serotech , Raleigh , NC ) at 4°C for 30 mins . Cells were fixed in Cytofix buffer ( BD Bioscience ) . At least 200000 events in the lymphocyte gate were acquired and analyzed using the BD LSRII Flow Cytometer and the FlowJo 8 . 8 . 6 software ( Tree Star , Inc . ) . DNA from DC-T cell pellets was extracted using DNeasy Blood & Tissue kit ( Qiagen Inc , Valencia , CA ) . Quantitative PCR for HIV gag DNA and an estimation of cell numbers using albumin DNA copy numbers was performed using published primers and molecular probes [58] . DNA was quantified by qPCR with an ABI 7000 PCR machine ( PerkinElmer Life and Analytical Sciences , Boston , MA ) using 5 µl of DNA for 40 cycles and the ABI master mix ( TaqMan Universal PCR Master Mix; Applied Biosystems ) . ALDH1A Primers are listed in Supplementary Table S2 and were generated using Primers3 [59] . They were designed to span at least 1 exon-exon junction and their specificity was verified by nucleotide blast . The GAPDH gene was used as positive assay control with primer sequences: FW GAAGGTGAAGGTCGGAGT , RW GAAGATGGTGATGGGATTTC . RNA extraction was carried out using RNeasy Mini Kit ( Quiagen ) and residual DNA was digested using the RNase-Free DNase Set ( Quiagen ) . The reverse transcription ( RT ) was performed using RandomPrimers ( Invitrogen ) , dNTPmix ( BioRad ) DTT ( 5 µM , Invitrogen ) Superscript III RT and 5× First strand buffer ( Invitrogen ) and the MyCycler , Thermal Cycler ( Bio-Rad , Laboratories , Inc . , Hercules , CA ) Cycling conditions: 25°C 5 mins , 50°C 45 mins , 70°C 15 mins . RNase H ( Invitrogen ) was used to remove RNA template . The PCR was performed using HotStarTaq Master Mix ( Qiagen ) . Cycling conditions: 95°C 10 mins , 25× ( 94°C 30 sec , 60°C 30 sec , 72°C 30 sec ) , 72°C 10 mins . mRNA from CD14− PBMCs was used as negative control for ALDH1A expression . The RT step for quantitative PCR ( qPCR ) was carried out using the SuperScript Vilo cDNA synthesis kit ( Invitrogen ) . 100 ng of RNA was used in each reaction . Relative qPCR was performed using the SYBR Green PCR Master Mix ( Applied Biosystems , Life Technologies ) . 1 µl of cDNA was used in each reaction . The 7000 Sequence Detection System cycler ( Applied Biosystems , Life Technologies ) was used for carrying out the reaction . Cycling conditions: 95°C 10 mins , 40× ( 95°C 15 sec , 60°C 1 min ) . Dissociation curves were generated to verify absence of unspecific amplification . Data were analyzed using the ABI Prism 7000 SDS Software ( Applied Biosystems ) . The standard curve was generated using 2 fold dilutions of RNA extracted from HSV-2 infected moDCs . RT of standards was performed each time together with the samples to avoid variation in the RT efficiency . In the real-time experiments GAPDH was used as endogenous control for sample normalization [60] . Arbitrary units were used to determine fold increase compared to uninfected ( mock ) moDCs . ALDH activity in individual cells was estimated using ALDEFLUOR staining kits ( StemCell Technologies , Vancouver , BritishColumbia , Canada ) , according to the manufacturer's protocol with modifications as previously described [32] . Briefly , cells were suspended at 106 cells/ml in ALDEFLUOR assay buffer containing activated ALDEFLUOR substrate ( 150 nM ) with or without the ALDH inhibitor diethylaminobenzaldehyde ( DEAB ) on ice . Cells were incubated for 45 mins at 37°C , washed and stained with LIVE/DEAD fixable aqua ( Invitrogen ) for 30 mins on ice in ALDEFLUOR assay buffer . They were washed again and stained with APC anti-HLA-DR mAbs or isotype control for 30 mins on ice . ALDEFLUOR reactive cells were detected using BD LSRII flow cytometer with 488-nm blue laser and standard FITC 530/30 nm bandpass filter . Stored cell culture supernatants were thawed and examined for CK/CC concentrations using the human cytokine 25-plex ( Invitrogen ) on the Luminex 200 ( Luminex Corp . Austin , Texas ) . The kit measures IL-1β , IL-1RA , IL-2 , IL-2R , IL-4 , IL-5 , IL-6 , IL-7 , CXCL8 , IL-10 , IL-12p40 , IL-13 , IL-15 , IL-17 , IFNα , IFNγ , TNFα , GM-CSF , CCL2 , CCL3 , CCL4 , CXCL9 , CCL11 , CCL5 . The StartStation software was used to analyze the data . Animals were challenged intra-rectally with 2×108 pfu of replication competent or UV-inactivated HSV-2 in 1 ml of serum-free RPMI 1640 . Rectal swabs were collected 4 days and 1 day before HSV-2 challenge and 3 days and 6 days post challenge . Swabs were drained of fluid and then discarded . The remaining samples were centrifuged at 3500 rpm for 10 mins . Total fluids or aliquots of supernatants were stored at −80°C . Serum for SHIV-RT RNA levels was collected prior to challenge and at time of necropsy . Plasma was separated from whole blood by centrifugation at 2000 rpm for 10 mins , clarified at 2000 rpm for 10 mins and stored at −80°C in 1 ml aliquots . SIV gag RNA was measured by quantitative RT-PCR assay [61] . HSV-2 DNA shedding was determined by measuring the presence of the HSV-2 gD gene ( which encodes the viral entry receptor glycoprotein D ) using a nested PCR . gD primers used: Ext FW AAGCGTGTTTACCACATTCAGCCG , RV TGTGTGATCTCCGTCCAGTCGTTT , Nested: FW TACTACGCAGTGCTGGAACG , RV CGATGGTCAGGTTGTACGTG . This assay was able to reproducibly detect HSV-2 gD DNA signals from 0 . 5 infected cells ( single replicates ) or 0 . 0005 infected cells ( at least 2 positives in 6 replicates ) [6] , DNA was extracted from 0 . 3 ml aliquots of the total fluids using DNeasy Blood & Tissue kit ( Qiagen ) . GAPDH primers and cycling conditions were performed as described above in the methods for the ALDH1A PCR . PBMCs were isolated from EDTA blood using Ficoll-Hypaque density gradient centrifugation . Axillary , inguinal , iliac and MLNs , as well as rectal tissues were obtained at necropsy . Fat tissue was removed from the LNs with a scalpel , LNs were cut in small pieces and passed through a 70 µm nylon cell strainer ( BD-Falcon , Franklin Lakes , NJ ) . Cells were washed twice with RPMI and resuspended in FACS staining buffer . After removal of fat tissue and blood vessels , from the rectal mucosa was cut in small pieces and incubated in HBSS without Ca2+ and Mg2+ with 200 µg/ml gentamycin ( Gibco , Life Sciences ) , 7 . 5 mg DTT ( Sigma-Aldrich ) and a final concentration of 1 . 7 mM of EDTA for 45 mins at room temperature on a shaking platform . HBSS was discarded and the remaining tissue washed in HBSS with Ca2+ and Mg2+ . Tissues were incubated in R10 with 1 mg/ml hyaluronidase ( Sigma-Aldrich ) 0 . 5 mg/ml Collagenase II ( Sigma-Aldrich ) 1 mg/ml DNAse I ( Roche ) for 4 h at 37°C or until tissue was completely digested . The cell suspension was passed through a 70 µm nylon cell strainer , cells were washed twice with PBS and resuspended in FACS wash buffer . Cells were stained with PerCP-Cy5 . 5 anti-CD4 ( clone SP34-2 ) , Pacific Blue anti-CD3 ( clone L200 ) , Alexa700 anti-CD69 ( Clone FN50 ) , FITC anti-CD95 ( clone DX2 ) , APC anti-CD28 ( clone 28 . 2 ) , PE anti-dimeric α4β7 ( Act-1 Clone ) and PE-Cy7 anti-CCR7 ( clone 3D12 ) . At least 200000 events were acquired in the lymphocyte gate . Samples were analyzed using the BD LSRII Flow Cytometer . Wilcoxon signed-rank and Mann-Whitney non-parametric tests were used to compare variables between groups ( mock versus live HSV-2 , UV-HSV-2 versus live HSV-2 and mock versus UV-HSV-2 ) . Wilcoxon signed-rank and one sample t test with 1 as hypothetical value were both used to analyze results expressed as fold increase . A two-tailed P value α<0 . 05 was considered significant . Analysis was performed using Prism ( GraphPad Software , Inc ) version 5a . NCBI Reference Sequences: mRNA ALDH1A1: NM_000689 . 3 mRNA ALDH1A2: NM_170696 . 1 mRNA ALDH1A3: NM_000693 . 2 Swiss-Prot: ICP-8 P11870 . 2
The vast majority of HIV-1 infections occur through genital and rectal mucosa . A better understanding of the characteristics of the mucosal microenvironment that help HIV-1 replication is critical to developing strategies for prevention of HIV-1 transmission . HSV-2 infects genital and rectal mucosa and infected individuals carry an increased risk for HIV-1 infection . Clarifying the mechanisms involved in the increased susceptibility of HSV-2 positive individuals to HIV-1 infection may help understating the characteristics of mucosal microenvironment that facilitate HIV-1 transmission . We previously described a specific interaction between HIV-1 and integrin α4β7 , a signature molecule that allows lymphocytes to gain access to the gut tissue , a major site of HIV-1 replication . Vitamin A and its metabolite , retinoic acid , have an important role in balancing the immune response in the gut and in the expression of integrin α4β7 . Here we describe that HSV-2 rectal infection in monkeys increases the frequency of α4β7+ CD4+ T cells in blood and rectal tissue and that this could be at least partially explained by the ability of HSV-2 infected DCs to secrete retinoic acid and up-regulate α4β7 on CD4+ T cells . These phenomena could be responsible for increasing HIV-1 replication in DC-T cell co-cultures .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "infectious", "diseases", "drugs", "and", "devices", "immunology", "biology", "microbiology", "molecular", "cell", "biology" ]
2011
HSV-2 Infection of Dendritic Cells Amplifies a Highly Susceptible HIV-1 Cell Target
Cellular senescence suppresses cancer by arresting cell proliferation , essentially permanently , in response to oncogenic stimuli , including genotoxic stress . We modified the use of antibody arrays to provide a quantitative assessment of factors secreted by senescent cells . We show that human cells induced to senesce by genotoxic stress secrete myriad factors associated with inflammation and malignancy . This senescence-associated secretory phenotype ( SASP ) developed slowly over several days and only after DNA damage of sufficient magnitude to induce senescence . Remarkably similar SASPs developed in normal fibroblasts , normal epithelial cells , and epithelial tumor cells after genotoxic stress in culture , and in epithelial tumor cells in vivo after treatment of prostate cancer patients with DNA-damaging chemotherapy . In cultured premalignant epithelial cells , SASPs induced an epithelial–mesenchyme transition and invasiveness , hallmarks of malignancy , by a paracrine mechanism that depended largely on the SASP factors interleukin ( IL ) -6 and IL-8 . Strikingly , two manipulations markedly amplified , and accelerated development of , the SASPs: oncogenic RAS expression , which causes genotoxic stress and senescence in normal cells , and functional loss of the p53 tumor suppressor protein . Both loss of p53 and gain of oncogenic RAS also exacerbated the promalignant paracrine activities of the SASPs . Our findings define a central feature of genotoxic stress-induced senescence . Moreover , they suggest a cell-nonautonomous mechanism by which p53 can restrain , and oncogenic RAS can promote , the development of age-related cancer by altering the tissue microenvironment . Cancer is a multistep disease in which cells acquire increasingly malignant phenotypes . These phenotypes are acquired in part by somatic mutations , which derange normal controls over cell proliferation ( growth ) , survival , invasion , and other processes important for malignant tumorigenesis [1] . In addition , there is increasing evidence that the tissue microenvironment is an important determinant of whether and how malignancies develop [2 , 3] . Normal tissue environments tend to suppress malignant phenotypes , whereas abnormal tissue environments such at those caused by inflammation can promote cancer progression . Cancer development is restrained by a variety of tumor suppressor genes . Some of these genes permanently arrest the growth of cells at risk for neoplastic transformation , a process termed cellular senescence [4–6] . Two tumor suppressor pathways , controlled by the p53 and p16INK4a/pRB proteins , regulate senescence responses . Both pathways integrate multiple aspects of cellular physiology and direct cell fate towards survival , death , proliferation , or growth arrest , depending on the context [7 , 8] . Several lines of evidence indicate that cellular senescence is a potent tumor-suppressive mechanism [4 , 9 , 10] . Many potentially oncogenic stimuli ( e . g . , dysfunctional telomeres , DNA damage , and certain oncogenes ) induce senescence [6 , 11] . Moreover , mutations that dampen the p53 or p16INK4a/pRB pathways confer resistance to senescence and greatly increase cancer risk [12 , 13] . Most cancers harbor mutations in one or both of these pathways [14 , 15] . Lastly , in mice and humans , a senescence response to strong mitogenic signals , such as those delivered by certain oncogenes , prevents premalignant lesions from progressing to malignant cancers [16–19] . Interestingly , some tumor cells retain the ability to senesce in response to DNA-damaging chemotherapy or p53 reactivation; in mice , this response arrests tumor progression [20–22] . Despite support for the idea that senescence is a beneficial anticancer mechanism , indirect evidence suggests that senescent cells can also be deleterious and might contribute to age-related pathologies [10 , 23–25] . The apparent paradox of contributing to both tumor suppression and aging is consistent with an evolutionary theory of aging , termed antagonistic pleiotropy [26] . Organisms generally evolve in environments that are replete with extrinsic hazards , and so old individuals tend to be rare in natural populations . Therefore , there is little selective pressure for tumor suppressor mechanisms to be effective well into old age; rather , these mechanisms need to be sufficiently effective only to ensure successful reproduction . Further , tumor suppressor mechanisms could in principle even be deleterious at advanced ages , as predicted by evolutionary antagonistic pleiotropy . Consistent with this view , senescent cells increase with age in mammalian tissues [27] , and have been found at sites of age-related pathologies such as osteoarthritis and atherosclerosis [28–30] . Moreover , in mice , chronically active p53 both promotes cellular senescence and accelerates aging phenotypes [31 , 32] . How might senescent cells be deleterious ? Senescent cells acquire many changes in gene expression , mostly documented as altered mRNA abundance , including increased expression of secreted proteins [33–41] . Some of these secreted proteins act in an autocrine manner to reinforce the senescence growth arrest [37 , 38 , 40 , 41] . Moreover , cell culture and mouse xenograft studies suggest that proteins secreted by senescent cells can promote degenerative or hyperproliferative changes in neighboring cells [35 , 39 , 42 , 43] . Thus , although the cell-autonomous senescence growth arrest suppresses cancer , factors secreted by senescent cells might have deleterious cell-nonautonomous effects that alter the tissue microenvironment . To date , a comprehensive analysis of the secretory profile of senescent cells is lacking , as is knowledge regarding how this profile varies with cell type or senescence inducer , or how it relates to the tumor suppressor proteins that control senescence . To fill these gaps in our knowledge , we modified antibody arrays to be quantitative and sensitive over a wide dynamic range and defined the senescence-associated secretory phenotype ( SASP ) . We show that this phenotype is complex , containing elements associated with inflammation and tumorigenesis , and is induced only by genotoxic stress of sufficient magnitude to cause senescence . SASPs are expressed by senescent human fibroblasts and epithelial cells in culture . Moreover , epithelial tumor cells exposed to DNA-damaging chemotherapy senesce and express a SASP in vivo . The arrays allowed us to identify two new malignant phenotypes promoted by senescent cells ( the epithelial–mesenchyme transition and invasiveness ) , and the SASP factors responsible for them ( interleukin [IL]-6 and IL-8 ) . Strikingly , the SASP was markedly amplified by oncogenic RAS or loss of p53 function . Our results identify a mechanism by which p53 acts as a cell-nonautonomous tumor suppressor , and RAS as a cell-nonautonomous oncogene , and provide a novel framework for understanding how age-related cancers might progress . To determine whether tissue of origin , donor age , or genotype affected secretory phenotypes , we first studied five human fibroblast strains , derived from embryonic lung ( WI-38 , IMR-90 ) , neonatal foreskin ( BJ , HCA2 ) , or adult breast ( hBF184 ) . We cultured the cells under standard conditions , and either atmospheric ( ∼20% ) O2 or 3% O2 , which is more physiological [44] . We made presenescent ( PRE ) cultures ( >80% of cells capable of proliferation ) quiescent by growing the cells to confluence in order to compare them to nondividing senescent ( SEN ) cultures ( <10% proliferative ) ( Table S1 ) . We induced senescence by either repeatedly passaging the cells ( REP , replicative exhaustion ) or by exposing them to a relatively high dose ( 10 Gy ) of ionizing radiation ( XRA [X-irradiation] ) ( see Materials and Methods; Table S1; and Text S1 ) . To identify proteins secreted by PRE and SEN cells , we generated conditioned media ( CM ) by incubating each culture in serum-free medium for 24 h . After normalizing for cell number , we analyzed CM using antibody arrays designed to detect 120 proteins selected for roles in intercellular signaling ( Table S2 ) . We modified the detection protocol ( see Materials and Methods and Text S1 ) , thereby rendering the arrays linear over two to three orders of magnitude; accurate , as determined by concordance with enzyme-linked immunosorbent assays ( ELISAs ) of recombinant proteins; and reliable , as determined by comparing triplicate samples analyzed separately to pooled samples ( Text S2 ) . We quantified the signals , normalizing intensities to controls on the arrays to facilitate interexperiment comparisons , and calculated secreted protein levels as log2-fold changes relative to averages of all samples for each cell strain ( baseline ) . We used these values for quantitative data analyses ( Datasets S1–S4 ) and for visual display ( Figure 1A ) . For the visual display , values over baseline are displayed in grades of yellow , and values under baseline are displayed in grades of blue ( Figure 1A ) . Although the display gives only a semiquantitative assessment of how secretion levels vary ( see accompanying scale in Figure 1A , with log2-fold changes indicated ) , the data ( Datasets S1–S4 ) show that SEN cells secrete significantly higher levels of numerous proteins compared to PRE cells ( Figure 1A ) . We term this phenomenon a senescence-associated secretory phenotype ( SASP ) . Of 120 proteins interrogated by the arrays , 41 were significantly altered in the SEN CM and were oversecreted in comparison to PRE CM ( Figure 1A and Dataset S4 ) . However , the SASPs did not result from a general stimulation of secretion . Seventy-nine proteins showed no significant differences in secreted levels between SEN and PRE cells , although many of these proteins were easily detectable by the arrays ( Dataset S4 ) . The SASPs were complex , and their biological effects could not be predicted a priori . SASP components included inflammatory and immune-modulatory cytokines and chemokines ( e . g . , IL-6 , −7 , and −8 , MCP-2 , and MIP-3a ) . They also included growth factors ( e . g . , GRO , HGF , and IGFBPs ) , shed cell surface molecules ( e . g . , ICAMs , uPAR , and TNF receptors ) , and survival factors ( Figure 1A and Table S2 ) . However , the SASP was not a fixed phenotype . Rather , it was a wide-ranging profile because each cell strain also displayed unique quantitative or qualitative features . In addition , within strains , PRE cultures secreted higher levels of some factors in 20% versus 3% O2 , and SEN cultures secreted higher levels of some factors in 3% versus 20% O2 . Thus , although human cells are less sensitive than mouse cells to hyperphysiological O2 [44] , human cells are not unaffected by the ambient O2 level . Nonetheless , the secretory phenotype was highly conserved ( r > 0 . 75 ) in human senescent cells cultured in 3% versus 20% O2 . By contrast , the ambient O2 level strongly affects the secretory phenotype of mouse senescent cells ( J . P . Coppe , C . K . Patil , F . Rodier , A . Krtolica , S . Parrinello , et al . , unpublished data ) . We verified the secretion levels of several SASP proteins by ELISAs ( Figure S1 and Text S1 ) . Further , because secretion increased greater than 10-fold for some SASP factors , we could verify up-regulation by intracellular immunostaining . For example , IL-6 and IL-8 were barely visible in PRE cells but clearly detectable in SEN cells ( Figure 1B , Figure S2 , and Text S1 ) . We performed the immunostaining on cells in 10% serum , which allowed us to rule out the possibility that the SASP was a senescence-specific response to the serum-free incubation needed to collect CM . Moreover , the SASPs of SEN cells induced by REP and XRA were highly correlated ( r > 0 . 9; Figure 1C ) , indicating that the phenotype was not specific to one senescence inducer . The secretory profiles of fibroblast strains from the same tissues ( e . g . , BJ and HCA2 from neonatal foreskin; and IMR90 and Wi-38 from fetal lung ) were highly correlated ( Datasets S3 and S4 ) . In subsequent figures , data from these related cell strains , as well as from REP and XRA samples from cells of the same type , were pooled and averaged in order to simplify the display . Because REP and XRA induce senescence primarily by causing genomic damage ( from telomere shortening and DNA breaks , respectively ) , we asked whether the SASP was a primary DNA damage response . We irradiated cells using either 0 . 5 or 10 Gy . As expected , both doses initiated a DNA damage response , as determined by p53 stabilization and phosphorylation ( see Figure S3 and Text S1 ) . However , cells that received 0 . 5 Gy transiently arrested growth for only 24–48 h before resuming growth , whereas cells that received 10 Gy underwent a permanent senescence growth arrest ( Figure 1D ) . Antibody arrays performed on CM collected between 2 and 10 d after irradiation showed that only 10 Gy induced a SASP ( Figure 1D and Figure S3 ) . Moreover , cells that senesced owing to DNA damage developed the SASP slowly , requiring 4–7 d after irradiation before expressing a robust SASP . These findings indicate the SASP is not a DNA damage response per se . However , it is induced by DNA damage of sufficient magnitude to cause senescence , after which it requires several days to develop . We also determined that proteins comprising the SASP were , in general , up-regulated at the level of mRNA abundance ( Figure 1E and 1F , red symbols and line; Figure S4 , and Text S1 ) . However , for detectable proteins that showed little or no senescence-associated change in secretion , mRNA levels were a poor predictor of secreted protein levels ( Figure 1F , blue symbols and line; and Figure S4 ) . Thus , antibody arrays provide a more accurate assessment of the senescence-associated secretory signature than mRNA profiling . To determine whether the SASP is limited to fibroblasts , we studied the secretory activity of epithelial cells . Normal human prostate epithelial cells ( PrECs ) underwent a classic senescence growth arrest in response to X-irradiation ( see Table S1 ) . We collected CM from PRE and SEN PrECs , and analyzed the factors secreted by these cells using antibody arrays . Normal PrECs expressed a robust SASP upon senescence ( Figure 2A and Datasets S5–S8 ) . Like fibroblasts , SEN PrECs secreted many factors at significantly higher levels compared to PRE PrECs . To compare the SASPs of normal human epithelial and stromal cells senesced under similar conditions , we analyzed factors that showed a significant change ( p < 0 . 05 ) upon senescence in PrECs or fibroblasts induced by XRA only ( Figure 2A ) . Using the hypergeometric distribution , we determined that the SASPs of both normal cell types overlapped highly significantly ( p = ∼10−3; see Materials and Methods ) . The trend analysis of all 120 factors on the arrays ( Figure 2B ) demonstrated that the secretory profiles were correlated ( r = 0 . 53 ) and also indicated >66% overlap between normal fibroblasts and normal epithelial cells . More specifically , both SASPs included inflammatory or immune factors such as IL-6 , IL-8 , or MCP-1 , growth modulators such as GRO and IGFBP-2 , cell survival regulators such as OPG or sTNF RI , and shed surface molecules such as uPAR or ICAM-1 ( Figure 2A ) . Not surprising , there were also differences between the SASPs of fibroblasts and PrECs . In contrast to fibroblasts , three factors ( Acrp30 , BTC , and IGFBP-6 ) were significantly down-regulated by SEN in PrECs . Moreover , IL-1α or HGF were SASP factors unique to either normal epithelial SASP or normal fibroblast SASP , respectively . This result indicates that the SASP is not limited to normal stromal cells , and that a substantial overlap between normal senescent cells of different tissue origins exists . Some tumor cells retain the ability to senesce in response to DNA damage , including DNA-damaging chemotherapy [20–22] . We therefore asked whether prostate cancer cells also developed a SASP . We studied three prostate tumor cell lines ( BPH1 [45] , RWPE1 [46] , and PC3 [47] , which differ in their degree of malignancy as follows: PC3 > RWPE1 > BPH1 ) . As with normal epithelial cells ( PrECs ) , we induced senescence by XRA , and analyzed CM using antibody arrays ( Datasets S5–S8 ) . SEN epithelial cells secreted significantly higher levels of numerous proteins compared to PRE counterparts ( Figure 2C ) . The SASPs of prostate epithelial cells showed striking overlap between normal and transformed cells ( Figure 2C and Dataset S8 ) , and there was also striking similarities between the SASP of fibroblasts and all epithelial cells , transformed and not transformed ( Figure 2C , asterisks indicate common secreted proteins , and Datasets S5–S8 ) . Twenty-four proteins were shared between the SASPs of all fibroblasts ( Figure 1A ) and all epithelial cells ( Figure 2C ) ; this overlap was highly significant relative to the overlap predicted from chance ( p = ∼10−5; see Materials and Methods ) . We conclude that normal fibroblasts and both normal and transformed epithelial cells can develop SASPs that significantly overlap , displaying many common , but also some distinct , features . Many human tumor cells retain the ability to senesce , in culture and in vivo , in response to DNA-damaging chemotherapeutic agents [48 , 49] . Epithelial cell lines , as well as normal fibroblasts , underwent senescence in culture in response to mitoxantrone ( MIT ) ( see Table S1 ) , a topoisomerase 2β inhibitor that causes DNA breaks and is used to treat prostate cancer [50] . Antibody arrays ( Figure 3A and Datasets S5–S8 ) and ELISAs for IL-6 , IL-8 , and GRO-α ( Figure S1 ) showed that MIT induced a SASP that correlated well ( r = 0 . 89 ) with the XRA-induced SASP ( Figure 3A ) . The finding that human prostatic tumor cells express a SASP in response to MIT in culture allowed us to determine whether MIT induced a SASP in vivo . We laser captured approximately 1 , 000 tumor epithelial cells in biopsies from human prostate cancer patients before MIT chemotherapy and in tissues removed after chemotherapy and prostatectomy [50] . By microscopic inspection , the captured cells were devoid of stromal cells and leukocytes . Since mRNA and secreted protein levels correlated well for significantly up-regulated SASP factors ( Figure 1E and 1F and Figure S4 ) , we used quantitative PCR to quantify mRNAs encoding senescence and proliferation markers and SASP factors . After chemotherapy , most of the tumors contained significantly higher levels of p16INK4a and p21 mRNAs , which are typically up-regulated in senescent cells ( Figure 3B ) . They also contained significantly lower levels of proliferation-associated mRNAs encoding cyclin A , MCM-3 , and PCNA ( Figure 3B ) . These results suggest that MIT induced tumor cells to senesce in vivo . Importantly , most of the tumors contained significantly higher levels of mRNAs encoding the SASP components IL-6 , IL-8 , GM-CSF , GRO-α , IGFBP-2 , and IL-1β ( Figure 3C ) . However , the levels of mRNA encoding IL-2 , which is not a SASP component , did not significantly change on average ( Figure 3D ) . These findings ( summarized in Figure 3E ) suggest that the SASP is not limited to cultured cells , but also occurs when human cells senesce in vivo . The epithelial–mesenchymal transition ( EMT ) confers invasive and metastatic properties on epithelial cells , and is an important step in cancer progression that presages the conversion of carcinomas in situ to potentially fatal invasive cancers [51 , 52] . We found that the fibroblast SASP induced a classic EMT in two nonaggressive human breast cancer cell lines ( T47D and ZR75 . 1 ) . Secreted factors from SEN , but not PRE , fibroblasts caused dose-dependent epithelial cell scattering , a mesenchymal characteristic ( Figure 4A ) . Moreover , immunostaining showed that PRE CM preserved surface-associated β-catenin and E-cadherin , and strong cytokeratin 8/18 expression ( Figure 4B ) , and western analysis showed that PRE CM preserved low expression of vimentin ( see below ) . These features are epithelial characteristics frequently retained by nonaggressive cells [51 , 52] . By contrast , CM from SEN cells markedly decreased overall and cell surface β-catenin and E-cadherin and reduced cytokeratin expression ( Figure 4B ) , consistent with a mesenchymal transition . Further , SEN CM down-regulated the tight junction protein claudin-1 , leaving the remaining protein localized primarily to the nucleus ( Figure 4B ) , a hallmark of an EMT and a feature of metastatic but not primary tumors [53] . Finally , SEN CM increased vimentin expression ( see below ) , another mesenchymal marker and hallmark of an EMT [52] . Consistent with a SASP-induced EMT , CM from SEN , but not PRE , cells stimulated premalignant MCF-10A and malignant T47D , ZR75 . 1 , CAMA1 , and HCC1187 cells to invade a basement membrane ( Figure 4C ) , as well as MDA-MB-231 and MDA-MB-453 ( data not shown and unpublished data ) . The antibody arrays guided us in identifying the highly secreted SASP components IL-6 and IL-8 as candidates for this activity [54 , 55] . Recombinant IL-6 and IL-8 added to PRE CM stimulated invasion to varying degrees depending on the epithelial line . Importantly , IL-6 and IL-8 blocking antibodies reduced the invasion stimulated by SEN CM ( Figure 4C ) , indicating a substantial contribution from IL-6 and IL-8 . These results support the idea that paracrine activities of the SASP can promote malignant phenotypes in nearby premalignant or malignant cells , and identify new SASP activities: the ability to induce an EMT and to invade a basement membrane . Certain oncogenes , of which oncogenic RAS is the prototype [56] , induce senescence in part by indirectly causing DNA damage [57 , 58] . RAS and related oncogenes are best known for generating mitogenic signals that promote cell-autonomous malignant phenotypes , although RAS-transformed cells are also known to secrete specific factors that contribute to tumorigenesis [59–61] . Our finding that SASPs can promote malignant phenotypes in nearby cells suggested that RAS-like oncogenes might also promote malignancy cell-nonautonomously via a complex SASP . To test this possibility , we expressed oncogenic RAS in fibroblasts and epithelial cells using lentiviruses , allowed the cells to senesce ( Table S1 ) , and analyzed CM using antibody arrays . RAS induced a SASP that had both common and unique features relative to SASPs induced by REP or XRA ( Figure 5A–5E and Datasets S9–S12 ) . The RAS-induced SASP subsumed a subset of proteins that showed increased secretion upon REP- or XRA-induced senescence ( Figure 5A ) . To simplify the visual comparison , we averaged the highly correlated data ( Figure 5A and 5C ) from cells originating from the same tissue ( WI-38 + IMR90 from embryonic lung , and BJ + HCA-2 from neonatal foreskin ) , and from cells induced to senesce by REP or XRA ( see Datasets S9–S12 for details of the averaging , and the raw and processed data ) . Overall , there was good correlation between the SASPs of fibroblasts induced to senesce by RAS , XRA , or REP ( Figure 5C ) . Correlations between SEN ( XRA or REP ) ( averaged ) and SEN ( RAS ) were 0 . 75 for WI-38 and IMR-90 fibroblasts ( averaged ) and 0 . 84 for HCA-2 fibroblasts . A striking feature of the RAS-induced SASP was that all fibroblasts induced to senesce by RAS secreted multiple proteins at levels significantly and dramatically higher than other SEN cells . Because the visual display ( Figure 5A ) is only semiquantitative , the quantitative nature of the amplified SASP is best illustrated by the bar graph ( Figure 5D ) , which plots the log2-fold increases in factors secreted by SEN ( RAS ) cells compared to their SEN ( REP or XRA ) counterparts ( nine proteins were significantly more secreted in SEN ( RAS ) versus SEN ( REP;XRA ) across all fibroblasts ) . In addition , the RAS-induced SASPs had unique features because this SASP included five proteins that were not secreted at significantly elevated levels by other SEN ( REP or XRA ) cells ( Figure 5E ) . We refer to the overall secretory response of cells induced to senesce by RAS , including the quantitative increase in secretion of specific proteins and the secretion of proteins not present in REP or XRA SASPs , as the amplified SASP . We confirmed the robust SASP induced by RAS by immunostaining ( Figure 5B and Figure S2 ) and ELISAs ( Figure S1 ) . Further , we confirmed that oncogenic RAS induced an amplified SASP in prostate epithelial cells ( Figure 5F and 5G ) . Taken together , these results suggest that oncogenic RAS , despite inducing a tumor-suppressive senescence arrest , might promote tumorigenesis in a cell-nonautonomous manner by inducing an amplified SASP . The p53 pathway is important for establishing and maintaining the senescence growth arrest caused by genotoxic stress , although cells that lack p53 can undergo senescence providing they express p16 [62] . We therefore asked whether p53 established or maintained the SASP . To inactivate p53 , we expressed genetic suppressor element 22 ( GSE22 , also designated GSE ) , a peptide that prevents p53 tetramerization and causes inactive monomeric p53 to accumulate ( detectable by immunostaining , Figure S2 ) [63] . We obtained similar results using a short hairpin RNA ( shRNA ) that reduces p53 expression by RNA interference . We induced WI-38 fibroblasts to senesce by REP or XRA and then inactivated p53 . Because WI-38 and IMR90 cells senesce with high levels of p16INK4a , they do not resume proliferation when p53 is inactivated [62] . To simplify the visual comparison of antibody array readouts , we averaged data from highly correlated samples , as described for Figure 5 ( see Datasets S13–S16 for details of the averaging , and the raw and processed data ) . The SASPs of SEN WI-38 in which p53 was either wild type or inactivated after senescence were similar by visual display ( Figure 6A , compare row 1 with row 11 ) , and by the graphical plot of the log2-fold changes that occurred in specific factors ( Figure 6B , green bars showing variations obtained using the appropriate p53 wild-type baseline ( e . g . , SEN ( REP>GSE ) versus SEN ( REP ) in WI-38 ) and Datasets S13–S16 ) . This finding indicates that p53 is not required to maintain an established SASP . To determine whether p53 is needed to initiate a SASP , we inactivated p53 in PRE WI-38 cells and then induced senescence by XRA , REP , or RAS ( Figure 6A , rows 8–10 ) . p53 inactivation did not induce a SASP in PRE cells ( Figures 6A , rows 5–7 , Figures S1 and S2 , and Datasets S13–S16 ) . Upon senescence by either REP , XRA , or RAS , however , p53-deficient cells not only developed a SASP , but the magnitude of the SASP was markedly enhanced ( Figure 6A , rows 8–10 versus 1–4 ) , similar to the amplified SASP induced by RAS . The quantitative effect of p53 deficiency on SASPs is best illustrated by the bar graph , which plots the log2-fold increases of significantly altered factors secreted by cells made p53 deficient and then induced to senesce , compared to cells with wild-type p53 and induced to senesce ( Figure 6C , red and grey bars ) . We confirmed the robust SASP by immunostaining ( Figure 6D and Figure S2 ) and ELISA ( Figure S1 ) . Together , these findings indicate that p53 is not required to initiate the SASP , and further that it restrains development of an amplified SASP . Importantly , the combined loss of p53 and gain of oncogenic RAS resulted in the most amplified SASP ( Figure 6A , rows 9–10 versus rows 1–4; Figure 6E and 6F , Figure S5A , and Text S1 ) . In addition , when p53 was inactivated prior to XRA , the SASP developed much earlier—between 2 and 4 d after irradiation ( Figure 6G and Figures S5B and S5C ) , compared to 4–7 d in cells with wild-type p53 ( Figure 1D ) . Interestingly , cells induced to senesce by RAS also developed the amplified SASP earlier—within 2–4 d after irradiation ( Figures 6G , Figures S5B , S5C , and S6 , and Text S1 ) . Thus , loss of the p53 tumor suppressor , or gain of oncogenic RAS , not only amplified the SASP , but also accelerated its development . We also inactivated p53 in fibroblasts that senesce with low p16INK4a levels: HCA2 , BJ , and WI-38 expressing a shRNA ( shp16 ) that reduces p16INK4a expression by RNA interference . In these cells , whether the cells were induced to senesce by REP or XRA , the SASP was also markedly amplified ( Figure 6A , rows 1–4 versus rows 11–14 ) . The quantitative outcome of p53 loss on established SASPs is best illustrated by the bar graph , which lists the significantly altered factors secreted by cells made to senesce and then induced to lose p53 function , compared to cells induced to senesce and keeping a functional p53 ( Figure 6B , blue and pink bars ) . As reported [62] , p53 inactivation reversed the growth arrest of these cells , and the reverted cells resumed growth ( Figure S6 ) . We refer to these cells as REV , and the reversal of the growth arrest verified the efficacy of the p53 inactivation . These findings indicate that , once established , the SASP cannot be suppressed despite reversion of the senescence growth arrest . Together , the results indicate that p53 activation by genotoxic stress not only restrains cell proliferation , but also restrains the SASP . The SASPs of p53-deficient cells were qualitatively similar to those of SEN cells with wild-type p53 , resulting in tightly clustered profiles ( Figure 6F ) . The main influence of p53 status was quantitative . As was the case for RAS-induced senescence , a subset of SASP proteins was secreted at 5- to 30-fold higher levels after p53 inactivation ( Figure 6B , 6C , and 6E , and Datasets S13–S16 ) . However , there were also unique features of the p53-deficient SASP ( Figure 6B and 6C , bottom ) . Interestingly , many factors that were further or uniquely up-regulated by cells made senescent by RAS were amplified in a similar fashion in p53-deficient cells ( Figures 6B , 6C , 6E , 5D , and 5E ) . p53 also restrained the SASP in prostate epithelial cells . Factors identified as part of the epithelial SASP ( Figure 2A and 2C ) were amplified in the PC3 , BPH1 , and RWPE1 cancer cells , which are p53 deficient , compared to normal PrECs , which have wild-type p53 ( Figure 6H , top cluster ) . In addition , p53-deficient epithelial cells that underwent senescence oversecreted most factors that were restrained by p53 in normal fibroblasts ( compare Figure 6H , bottom cluster versus listed factors in Figure 6B and 6C ) . Taken together , these findings indicate that fibroblasts and epithelial cells that are induced to senesce by genotoxic stress develop a SASP that is restrained by p53 activity . To determine the possible biological consequences of the amplified SASPs , we compared the ability of CM from fibroblasts with unamplified or amplified SASPs to induce an EMT and invasiveness in relatively nonaggressive human cancer cells . CM from cells with an amplified SASP was significantly more potent than CM from SEN cells with wild-type p53 at inducing an EMT , as determined by cell scattering ( compare Figure 7A with Figure 4A ) , immunostaining ( compare Figure 7A with Figure 4B ) , and robust expression of vimentin ( Figure 7A ) , an important quantitative marker of the EMT [52] . These comparisons were made on cells from the same single experiment . Further , the amplified SASP was significantly more potent at stimulating cancer cell invasiveness ( Figure 7B ) . Senescent cells have been shown to stimulate the growth of premalignant or malignant epithelial cells [42 , 43] . We found the amplified SASP stimulated this epithelial cell growth to a significantly greater extent than the unamplified SASP ( Figure 7C ) . These findings support the idea that p53 restrains the cell-nonautonomous promalignant activities of the SASP . We identified a hallmark of cellular senescence—the senescence-associated secretory phenotype or SASP—that confers cell-nonautonomous paracrine functions on cells , and is markedly exacerbated by gain of oncogenic RAS or loss of p53 function . To study the SASP , we modified a commercially available antibody array protocol , substituting radioactivity for chemiluminescence as a final detection method . This modification greatly improved the dynamic range of the arrays , and rendered them highly quantitative , reliable , and accurate . Using this modified array protocol , we were able to study both qualitative and quantitative aspects of the SASP , and compare similarities and differences among individual donors , cell types , and tissues of origin . Importantly , we uncovered quantitative differences caused by oncogenic RAS or loss of p53 function . The SASP was a general feature of senescent fibroblasts from different tissues , donors , and donor ages , as well as prostate epithelial cells , both normal and transformed . There were distinct quantitative and qualitative differences among the different cell strains and lines , as expected given their different genotypes and tissue origins , indicating that the SASP is not an invariant phenotype . However , the striking feature of the phenotype was the marked similarities among the SASPs from diverse donors , cell types , and tissues , suggesting the existence of a conserved core secretory program that any cell undergoing senescence would trigger . Notably , all the SASPs featured high levels of secreted inflammatory cytokines , immune modulators , and growth factors , suggesting that SASPs might have myriad biological activities in addition to those we describe here . Many SASP factors were up-regulated at the level of mRNA abundance , suggesting that the phenotype may be controlled transcriptionally . The correspondence between mRNA levels and SASP factors allowed us to probe human biopsy samples for the expression of SASP components before and after DNA-damaging chemotherapy . Our results showed that human tumor cells very likely undergo senescence in response to DNA damaging chemotherapy in vivo , as reported for mice [49] . Moreover , human tumor cells very likely express a SASP after chemotherapy . We speculate that components of chemotherapy-induced SASPs , particularly the high levels of inflammatory cytokines , might contribute to the debilitating effects of DNA-damaging chemotherapy . These SASPs might also fuel development of secondary cancers by creating a local tissue environment that is permissive for the growth and progression of cells that acquire therapy-induced mutations , and fail to senesce or die . Senescent human fibroblasts have been shown to stimulate the proliferation of premalignant and malignant epithelial cells in culture , and the tumorigenicity of premalignant epithelial cells in mouse xenografts [35 , 42 , 43] . However , the mechanisms responsible for these stimulatory activities are incompletely understood . We identified two new biological activities of SEN cells mediated by the SASP: the ability to induce an EMT in relatively nonaggressive carcinoma cells , and the ability to stimulate their invasion through a basement membrane . The antibody arrays allowed us to identify two SASP factors , IL-6 and IL-8 , which explained much of these two biological activities . In addition to stimulating an EMT and invasiveness , IL-6 and IL-8 promote inflammation , as do other SASP components . Further , senescent cells secreted or shed cytokine receptors , which could act as decoys and allow nearby premalignant or malignant cells to avoid immune surveillance . As they persist in tissues , senescent cells likely create a proinflammatory tissue environment , which is known to be protumorigenic [3 , 64] . Taken together , our findings support the idea that senescent cells can create a tissue microenvironment that promotes multiple stages of tumor evolution . Recent findings show that tumors induced to senesce in mice gradually regress [21 , 22] , owing perhaps to infiltration by cells of the innate immune system [22] . Inflammatory cytokines and chemokines , such as IL-6 , IL-8 , GRO-α , MCP-1 , or GM-CSF , which are core features of the SASP , might contribute to this infiltration and eventual clearance . Why , then , are senescent cells found with increasing frequency during aging and at sites of age-related pathology ? Some SEN cells might be refractory to immune clearance either because they are intrinsically different or they produce higher levels of factors that promote immune evasion . Alternatively , aging or age-related pathologies may dampen immune responses or increase the rate at which senescent cells are produced . Whatever the case , there is mounting evidence that senescent cells increase with age [65–68] and that chronic inflammation is a prominent feature of aging [69] . If the senescence response is an example of antagonistic pleiotropy , the senescent microenvironment created by SASPs might contribute to degenerative diseases of aging , such as osteoarthritis or atherosclerosis [28–30] , in which senescent cells are found , as well as fuel the development of late-life cancers . The evolutionary theory of antagonistic pleiotropy provides an explanation for the apparent dilemma of how the senescence response , or any biological process , can be both beneficial and deleterious , depending on the age of the organism . It is now recognized that aging is a consequence of the declining force of natural selection with age [26 , 70] . This decline is due to the high mortality caused by extrinsic hazards in natural environments , resulting in the relative scarcity of older individuals . Thus , natural selection can favor a trait that contributes to early life fitness ( e . g . , protection from cancer ) , even if that trait is deleterious in older individuals ( e . g . , promoting cancer development ) . We speculate that both the growth arrest and the secretory phenotype of senescent cells can be both beneficial and deleterious . The senescence-associated growth arrest is beneficial because it arrests the growth of cells at risk for neoplastic transformation ( cell-autonomous tumor suppressor function ) . It can be deleterious , however , because an accumulation of nondividing senescent cells can diminish the ability of renewable tissues to repair or regenerate . Although some aged tissues contain less than one or only a few percent of senescent cells [29 , 66 , 71] , others can accumulate as many as 15% senescent cells [65 , 72] . Likewise , the senescence-associated secretory phenotype might have both beneficial and deleterious effects . The SASP can be beneficial because some SASP components reinforce the senescent growth arrest by an autocrine cytokine network [37 , 38 , 40 , 41] , thereby contributing to maintenance of the senescence growth arrest . In addition , many SASP components are predicted to stimulate tissue repair and regeneration , and act as “danger signals” within the vicinity of tissues or systemically at the organism level . Thus , cells undergoing senescence may initially signal tissue damage , and initiate tissue repair via the SASP . Such effect would be the beneficial cell-nonautonomous function of cellular senescence . When chronically present , however , the secretory activity of senescent cells may be deleterious , disrupting normal tissue structure and function , and eventually stimulate age-associated tissue degeneration or promote malignant phenotypes ( e . g . , cancer progression , as described here ) . Oncogenic RAS induced a SASP that was more robust than other senescence inducers , even when p53 function was intact . Oncogenic RAS is a cell-autonomous driver of cell proliferation in many cancer cells . In normal cells , however , oncogenic RAS causes genotoxic stress and senescence [57 , 58] , inducing a SASP and thereby conferring complex cell-nonautonomous oncogenic activities . Thus , oncogenes such as RAS , which are known to activate protumorigenic paracrine mechanisms during transformation [59–61] , might also exert cell-nonautonomous protumorigenic effects through nontransformed cells during the process of inducing senescence ( Figure 7D ) . How does oncogenic RAS induce a SASP ? One possibility is that this activity of RAS is the result of the genotoxic stress caused by RAS-stimulated hyperproliferation . Alternatively , oncogenic RAS might induce a SASP more directly by stimulating the MAP kinase or other signaling pathway . Whatever the case , many aspects of the SASP induced by RAS resembled the SASP of p53-deficient cells . Genotoxic stress sufficient to cause senescence both activates p53 and stimulates a SASP . Our data indicate a dual role for p53 ( Figure 7D ) . First , in responding to genotoxic stress , p53 imposes the senescence growth arrest , consistent with its role as a cell-autonomous tumor suppressor . Second , p53 restrains the SASP because loss of p53 function , in combination with senescence-causing damage , greatly amplifies the SASP . p53 might restrain the SASP in part by rapidly arresting growth after cells experience DNA damage ( unpublished data ) , thereby preventing the accumulation of further damage that could ensue should cells attempt to replicate the damaged DNA template . Additionally , p53 optimizes DNA repair , so cells that lack p53 might accumulate more DNA damage than cells with wild-type p53 , which in turn might result in a more robust ( amplified ) SASP . Thus , the p53 tumor suppressor may act as an early sensor of oncogenic stress , and ultimately operate as a molecular catalyst preventing tissue inflammation . The strong correlation between DNA damage and development of a SASP suggests the SASP might be activated by the mammalian DNA damage response ( DDR ) . Indeed , our preliminary data suggest that some components of the DDR are important for establishing and maintaining the SASP ( F . Rodier , J-P . Coppé , C . K . Patil , W . A . M . Hoeijmakers , D . P . Muñoz , et al . , unpublished data ) . However , the SASP does not develop immediately after DNA damage and therefore is not a simple or classic DDR . Rather , the SASP is a slow and persistent response to severe or irreparable damage of sufficient magnitude to cause senescence . The persistence of the SASP might have important biological consequences . For example , cells that express low p16INK4a levels ( e . g . , SEN ( REP ) or SEN ( XRA ) HCA2 ) senesce in response to severe damage by activating the p53 pathway; when p53 is subsequently inactivated in these cells , they resume proliferation [62] , but do not lose the SASP . Moreover , they eventually amplify the SASP as they acquire additional damage owing to proliferation in the absence of a functional checkpoint . Proliferating p53-deficient cells that senesced in response to genotoxic stress also developed a highly amplified secretory phenotype . These cells are at greater risk for escaping senescence ( unpublished data ) and would pose a danger to the tissue , not only by virtue of their proliferation , but also by virtue of their amplified SASP . Moreover , human cells that bypass oncogene-induced senescence [58] , as well as cells in some human premalignant lesions [73 , 74] , show signs of a persistently activated DDR . It is possible , if not likely , that these cells also express a SASP and therefore greatly increase the risk of cancer progression in vivo . By restraining the SASP , p53 acts as a cell-nonautonomous tumor suppressor , dampening the protumorigenic activities of the SASP . This activity might explain why a p53-deficient stroma promotes epithelial cancer progression [75 , 76] . We therefore propose that , in addition to its cell-autonomous ability to suppress cancer by inhibiting cell growth , p53 might further suppress cancer by restraining development of an inflammatory tissue milieu caused by a SASP . Our broad , quantitative assessment of factors secreted by senescent cells revealed a highly complex secretory phenotype . We show here that this phenotype can promote cellular behaviors associated with malignancy , and suggest that cells that acquire mutations such as those that inactivate p53 and/or activate RAS functions can be particularly malignant owing to the paracrine activities of the SASP . It is very likely , though , that additional consequences of the SASP will be uncovered as the many SASP components are tested for specific activities . Cells were obtained , cultured , and made quiescent or senescent as described in Text S1 [42 , 66] . Cultures were washed and incubated in serum-free Dulbecco's modified Eagle medium ( DMEM ) for 24 h to generate CM , which was collected and cells counted . CM was filtered ( 0 . 2 μm pore ) , frozen at −80 °C , and analyzed using antibody arrays ( RayBiotech or Chemicon; Human cat #AA1001CH-8; Mouse cat #AA1003M-8 ) essentially as per the manufacturer's instructions . Briefly , CM was thawed and concentrated 2- to 3-fold at 4 °C ( 3 kDa cutoff ) . Volumes equivalent to 2 × 105 cells were diluted to 1 . 2 ml with DMEM and mixed with 300 μl of blocking solution . Array membranes were preincubated with 1 . 5 ml of blocking solution , incubated with CM mixture ( overnight , 4 °C ) , washed 5× , then incubated with biotin-conjugated antibody cocktail ( 1 h 45 min , room temperature ) . After five washes , detection solution containing 0 . 265 μCi 35S-streptavidin ( 732 Ci/mmol; 0 . 1 mCi/ml ) in blocking solution was added ( 1 h 45 min , room temperature ) , followed by five washes . Radioactivity bound to the filters was detected and quantified using a phosphorimager . Signals were analyzed as described in Text S2 . Assays were performed as described [77 , 78] , using kits and antibodies described in Text S1 . Recombinant proteins and blocking antibodies were obtained as described in Text S1 . Vectors to express oncogenic RAS ( Ha-RASv12 ) , TIN215C , and GSE22 were described [62 , 77 , 79] . Patients with high-risk localized prostate cancer enrolled and treated on a phase I–II clinical neoadjuvant chemotherapy trial at the Oregon Health & Science University , Portland VA Medical Center , Kaiser Permanente Northwest Region , Legacy Health System , and University of Washington [50] . Patients provided signed informed consent . From each patient , prostate biopsies were obtained prior to chemotherapy . At the time of radical prostatectomy following chemotherapy , cancer-containing tissue samples were obtained and frozen . Frozen sections were processed as described in Text S1 . Cancerous epithelium from pretreated biopsy and posttreated prostatectomy specimens were captured separately and histology of acquired cells verified by review of hematoxylin and eosin ( H&E ) -stained sections from each sample and review of the laser confocal microscopy ( LCM ) images . RNA was isolated from cultured or laser-captured cells and analyzed as described in Text S1 . Correlation coefficients were evaluated using Pearson correlation . Statistical significance between distributions of protein or mRNA signals was evaluated using a Student t-test with two tails , and an assumption of equal variance . For determination of the significance of overlap between epithelial and fibroblast SASPs , we used the hypergeometric distribution with the following parameters: population size = 120 ( total proteins on the array ) , sample size = 41 ( fibroblast SASP; see Figure 1A ) , successes in population = 39 ( epithelial SASP; see Figure 2C ) , and successes in sample = 24 ( overlap between the fibroblast and epithelial SASPs; see Figure 2C , asterisks ) . The same statistical analysis was used to compare SEN ( XRA ) normal epithelial cells ( PrECs ) versus SEN ( XRA ) normal fibroblasts ( the following parameters were used: 120 , 29 , 25 , and 12; see Figure 2A and Results ) .
Cells with damaged DNA are at risk of becoming cancerous tumors . Although “cellular senescence” can suppress tumor formation from damaged cells by blocking the cell division that underlies cancer growth , it has also been implicated in promoting cancer and other age-related diseases . To understand how this might happen , we measured proteins that senescent human cells secrete into their local environment and found many factors associated with inflammation and cancer development . Different types of cells secrete a common set of proteins when they senesce . This senescence-associated secretory phenotype ( SASP ) occurs not only in cultured cells , but also in vivo in response to DNA-damaging chemotherapy . Normal cells that acquire a highly active mutant version of the RAS protein , which is known to contribute to tumor growth , undergo cellular senescence , and develop a very intense SASP , with higher levels of proteins secreted . Likewise , the SASP is more intense when cells lose the functions of the tumor suppressor p53 . Senescent cells promote the growth and aggressiveness of nearby precancerous or cancer cells , and cells with a more intense SASP do so more efficiently . Our findings support the idea that cellular senescence can be both beneficial , in preventing damaged cells from dividing , and deleterious , by having effects on neighboring cells; this balance of effects is predicted by an evolutionary theory of aging .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biotechnology", "oncology", "developmental", "biology", "cell", "biology", "immunology", "evolutionary", "biology", "molecular", "biology" ]
2008
Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor
Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways . Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment . Currently , there is a lack of computational methods that enable analysis of multiple gene networks , each of which exhibits differential activity compared to the network of the baseline/healthy condition . We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks , termed M-DMs ( multiple differential modules ) . We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes . We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks . We found that condition-specific M-DMs exhibit differential activities , mediate different biological processes , and are enriched for genes with known cardiovascular phenotypes . By analyzing M-DMs that are present in multiple conditions , we revealed dynamic changes in pathway activity and connectivity across heart failure conditions . We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure . Thus , pathway dynamics is a powerful measure for understanding pathogenesis . iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype . With the exponential growth of omics data , our method can aid in generating systems-level insights into disease progression . Many heart diseases are attributable to both genetic and environmental factors [1] . These factors can perturb gene transcript levels , protein levels , and metabolite levels , which in turn perturbs the interactions among the molecules . Perturbation of the molecular network ultimately leads to perturbation of the cellular and physiological states , contributing to the diseases . Therefore , understanding molecular networks can lead to important insights into the pathogenic mechanisms of heart diseases . The concept of network biology has been applied to studies of various cardiovascular diseases , including heart failure [2 , 3] , atherosclerosis [4] , coronary heart disease [5] , and atrial fibrillation [6] , just to name a few . Because transcriptome data is the most abundant type of omics data , most studies used co-expression networks . In such networks , two genes are connected and assumed to functionally interact if their expression profiles are correlated across multiple conditions . Because genes in the same pathway tend to have correlated expression , analyzing co-expression network is an effective strategy for pathway inference . However , a limitation of previous studies is that networks were constructed using only co-expression information . This practice reduces the statistical power for identifying pathways that are perturbed under diseased conditions . It is more powerful to identify groups of genes that exhibit coherent differential activities between healthy and diseased conditions . Such gene groups directly capture the perturbed pathways . Here we described a novel computational framework , inference of multiple differential modules ( iMDM ) that enables simultaneous analysis of multiple differential co-expression networks ( DCNs ) . iMDM finds coherently differentially expressed gene modules that are either unique or shared among multiple DCNs . By definition , sets of genes that are differentially expressed under diseased states but do not exhibit correlated expression pattern will not be identified as a module . This is consistent with the notation that the entire pathway is perturbed under disease condition . To capture dynamic changes in gene modules across conditions , we have applied a novel graph-theoretical measure that quantifies changes in both gene activity and gene connectivity . We demonstrated the utility of our method using the development of heart failure as our model system . Using RNA-Seq , we measured the transcriptome of the heart at four critical stages during the development of heart failure . By applying iMDM to multiple differential co-expression networks constructed from our time-course RNA-Seq dataset , we discovered both condition-specific and shared gene modules in gene networks of different heart failure conditions . By quantifying connectivity changes in shared gene modules across different conditions , we showed that gene modules with higher connectivity dynamics have higher correlation with the dynamics of heart failure phenotypic measures , suggesting that studying pathway dynamics using iMDM is an effective strategy to uncover causal genes of disease progression . Given the vast amount of transcriptome data , there are ample opportunities to apply our method to better understand the role of network dynamics in the development of heart diseases . We performed a factorial RNA-Seq study to monitor the impact of mitochondrial respiratory complex I deficiency and chronic pressure overload on the heart transcriptome as it progressed from hypertrophy to failure ( Fig 1A ) . Complex I deficiency was triggered by cardiac-specific deletion of Ndufs4 which encodes a structural component of complex I [7] . Pressure overload was triggered by transverse aortic constriction ( TAC ) . For each single perturbation or their combinations , we monitored disease progression at four time points , 1 , 2 , 4 and 8 weeks after the introduction of the perturbation . In total , we profiled the heart transcriptome under 4 major conditions . For the sake of discussion , we termed these conditions wild type sham ( WTSH ) , wild type TAC ( WTTAC ) , knock out sham ( KOSH ) , and knock out TAC ( KOTAC ) . For each time point , four biological replicate RNA-Seq data were generated using 4 hearts ( Manuscript in preparation ) . Hierarchical clustering revealed that the transcriptome profiles of the hearts segregate first by treatment conditions ( TAC vs . SH ) and then by genotypes ( WT vs . KO ) ( Fig 1B ) . Further , we found the largest number of differentially expressed genes ( DEGs ) in the KOTAC vs . WTSH comparison ( N = 6521 , False Discovery Rate ( FDR ) < 0 . 05 ) , followed by the WTTAC vs . WTSH comparison ( N = 5238 ) . In contrast , there were only 251 DEGs in the KOSH vs . WTSH comparison . This result suggests that the transcriptome of KOTAC hearts is most perturbed , which is also associated with accelerated heart failure . On the other hand , there is only a very modest perturbation to the transcriptome of KOSH hearts . Although clustering and differential gene expression analyses can reveal global trend in transcriptome dynamics , such methods cannot reveal individual pathways and their dynamics across conditions , motivating us to develop the inference of multiple differential modules ( iMDM ) algorithm . The major algorithmic steps of iMDM are illustrated in Fig 2 . We applied iMDM to our heart failure RNA-Seq data and identified M-DMs that occur in single as well as multiple DCNs . Using our RNA-Seq data , we first constructed three Differential Co-expression Networks ( DCNs , see Materials and Methods ) , each of which contains 10929 genes . At a p-value threshold of 0 . 05 , we identified a total of 232 M-DMs , including 109 1-DMs , 107 2-DMs , and 16 3-DMs ( Fig 3 ) . A summary of the discovered M-DMs is provided in S1 Table . Consistent with the result of our differential expression analysis , the KOTAC DCN yielded the largest number of condition-specific 1-DMs ( N = 56 ) followed by the WTTAC DCN ( N = 46 ) . In contrast , much smaller number of modules ( N = 7 ) was identified in the KOSH DCN . iMDM also uncovered a large number of 2-DMs in both the KOTAC and the WTTAC DCNs ( N = 73 ) . We conducted two types of comparisons to demonstrate the advantages of iMDM over existing methods . To determine if using differential network can improve performance over using co-expression network alone , we have compared the performance of iMDM when fed with these two types of networks separately . We used our RNA-Seq data to construct three DCNs and three co-expression networks for WTTAC , KOTAC , and KOSH condition , respectively . The two algorithms were fed with appropriate sets of input networks ( i . e . DCNs for the iMDM , co-expression networks for the other algorithm ) . The outputs of the two algorithms were seven sets of modules that were discovered from seven sets of networks ( three single networks , three sets of two networks , and one set of three networks ) . To determine if using multiple networks can improve performance over using a single co-expression network , we have compared iMDM to the popular WGCNA algorithm [8] , which is primarily designed for the analysis of a single co-expression network and has been used in several studies of heart diseases [2 , 4–6] . We generated seven single co-expression networks using one , two , and three experimental conditions at a time , respectively . Each single co-expression network was fed to WGCNA to return a set of modules . Like the other two algorithms , seven sets of modules were computed by WGCNA . We evaluated the resulting seven sets of modules discovered by the different algorithms using multiple reference pathway annotations , including Gene Ontology [9] , KEGG [10] , MGI pathways [11] , Canonical pathways [12] , Biocarta [13] , and Reactome [14] . iMDM achieved significantly higher specificity and sensitivity when evaluated using all except one reference sets ( p-value < 0 . 05 , one-sided Fisher’s exact test , Fig 4A and 4B ) . Besides gold-standard pathway annotations , a higher percentage of gene modules identified by iMDM was enriched for genes whose deletions lead to cardiovascular phenotypes documented in the Mouse Phenome Database [15] ( Fig 4C ) . We concluded that compared to using co-expression networks , simultaneous analysis of multiple differential co-expression networks improves the inference accuracy of gene pathways . We found that the three sets of 1-DMs were enriched for different Gene Ontology ( GO ) annotations ( Fig 5A ) . For instance , KOSH 1-DMs were enriched for nucleotide catabolism and localization of cell . WTTAC 1-DMs were enriched for terms such as tricarboxylic acid cycle , phospholipid metabolism , and enzyme linked receptor protein signaling . KOTAC 1-DMs were enriched for terms such as extracellular structure organization , fatty acid metabolism , hemostasis , and negative regulation of response to stimulus . In general , the different enriched terms were consistent with their specific phenotypes . Several of the rate-limiting steps of nucleotide metabolism take place in the mitochondria and can be affected by the fitness of the organelle [16] . Nucleotide metabolism is generally regarded as a house-keeping process . This is likely the reason why genes involved in nucleotide metabolism were enriched in modules identified under KOSH condition . For the more severe phenotypes of WTTAC and KOTAC , other processes directly related to heart failure were enriched other than this house-keeping process . The other term unique to KOSH 1-DMs was “localization of cell” . Genes annotated with this term are involved in communication with the extracellular matrix . Changes in extracellular matrix are linked to myocardial fibrosis and inflammation , which are earlier events of , hear failure development [17] . For the terms specifically enriched among WTTAC 1-DMs , both TCA cycle and phospholipid metabolism contribute to the general energy metabolism deficiency in failing heart , which has been observed before using the TAC model of heart failure [18] . For KOTAC condition , loss of Ndufs4 leads to significant lower NAD+/NADH ratio in KOTAC hearts compared to WTTAC hearts [7] . The low NAD+/NADH ratio inhibits fatty acid beta-oxidation [19] . This coordinated down-regulation of the fatty acid module likely contributes to the more severe deregulation of energy metabolism in KOTAC hearts . Hemostasis has been reported to be associated with more severe form of heart failure such as KOTAC [20] . Besides GO annotation , we found that a higher fraction of KOTAC 1-DMs ( versus WTTAC ) was enriched for genes whose disruption leads to cardiovascular phenotypes documented in the Mouse Phenome Database [15] ( 17 . 9% vs . 4 . 3% , p-value = 0 . 03 , one-sided Fisher’s exact test , Fig 5B ) . Because the edge weight in DCNs is a measure of differential gene expression between the disease and baseline conditions , a larger average edge weight of a 1-DM means a bigger difference in the expression of module genes . In other words , the average edge weight serves as a measure of differential activity of the module . We next compared the distributions of average edge weight in the 1-DMs for WTTAC and KOTAC . Our result shows that 1-DMs in the KOTAC network had a greater difference in the expression level than those in the WTTAC network ( 0 . 32 vs . 0 . 19 , p-value = 2 . 4E-16 , one-sided t-test , Fig 5C ) . We also compared the percentages of up- or down-regulated 1-DMs in the WTTAC and KOTAC networks . At a p-value cutoff of 0 . 01 , we found that the percentage of differentially expressed ( up- and down-regulated ) KOTAC 1-DMs was significantly higher than that of WTTAC 1-DMs at all time points . For example , the percentages at week 1 are 54 . 3% and 85 . 7% for WTTAC and KOTAC , respectively ( p-value = 4 . 9E-4 , one-sided Fisher’s exact test , Fig 5D ) . Fig 6 shows two example 1-DMs , one unique to the WTTAC network and one unique to the KOTAC network . The top panels of the figure show the visualization of the 1-DMs . The middle panels show the expression profiles of the module genes under four perturbation conditions over time . The bottom panels show the mean edge weights of the 1-DMs in the three non-baseline conditions . Together the middle and right panels explain why a 1-DM is uniquely observed in one condition . Taking the WTTAC 1-DM for example , although many genes of the module were differentially expressed in both WTTAC and KOTAC conditions , their expression correlation was much lower in the KOTAC condition . Notice the tighter correlation of expression profiles among WTTAC module genes compared to that of KOTAC module genes ( Fig 6A middle panel ) . As a result , the edge weights among the module genes in the KOTAC DCN were significantly smaller than those in the WTTAC DCN ( Fig 6B right panel ) . Thus , this module was only identified by iMDM in the WTTAC DCN . The example WTTAC 1-DM is enriched for genes involved in the regulation of cell adhesion ( Fig 6A , p-value = 1 . 1E-4 ) . The example KOTAC 1-DM is enriched for genes involved in fatty acid metabolism ( Fig 6B , p-value = 3 . 2E-8 ) . The expression of this module is significantly lower in KOTAC compared to WTTAC at weeks 2 , 4 , and 8 . A number of module genes encode enzymes for fatty acid metabolism and have significantly reduced expression , including Acot1 , Acot2 , Acsl1 , Cpt1b , Cpt2 , Crat , and Decr1 ( S2 Fig ) . These observations are consistent with our previous finding that loss of Ndufs4 leads to significant lower NAD+/NADH ratio in KOTAC hearts compared to WTTAC hearts [7] . The low NAD+/NADH ratio inhibits fatty acid beta-oxidation [19] . This coordinated down-regulation of the fatty acid module likely contributes to the more severe deregulation of energy metabolism in KOTAC hearts . In summary , the above analyses demonstrate the power of simultaneous analysis of multiple DCNs for uncovering condition-specific pathways involved in heart failure . We found that 1-DMs in the KOTAC condition exhibited higher differential activities during heart failure progression and were enriched for higher fraction of genes with known cardiovascular phenotypes when disrupted . These KOTAC-specific 1-DMs provide new insights into the mechanisms for the accelerated heart failure in KOTAC mice . Pathway dynamics can be attributed to changes in both gene expression and connectivity among genes ( i . e . pathway rewiring ) . Although less studied , the latter type of dynamics has recently been shown to play a critical role in disease progression and treatment response , such as the role of hub genes [22] and rewiring of signaling pathways during cancer treatment [23] and cardiac hypertrophy [24] . Here , we demonstrate that iMDM enables systematic analysis of pathway dynamics by considering both activity and connectivity changes among shared 2/3-DMs across networks . We further show pathway dynamics is correlated with the dynamic changes in disease phenotypes , which can provide better insights into molecular mechanisms of disease progression . Because component modules of a 2/3-DM share the same set of genes in multiple DCNs but can differ in their connectivity , 2/3-DM provides a natural way to capture dynamic changes in pathway connectivity . We thus devised the Module Connectivity Dynamic Score ( MCDS ) to quantify the dynamics of M-DMs ( see Materials and Methods for details ) . Since the DCNs are weighted based on the degree of correlated differential expression , MCDS quantifies not only the presence and absence of edges but also changes in edge weights that can be viewed as the interaction strength among genes . To identify M-DMs that exhibit significant dynamics than expected by chance , we compared the MCDS values of real 2/3-DMs to a null distribution of MCDS values of random 2/3-DMs . At a p-value cutoff of 0 . 01 , we found 102 dynamic 2/3-DMs . A list of the dynamic 2/3-DMs is provided in S1 Table . Fig 7A shows an example dynamic 2-DM , observed in both KOTAC and WTTAC DCNs . For clarity , only edges with significant weight changes ( p < 0 . 05 ) are shown . For this module , the majority of the changed edges had increased weight in the KOTAC condition compared to the WTTAC condition ( in red ) , due to more significant changes in the expression of the two genes under the KOTAC condition compared to the baseline . There were also a few edges ( in green ) with decreased weight in the KOTAC condition . These connectivity changes suggest that the pathway was rewired between different heart failure conditions . The degree of rewiring can be quantified by our MCDS metric . Additional example dynamic 2-DMs and 3-DMs are shown in S3 and S4 Figs . Previous studies have shown that certain pathways are more dynamic than others during disease progression or stress response [22 , 25 , 26] . To examine this issue in the context of heart failure , we performed GO term enrichment analysis of the 2/3-DMs . Although certain GO terms were enriched among both dynamic and static 2/3-DMs , each type of M-DMs was also enriched for a unique set of GO terms . For instance , unique functions of the dynamic M-DMs included cell proliferation , trans-membrane transport , ion homeostais , and cell morphogenesis whereas those of static 2/3-DMs include regulation of transcription , chromosome organization and response to organic nitrogen ( S5 Fig ) . The enrichment of unique functional annotations among dynamic modules suggests that dynamic modules may be effective markers for disease progression . We therefore asked how the observed dynamics of 2/3-DMs correlate with the change in cardiac function . We used the following three measures to monitor the function of the heart as it progressed to failure ( S6 Fig ) : heart weight normalized by tibial length ( HW/TL ) , left ventricular internal dimension in diastole ( LVID ( d ) ) and LV fractional shortening ( FS% ) . For each 2/3-DM , only using conditions from which the M-DM is derived , we computed the correlation between its average normalized gene expression level and each of the three cardiac function measures ( Fig 7B , S1 Table , and S1 Text ) . Strikingly , we found that dynamic 2/3-DMs had significantly higher correlation with measures of cardiac function than static 2/3-DMs ( Fig 7C ) . For example , the correlations with fractional shortening were 0 . 60 and 0 . 31 for dynamic and static modules , respectively ( p-value = 5 . 7E-6 , one-sided t-test ) . This result suggests that dynamic 2/3-DMs are better markers for disease progression . From a systems biology point of view , diseases are caused by perturbations to the gene network . Such perturbations change dynamically as the disease progresses . We developed a mathematical model to represent perturbed gene networks and a robust search algorithm to identify regions of the perturbed networks with differential activities and connectivities . Differential network analysis has been applied to protein-DNA interaction networks [27 , 28] , protein-protein interaction networks [29 , 30] , genetic interaction networks [25 , 31] , and functional gene interaction networks [32 , 33] . However , in all previous work , only two conditions were considered ( i . e . only one resulting differential network ) in the computational methods . A key innovation in our method is the ability to identify unique and shared modules from multiple differential gene networks , each of which representing a different perturbation condition . By definition , iMDM finds coherently differentially expressed gene modules . Sets of genes that are differentially expressed under diseased states but do not exhibit correlated expression pattern will not be identified as a module . This is consistent with the notation that the entire pathway is perturbed under disease condition . From a computational point of view , it increases the specificity of the inference as we demonstrated in the benchmarking experiment ( Fig 4A ) . Another challenge in studying network dynamics is how to quantify the rewiring of the pathways . Previous studies only focused on highly connected genes in a pathway , the so-called hub genes , instead of the entire pathway [22 , 34 , 35] . Here , We have used the MCDS metric to quantify the dynamics of an entire pathway . MCDS examines all edges in a module . More importantly , it quantifies not only the presence and absence of edges but also changes in edge weights that can be viewed as interaction strength among genes . By applying the iMDM algorithm to our heart failure RNA-Seq data , we found that condition-specific 1-DMs exhibit differential activities , mediate different biological processes , and are enriched for genes with known cardiovascular phenotypes . Unlike 1-DMs , 2/3-DMs are not condition-specific . A previous study has suggested that there were major differences in topological and biological properties among gene pairs that have global vs . conditional co-expression [36] . We thus compared 1-DMs to 2/3-DMs in terms of their topological features and their activity correlation with disease phenotypes . We found genes in 1-DMs had more connections and located in more central positions in the networks . Activities of 1-DMs also had higher correlation with the disease phenotype measures ( S7 Fig ) . This is consistent with the previous observation that conditional interactions are enriched for genes that are key to maintaining network integrity . In contrast to 1-DMs , M-DMs identified in 2 or more conditions enabled us to study the dynamics of gene modules . By applying the MCDS metric , we were able to distinguish dynamic and static 2/3-DMs . We demonstrated that these two types of modules differ in multiple aspects , including their functional annotations . In particular , we have found that activities of dynamic 2/3-DMs have higher correlation with changes in cardiac disease phenotype , suggesting dynamic modules may play a more important role during disease progression . Thus , studying pathway dynamics can lead to novel insights into disease pathogenesis . iMDM only needs transcriptome profiling data as the input and both microarray and RNA-Seq data are applicable . Given the increasing amount of transcriptome data on various cardiovascular diseases , we envision that iMDM can be applied in several ways to reveal network dynamics under different conditions , including temporal dynamics during disease progression and dynamics between disease subtypes . Besides comparing disease subtypes as what was done here , another interesting analysis is between-disease comparison , such as heart failure versus arrhythmia . The pioneering work on human disease network by Goh et al . [37] has revealed that genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts , supporting the existence of distinct disease-specific functional modules . We envision that a pan-heart analysis using iMDM can lead to similar insights , in particular pathway signature and disease-specific pathways . There are a couple of directions that the basic concept of iMDM can be extended in future work . First , integrating multiple types of molecular analytes beyond gene expression might further expand our ability to identify dynamic molecular events that are associated with phenotypic dynamics . Genetic mutation data such as those from exome and whole-genome sequencing can be used as prior information to guide module search under the assumption that mutated sequences are likely to be involved in the diseases . Epigenomic data can be integrated with transcriptome data to understand how environmental factors perturb gene networks . Second , comparing and contrasting dynamic events involving different molecular types may yield new mechanistic insights into their interactions in the context of disease progression . All animal procedures were performed with the approval of the Institutional Animal Care and Use Committee of the University of Washington . Fig 2 provides a schematic of the iMDM algorithm . The algorithm takes as the input transcriptome profiles gathered under both healthy/baseline and disease conditions . Using the transcriptome profiles , iMDM first constructs multiple differential co-expression networks ( DCNs ) , one for each condition . Two genes are connected in a DCN if they exhibit correlated expression profiles across conditions and their expression levels are significantly different between the disease and the baseline conditions . Next , we adapted the M-module algorithm [38] to identify statistically significant multiple differential modules ( M-DMs ) present in multiple DCNs . iMDM is implemented in the R statistical programming language . The software is freely available upon request . In the following sections , we describe details of each algorithmic steps of the method . For each disease condition , construction of the DCN consists of two steps: 1 ) construction of a binary co-expression network; and 2 ) edge weight assignment based on differential gene expression between the disease and baseline conditions . To construct the binary gene co-expression network , edges are chosen based on the absolute value of the Pearson correlation of the expression profiles of two genes . To remove indirect correlation due to a third gene , we used the 1st order partial Pearson correlation coefficient [39] . Only edges whose correlations are equal or greater than the pre-defined threshold δ are chosen . In this study , the value of δ was set at 0 . 8 such that maximal number of genes was connected in all DCNs to be constructed . In step 2 , weights are assigned to edges in the binary co-expression network based on the p-value of differential gene expression between the disease and baseline conditions . Various methods can be used to detect differential gene expression for microarray or RNA-Seq data . Here , we used EdgeR [40] . The weight wi , j on edge ( i , j ) in the differential network is defined as following: wi , j={ ( logpi+logpj ) 1/2 ( 2*maxl∈V| logpl | ) 1/2 , ifcor ( i , j ) ≥δ , 0 , ifcor ( i , j ) <δ , where pi and pj are p-values of differential expression for genes i and j , respectively . V is the node set of the co-expression network , and cor ( i , j ) is the absolute value of Pearson correlation between genes i , j based on their expression profiles . Under this weighting scheme , genes that are co-expressed and significantly differentially expressed are assigned higher weights , which satisfies our assumption that those genes likely participate in a pathway that exhibit differential activities between the two conditions being compared . Mathematically , given M DCNs with the same node set but different edge sets , Gk = ( V , Ek ) ( 1≤k≤M ) , they can be represented by a 3-dimensional matrix A = ( aijk ) nxnxM where aijk denotes the weight on the edge e ( i , j ) , wi , j , in network Gk . An M-DM , C , is defined as a set of genes whose connectivity within them is stronger than random expectation across all M DCNs under consideration . We adapted our recently developed M-module algorithm to identify M-DMs . M-module is designed for identifying gene modules with common members but varied connectivity across multiple molecular interaction networks [38] . M-DM search consists of three steps: seed prioritization , module search by seed expansion , and refinement of candidate modules . The seed prioritization step ranks genes in multiple networks by using the topological feature of the gene in the network . Briefly , for each network Gk = ( V , Ek ) ( 1≤k≤M ) with an adjacency matrix Ak = ( aijk ) nxn , we construct a function g:V→R such that g ( i ) denotes the importance of vertex i in the corresponding network . The function is defined as gi=∑j∈Nk ( i ) Aijk'g ( j ) where Nk ( i ) denotes the set of neighbors of i in Gk; Ak' denotes the degree normalized weighted adjacency matrix which is computed as Ak'=D-1/2AkD1/2 where D is diagonal matrix with element Dii = ΣjAijk . The product , A′g , denotes the information propagation on network via the edges of networks , which means the importance of a node depends on the number of its neighbors , strength of connection and importance of its neighbors . The exact solution to the equation above is 1-Ak'-1 . For each gene , after obtaining its ranks in all individual networks , denoted as g = [g ( 1 ) , … , g ( M ) ] , we calculate a z-score for each rank g ( l ) . Then we obtain the rank for that gene across all networks by averaging the z-scores across all networks . The top 10% genes were selected as the seeds although the search result is not sensitive to the fraction of seeds used [38] . Starting with each seed , the module search step iteratively includes genes whose addition leads to the maximum decrease in the graph entropy-based objective function until there is no decrease in the objective function . For a given vertex i∈C , let Lk ( i ) denotes the total weight between vertex i and other vertices of the M-DM C in the network Gk , i . e . , Lk ( i ) = Σj≠i , j∈Caijk . Similarly , let L-ki=∑j≠i , j∈V\Caijk denotes the weight between i and vertices outside of C . We defined the entropy for the connectivity of vertex i to C as Hk ( Ci ) =-piklogpik- ( 1-pik ) log⁡ ( 1-pik ) where pik=Lk ( i ) ( L-ki+Lk ( i ) ) . The motivation for using graph entropy is that it quantifies the skewness of in-module connectivity versus out-module connectivity . Summing over all vertices in C and network k , we have Hk ( C ) = Σi∈CH ( Ci ) . The graph entropy for C across all networks and normalized for the size of C is H ( C ) =∑k=1MHk ( C ) C The objective function of the algorithm is defined as: ∑i=1τmin⁡HCi s . t . xij∈0 , 1∑j=1τxij≥1∑i=1nxij>0 where Ci ( 1≤i≤τ ) is a candidate M-DM . X = [x1 , … , xτ] is an index matrix in which each column corresponds to an M-DM and each row corresponds to a gene . The constraints mean that each gene can belong to one or more modules and each module has to contain at least one gene . During the refinement step , M-DMs whose sizes are smaller than five are removed . To merge overlapping M-DMs , we used Jaccard index which is the ratio of intersection over union for two sets . A Jaccard index of 0 . 5 was used in this study . The statistical significance of M-DMs is computed based on the null score distribution of M-DMs generated using randomized networks . Each network is completely randomized 100 times by degree-preserved edge shuffling . To obtain module scores for the null distribution , we performed module search on the randomized networks . Using the null distribution , the empirical p-value of an M-DM is calculated as the probability of the module having the observed score or smaller by chance . P-values are corrected for multiple testing using the method of Benjamini-Hochberg [41] . An adjusted p-value of 0 . 05 was used as the significance threshold . By definition , each M-DM with M≥2 has multiple component modules from different DCNs . To quantify the change in the connectivity of component modules , we used a graph-theoretical measure , the Module Connectivity Dynamic Score ( MCDS ) . Specifically , given an M-DM C whose weighted adjacent matrices of the corresponding induced subgraphs are denoted by AiC ( 1≤i≤M ) , the MCDS between two adjacent component modules is defined as the L2 norm of the matrix subtraction normalized by the number of genes in the M-DM , i . e . , ΔAi , i+1C=||AiC-Ai+1C||2/|C| where ||·||2 is the matrix L2 norm . The overall MCDS of an M-DM is defined as the average MCDS of all pairwise comparisons: τAC=∑i=1M-1ΔAi , i+1C/ ( M-1 ) The statistical significance of MCDS for an M-DM is computed in a similar way as that for M-DMs . Briefly , we first calculate the null distribution for MCDS scores based on random M-DMs . The empirical p-value of an MCDS is calculated using the null distribution . The method of Benjamini-Hochberg is used for multiple testing correction . An adjusted p-value of 0 . 05 was used as the significance threshold . Generation of transgenic mice with cardiac restricted Ndufs4 deletion was described in our recent publication [7] . Mice were fed on rodent diet and water available ad libitum with a 12-hour light/dark cycle in a vivarium . Adult male mice ( 3–4 months old ) received transverse aortic constriction ( TAC ) to induce chronic pressure overload or sham surgeries as previously described [42] . Cardiac geometry and function ( left ventricular internal dimension in diastole ( LVID ( d ) ) and LV fractional shortening ( FS% ) ) were recorded at 1 , 2 , and 4 weeks using echocardiography with the VEVO 770 system equipped with a 707B scan head . All measurements were averaged from six cardiac cycles . Total RNA was isolated from frozen cardiac tissue using the RNeasy Kit for fibrotic tissues ( Qiagen ) and treated with DNase to remove genomic DNA contamination . Quality and integrity of RNA were checked using Agilent Bioanalyzer 2100 . All samples used for RNA sequencing had a Bioanalyzer RIN number of at least 8 . Illumina TruSeq RNA sample preparation kit was used to generate multiplexed sequencing libraries . Libraries were loaded into a flowcell at a concentration of 5 pM and clustered on an Illumina cBot . Sequencing was done on a HiSeq2000 that generated paired-end reads of length 50 bp . Paired-end reads were mapped to the mouse genome ( mm9 ) using Tophat [43] . Only uniquely mapped reads with fewer than 2 mismatches were used for downstream analyses . Transcripts were assembled using Cufflinks [44] and Ensemble ( release 66 ) as the source of annotated transcripts . Normalized transcript abundance was computed using Cufflinks and expressed as FPKM ( Fragments Per Kilobase of transcripts per Million mapped reads ) . Gene-level FPKM values were computed by summing up FPKM values of their corresponding transcripts [44] . FPKM values were used to compute gene co-expression networks .
Recent advances in systems biology have revealed that changes in the structure and activity of gene network play a critical role in the disease progression . Heart failure is a complex disease involving multiple molecular pathways . Yet little is known regarding the dynamic changes in the gene network of heart cells during heart failure development . We have combined experimental and computational approaches to address this question . We developed a computational method to analyze multiple gene networks , each of which exhibits differential activity compared to the network of the healthy condition . In doing so , we are able to identify both unique and shared gene pathways across multiple differential networks . By applying our algorithm to our time-course transcriptome data of heart failure , we revealed dynamic changes in pathway activity and connectivity across heart failure conditions . We further showed that pathway dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure . Our approach provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[]
2015
Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks
Vaccinia virus ( VACV ) is being developed as a recombinant viral vaccine vector for several key pathogens . Dendritic cells ( DCs ) are specialised antigen presenting cells that are crucial for the initiation of primary immune responses; however , the mechanisms of uptake of VACV by these cells are unclear . Therefore we examined the binding and entry of both the intracellular mature virus ( MV ) and extracellular enveloped virus ( EV ) forms of VACV into vesicular compartments of monocyte-derived DCs . Using a panel of inhibitors , flow cytometry and confocal microscopy we have shown that neither MV nor EV binds to the highly expressed C-type lectin receptors on DCs that are responsible for capturing many other viruses . We also found that both forms of VACV enter DCs via a clathrin- , caveolin- , flotillin- and dynamin-independent pathway that is dependent on actin , intracellular calcium and host-cell cholesterol . Both MV and EV entry were inhibited by the macropinocytosis inhibitors rottlerin and dimethyl amiloride and depended on phosphotidylinositol-3-kinase ( PI ( 3 ) K ) , and both colocalised with dextran but not transferrin . VACV was not delivered to the classical endolysosomal pathway , failing to colocalise with EEA1 or Lamp2 . Finally , expression of early viral genes was not affected by bafilomycin A , indicating that the virus does not depend on low pH to deliver cores to the cytoplasm . From these collective results we conclude that VACV enters DCs via macropinocytosis . However , MV was consistently less sensitive to inhibition and is likely to utilise at least one other entry pathway . Definition and future manipulation of these pathways may assist in enhancing the activity of recombinant vaccinia vectors through effects on antigen presentation . Vaccinia virus ( VACV ) is best known for its role as a vaccine in the global eradication of smallpox . Research on VACV has been pursued with renewed fervour in recent years in light of its potential use as an effective vaccine vector for viral and parasitic infections as well as cancer . Exploiting certain aspects of the biology of the immune system may be the key to improving the efficacy of such modern vaccines . Dendritic cells ( DCs ) are key players in the initiation of adaptive immune responses and as such are attractive targets for vaccination [1] , [2] . They are specialised at antigen uptake and highly express C-type lectin receptors ( CLRs ) , a family of Ca2+-dependent carbohydrate recognition receptors that bind to an array of microbial pathogens [3] . DCs use CLRs as a trapping mechanism for pathogens before internalisation or transfer of the pathogen to its specific receptor . DCs also employ a range of mechanisms for antigen uptake including receptor-mediated endocytosis and phagocytosis , as well as non-receptor-mediated processes such as macropinocytosis [4] , [5] . Further information about the mechanisms of DC binding and uptake of VACV could be employed to better target VACV-vectored vaccines to DCs , either directly or via uptake of bystander infected cells and also influence recombinant antigen processing to enhance immune responses . VACV is a large , enveloped DNA poxvirus that exists in multiple infectious forms [6] , [7] . The majority of progeny virions are mature viruses ( MV ) which are released from the cell upon lysis . A small proportion of MVs become further enveloped and are exocytosed from the cell as extracellular virus ( EV ) . The EV envelope contains unique viral proteins not found in the MV envelope [8] . As a result , MV and EV have been shown to have different binding characteristics and infection efficiencies [9] . Despite being studied for several decades , entry receptors for VACV have yet to be conclusively identified . MV binds to glycosaminoglycans [10]–[12] and also to the extracellular matrix protein laminin [13] , however these interactions are not required for infection [13]–[16] . Furthermore , there is evidence that the receptor for VACV may differ between cell types such as primary haematolymphoid cells and epithelial cell lines [9] , [17] . VACV enters cells via several different mechanisms in a cell-type specific manner [18] . Both forms of the virus can enter cell lines via fusion with the plasma membrane [14] , [16] , mediated by a multi-protein fusion complex on the virus [19] , [20] . A low pH dependent endosomal route of entry and macropinocytosis have also been described for MV entry in cell lines [21]–[23] . An endocytic route of entry for EV has been suggested [24] , [25] but not yet confirmed . Furthermore , in DCs , the visualisation of MV in intracellular vesicles by electron microscopy has suggested an endocytic mode of uptake [26] although the nature of these vesicles and the actual mode of uptake have not been described . Few previous studies investigating VACV entry have examined EV as it represents only a small percentage of progeny virions and the outer membrane is very fragile [24] making purification and concentration of this form of the virus difficult . Here we have characterised the entry pathway for both MV and EV in human monocyte-derived dendritic cells ( MDDCs ) as a model for skin DCs . Using a systematic combination of pharmacological inhibitors and confocal microscopy we have shown that both forms of the virus are taken up via a clathrin- , caveolin- , flotillin- and dynamin-independent endocytic pathway , and the virus does not enter the endolysosomal pathway or rely on low pH to enter the cytoplasm . For EV , this uptake mechanism is predominantly macropinocytosis . MV is also macropinocytosed although to a lesser extent and it is likely that this form of VACV utilises multiple redundant entry mechanisms . In addition we have shown that VACV does not bind to CLRs expressed on DCs . To individually study the entry properties of MV and EV we first produced a concentrated , purified stock of GFP-labelled MV via ultracentrifugation on an Optiprep gradient . The purity of the stock was confirmed by immunofluorescence and electron microscopy , and SDS-PAGE followed by general protein staining and western blotting for the D8 and GFP proteins ( Fig . S1 ) . Although the fragility of the outer EV envelope makes purification of this virus difficult we were able to use gentle centrifugal filtration to produce a concentrated stock of GFP-labelled EV in which contaminating MV or damaged EV particles were subsequently neutralised with an MV-neutralising antibody ( Fig . S2 ) . The presence of intact EV in these preparations was confirmed by plaque assay in the presence of the neutralising antibody and also by immunofluorescence microscopy where intact EV was identified by direct detection with an EV-specific antibody or GFP-fluorescence as well as exclusion of MV-specific antibody staining ( Fig . S3 ) . On average , the percentage of intact EV was 46 . 0±15 . 9% with an intact EV titre of 2 . 3×107 pfu/mL ( n = 7 ) . We used fresh EV preparations for each experiment and as the EV titre was calculated retrospectively , this resulted in a range of MOIs being used for EV experiments with multiple DC donors . When we studied the kinetics of VACV entry in MDDCs we made a number of observations . Firstly , we observed virus capping at one end of the cells , a hallmark of endocytosis , for both MV ( 70% of 327 cells ) and EV ( 67% of 90 cells ) within 30 min of binding , consistent with a previous report [26] . We also observed that almost all MV bound to cells at 4°C could be stripped by trypsin , whereas 30 min after entry at 37°C , around half of the bound virions became resistant to trypsin . Moreover , virus cores could first be detected in the cytoplasm only after 60 min by probing with an anti-GFP antibody . This was in marked contrast to BS-C-1 cells where cores were readily detectable at 30 min ( Fig . 1A ) . We interpret these results to suggest VACV does not fuse with the plasma membrane but is removed from the surface of the cell within 30 min and takes up to 60 min to fuse out of an intracellular compartment . VACV infection is abortive in DCs , limited to the expression of early viral proteins which takes place in the cytoplasm [26] but the delayed appearance of virus cores in DCs compared to BS-C-1 cells was mirrored in the kinetics of expression of two immediate early viral genes . E3L ( a dsRNA-binding protein/PKR inhibitor ) and B2R ( unknown protein ) transcripts were abundant within 15 min of virus entry , peaking at 2 h in BS-C-1 cells but were not clearly detectable in DCs until 45-60 min with a delayed peak at 3 h ( Fig . 1B , C ) . Furthermore , the magnitude of early viral gene expression from MV and EV was equal in BS-C-1 cells but in DCs , gene expression from EV was suppressed compared to MV , suggesting differences in the entry pathways or the mechanics of virus core release between the cell types and possibly even between MV and EV in DCs . Active uptake of antigen by DCs is an energy-intensive process requiring rearrangement of the plasma membrane and cytoskeleton and ligation of cellular receptors which often triggers a signalling cascade that coordinates internalisation of the antigen by endocytosis and subsequent events . Conversely , fusion of a viral envelope with the plasma membrane does not usually require cellular ATP and may or may not induce signalling . To distinguish between these pathways of entry in DCs , we examined the requirement for ATP for VACV entry using antimycin A ( AntiA ) , an inhibitor of the mitochondrial electron transport chain that has been shown to inhibit energy-dependent processes [27] . MDDCs were pre-treated with AntiA in glucose-free medium , prior to spinoculation with GFP-labelled MV or EV at 4°C . Bound virus was then allowed to enter the cells in the presence of inhibitor for 30 min at 37°C and any remaining surface-bound virus was stripped by trypsinisation . We chose a 30 min time point to specifically assess the drug's effect on the initial step of virus entry into vesicles . Virus entry was measured by detection of GFP by flow cytometry . Concentrations up to 20 µM AntiA depleted cellular ATP in a dose-dependent fashion by up to 95% ( data not shown ) . Both MV and EV entry was significantly reduced in AntiA-treated cells compared to untreated cells , up to 77 . 2±8 . 7% ( mean ± SEM , n = 3 , p = 0 . 029 ) for MV and 74 . 6±10 . 4% ( n = 3 , p = 0 . 029 ) for EV ( Fig . 2A–C ) , although the remaining ∼25% remained refractory to increasing concentrations of AntiA . Thus , VACV depends on cellular energy for entry in MDDCs . Next , as ligation of cellular receptors often triggers a Ca2+-mediated signalling cascade that coordinates internalisation of the antigen and subsequent events , we examined VACV entry into MDDCs in the presence of EGTA/AM , a membrane permeable intracellular Ca2+ chelator . Both MV and EV entry was dependent on Ca2+ ( Fig . 2D ) . MV entry was significantly inhibited by 63 . 4±4 . 7% ( n = 4 , p = 0 . 003 ) in the presence of 250 µM EGTA/AM whereas EV entry was almost completely abrogated ( 99 . 1±0 . 7% , n = 3 , p<0 . 001 ) . Interestingly , low concentrations of EGTA/AM ( 2 . 5-25 µM ) consistently enhanced both MV and EV entry by 10– 0% . Treatment of the cells with non-membrane permeable EGTA had no inhibitory effect on VACV entry ( data not shown ) indicating that it was intracellular Ca2+ stores that were important for virus entry . Many viruses rely on dynamic changes to the actin cytoskeleton to aid their entry , either to effect endocytosis [28] or transport membrane-bound virus to areas of high endocytic activity [29] . The drugs cytochalasin D ( CytD ) and latrunculin A ( LatA ) disrupt actin polymerisation and inhibit these processes [30] . Both MV and EV entry into MDDCs was significantly inhibited , in a dose-dependent manner , by more than 88 . 4% in treated cells compared to untreated cells at the highest concentrations of both CytD and LatA ( n = 3 , p<0 . 001 for all; Fig . 2E ) . These data indicate that there is a requirement for actin cytoskeleton rearrangements in VACV entry into MDDCs . Altogether , the delayed appearance of virus cores , a reliance on cellular ATP , intracellular Ca2+ and actin strongly suggests that VACV is taken up actively , via an endocytic or macropinocytic mechanism in MDDCs . DCs express an array of CLRs that mediate rapid endocytosis of a variety of glycosylated antigens and pathogens in a Ca2+-dependent manner [3] . Mannose receptor ( MR ) and DC-SIGN are two CLRs that are highly expressed on MDDCs . After having established that VACV is likely taken up via some form of endocytosis in MDDCs , we investigated whether these CLRs were involved in this process . MDDCs were treated with a variety of CLR inhibitors–mannan ( a pan-CLR inhibitor ) , a neutralising anti-DC-SIGN mAb , D-mannose ( a specific inhibitor for MR ) and EGTA ( a Ca2+ chelator ) , prior to MV or EV binding at 4°C . Virus binding was measured by flow cytometry of GFP fluorescence ( Fig . 3A ) or qPCR detection of the virally encoded GFP gene ( Fig . 3B ) , or qualitatively by confocal microscopy ( Fig . 3C ) . Binding of either MV or EV was not significantly reduced by any of the CLR inhibitors nor was there any evidence of a dose-response to mannan . In contrast , the inhibitors were effective at blocking HIV-1 gp120 binding to MDDCs as well as HIV-1 infection of MDDCs ( Fig . 3D ) , as previously reported [31] . Furthermore , VACV bound to the surface of MDDCs did not colocalise with DC-SIGN or MR ( Fig . 3E , F ) . There was also no appreciable difference in the number of particles bound to DC-SIGN- and MR-bright cells compared to dim cells . Thus we conclude that mannose-binding CLRs are not involved in the binding and entry of VACV to MDDCs . Next we investigated whether clathrin-mediated or caveolin-mediated endocytosis are involved in VACV uptake in DCs . VACV has dimensions of 250–350 nm , which possibly precludes it from clathrin- or caveolin-mediated endocytosis as these pathways are normally reserved for particles with a diameter of 100 nm or less . However , these size restrictions may not be absolute particularly in DCs that are specialised at antigen uptake . The large GTPase dynamin II is required for pinching off endocytic vesicles from the plasma membrane during clathrin-mediated and caveolin-mediated endocytosis [32] , [33] . We used two dynamin inhibitors–Bis-T-23 and Dynasore ( Dyngo7a ) that act via different mechanisms to study the requirement for dynamin in VACV entry . Dynasore is a dynamin GTPase inhibitor while Bis-T-23 acts on the assembly domain of dynamin . Each of these drugs inhibited uptake of transferrin , which is taken up by clathrin-mediated endocytosis via the transferrin receptor ( Fig . 4A ) , but did not inhibit MV uptake ( Fig . 4B ) . EV uptake was slightly but not significantly inhibited in the presence of Bis-T-23 ( 14 . 3±7 . 7% , n = 3 , p = 0 . 075 ) and no inhibitory effect was seen with Dynasore ( Fig . 4B ) . Furthermore , when VACV was bound to MDDCs at 4°C then allowed to enter in the presence of fluorescently conjugated transferrin , no colocalisation occurred between the two antigens over a course of 30 min at 37°C ( Fig . 4C ) . Thus , VACV entry in DCs is dynamin-independent . We also found that while caveolin-1 ( Cav-1 ) expression was detectable in MDDCs at the RNA level , only very low amounts of Cav-1 protein were detected by western blot which were undetectable by flow cytometry or confocal microscopy ( data not shown ) . Therefore since VACV entry does not require dynamin , does not colocalise with transferrin and Cav-1 expression is almost undetectable in MDDCs , we conclude that VACV entry in DCs is not via clathrin- or caveolin-mediated endocytosis . An alternative endocytic pathway is the clathrin-independent carrier ( CLIC ) pathway which is clathrin- , caveolin- and dynamin-independent but requires cholesterol in the plasma membrane [4] , [5] . Macropinocytosis also occurs in cholesterol-rich domains in the cell membrane [34] . We used two agents to disrupt lipid rafts to determine their involvement in VACV entry in MDDCs . Methyl-β-cyclodextrin ( mβCD ) disrupts lipid rafts by extracting cholesterol from lipid membranes and filipin III ( Fil ) is a sterol-binding agent that sequesters cholesterol within the membrane . We observed notable reductions in MV entry of up to 19 . 1±2 . 2% ( n = 3 ) in the presence of Fil and up to 28 . 3±14 . 6% ( n = 3 ) in the presence of mβCD , however these reductions were not statistically significant ( p = 0 . 183 and 0 . 305 respectively . Fig . 5A ) . Conversely , EV entry was significantly reduced in the presence of each drug in a dose-dependent manner by 61 . 9±4 . 3% ( n = 4 , p<0 . 001 ) and 63 . 4±11 . 6% ( n = 4 , p = 0 . 009 ) compared to untreated cells ( Fig . 5A ) . The previously reported finding that MV penetration of BSC40 cells can be reduced by more than 90% using 10 mM mβCD [35] could not be repeated in MDDCs since concentrations greater than 2 . 5 mM were found to be toxic to these cells ( data not shown ) . The concentrations of mβCD used here reduced the content of cellular cholesterol by up to 30% compared to the untreated control , as measured by an Amplex Red assay ( data not shown ) , however the cholesterol content could not be further reduced due to the toxicity of higher drug concentrations . While MV was clearly less sensitive to cholesterol-depletion than EV , we wanted to confirm our hypothesis that MV entry might be increasingly inhibited if the MDDCs could tolerate more marked cholesterol depletion . To further elucidate the requirement for cholesterol in MV entry in MDDCs we firstly pre-treated the cells with mβCD , and found MV binding at 4°C was moderately inhibited by 17 . 9±11 . 1% ( n = 5 , Fig . 5B ) . Secondly , mβCD was added to cells either 60 min prior to , at the time of , or up to 60 min after the initiation of virus entry at 37°C . Once MV entry was initiated , the degree to which the addition of mβCD could inhibit entry was diminished until finally at 60 min post-entry , mβCD no longer had any effect on virus uptake ( Fig . 5C ) . The partial recovery of MV entry that occurred between treatment at −60 min and 0 min may be indicative of redistribution of the remaining cholesterol in the plasma membrane that was sufficient for MV entry . Thirdly , in the presence of mβCD , we were able to rescue and indeed enhance the entry of MV in MDDCs with the addition of soluble cholesterol ( Fig . 5D ) . Together these results show that cholesterol indeed contributes to MV entry in DCs . The CLIC pathway is the major pathway for the uptake of cholera toxin B and GPI-linked proteins and is marked by high concentrations of Flot-1 in the plasma membrane and the membranes of endocytic intermediates [4] , [36] . We found that MDDCs express Flot-1 at the RNA and protein level ( Fig . S4 ) . However , when VACV was bound to MDDCs at 4°C then allowed to enter over a course of 60 min , neither MV nor EV colocalised with Flot-1 at the time of virus binding or during entry ( Fig . S4 ) . Thus the entry of VACV does not appear to be associated with Flot-1 . DCs employ phagocytosis for the ingestion of large ( >500 nm ) particulate antigens via Fcγ and complement receptors . We used aggregated IgG and a neutralising CD18 mAb respectively to block each of these receptors and found no reduction in the binding or entry of MV or EV in MDDCs ( data not shown ) . However , phagocytosis via other receptors , such as scavenger receptors , cannot be ruled out at this stage . Macropinocytosis is a non-receptor mediated pathway characterised by the extension of filopodia that fold back onto the cell membrane to form large , irregular macropinosomes . It is a constitutive process in DCs enabling them to sample and concentrate large quantities of soluble antigen and contributes to efficient MHC class I and class II presentation to T cells [37] , [38] . Macropinocytosis also provides a means of entry into host cells for several pathogens including bacteria [39] , [40] and viruses [41]–[44] . As mentioned previously , the MV form of VACV enters HeLa cells via macropinocytosis [23] , [45] . Macropinocytosis is dependent on ATP , actin and an increase in intracellular Ca2+ for membrane ruffling and the formation of filopodia and depends on cholesterol but not dynamin [34] , [46] , [47] . To test whether macropinocytosis is also involved in VACV entry in DCs we used three commonly used inhibitors of macropinocytosis–rottlerin , 5- ( N-ethyl-N-isopropyl ) amiloride ( EIPA ) and dimethyl amiloride ( DMA ) . Amilorides inhibit the Na+/H+ ion exchange pump in the plasma membrane affecting the intracellular pH , resulting in the cessation of macropinocytosis , however the mechanism of rottlerin inhibition is unknown [48] . EV entry was significantly reduced by 56 . 3±6 . 9% ( n = 3 , p = 0 . 023 ) with rottlerin , 65 . 8±8 . 6% ( n = 3 , p = 0 . 019 ) with DMA and 74 . 3±3 . 9% ( n = 3 , p = 0 . 038 ) with EIPA . In contrast , MV entry was modestly reduced in the presence of rottlerin ( 17 . 4±7 . 8% , n = 3 , p = 0 . 06 ) and DMA ( 33 . 9±14 . 9% , n = 3 , p = 0 . 020 ) but remained unaffected by EIPA compared to untreated cells ( Fig . 6A ) . We tested the specificity of the three drugs for macropinocytosis in MDDCs by assessing their ability to inhibit uptake of the classical fluid-phase marker Lucifer Yellow , without affecting transferrin uptake which is via receptor-mediated endocytosis ( Fig . S5 ) . Both rottlerin and DMA effectively inhibited Lucifer Yellow uptake , however DMA equally inhibited transferrin uptake . In contrast , rottlerin had only a minimal effect on transferrin uptake , consistent with previous reports [48] . EIPA was actually more effective at inhibiting transferrin than Lucifer Yellow uptake . Therefore in MDDCs , rottlerin can be considered a specific macropinocytosis inhibitor , whereas the other two drugs are less specific . Since others have reported that EIPA blocks uptake of MV in HeLa cells [23] we determined whether the effect of this drug was cell type-dependent . Despite having no effect on MV uptake in MDDCs , EIPA did indeed block uptake of MV and EV in HeLa cells ( Fig . S5 ) , consistent with the previous report , demonstrating that the effects of EIPA are cell type-dependent . We wanted to further investigate whether the small reduction in MV entry as a result of rottlerin treatment was similar to that observed with the cholesterol inhibition studies where MV entry was less sensitive to perturbation than EV and the MDDCs were able to partially recover from the effects of the drug treatment sufficiently for MV entry to occur . To address this , we used a drug treatment time course , adding rottlerin either 30 min before , at the time of , or up to 60 min after initiating virus entry at 37°C . EV entry was clearly blocked with rottlerin treatment prior to virus entry and the effect diminished as rottlerin was added at later times after virus entry had begun to take place ( Fig . 6B ) . Although the effect on MV was less significant , the trend was the same as for EV which suggests that a proportion of MV is entering via macropinocytosis . Additionally , we assessed whether using a higher MOI with MV was masking the effect that was visible with EV with these and several other of the entry inhibitors we have employed but when we repeated the experiments using a high MOI ( 10 ) versus a low MOI ( 1 ) for MV the results were identical ( data not shown ) . Macropinocytosis in various cell types is dependent on several kinases , including phosphotidylinositol-3-kinase ( PI ( 3 ) K ) and protein kinase C ( PKC ) which are involved in the signalling pathways that promote membrane ruffling and macropinosome formation , although it has been shown that PKC is not critical for macropinocytosis in DCs [48] . We found that both MV and EV entry in MDDCs was significantly reduced in the presence of wortmannin , a PI ( 3 ) K inhibitor , but not in the presence of GF109203X , a small molecule inhibitor of PKC ( Fig . 6C ) . MV entry was decreased by up to 72 . 5±9 . 3% ( n = 3 , p = 0 . 003 ) and EV by 80 . 3±8 . 8% ( n = 3 , p<0 . 001 ) by wortmannin , implicating the involvement of PI ( 3 ) K in VACV entry in MDDCs . Finally , we examined VACV uptake in the presence of another fluid-phase marker , high molecular weight dextran , by confocal microscopy . We observed that both MV and EV considerably colocalised with dextran-Texas Red ( Fig . 6D ) . After 15 min this was 29 . 3±10 . 8% and 29 . 7±9 . 5% for MV and EV respectively , increasing to 42 . 5±3 . 0% and 35 . 1±3 . 3% respectively after 30 min . Having established that VACV entry in MDDCs is dependent on ATP , actin , intracellular Ca2+ and cholesterol but not dynamin ( all features of macropinocytosis ) , the pattern of inhibition of VACV entry by rottlerin and DMA and reliance on PI ( 3 ) K together with its colocalisation with dextran strongly suggest that VACV enters DCs by macropinocytosis . For EV this is the major route of entry however , it appears that this is a sub-dominant pathway for MV and it is likely that this form of the virus utilises multiple , redundant entry mechanisms . Finally , we investigated the fate of VACV upon entry into DCs . Little is known about the trafficking of macropinosomes , however , their destination seems to depend on the nature of the cargo [49] . We looked for colocalisation of the virus with the early and late endosomal markers , EEA1 and CD63 and the lysosomal marker , Lamp2 . Neither MV nor EV colocalised significantly with EEA1 over the course of 60 min of virus entry ( Fig . 7A ) . Furthermore , neither form of VACV colocalised with CD63 ( data not shown ) or Lamp2 ( Fig . 7B ) . We also assessed the effect of bafilomycin A which prevents the acidification of intracellular compartments , on viral gene transcription and found it to be unaltered for two genes for both MV and EV ( Fig . 7C and data not shown ) . This was consistent with the fact that we did not see any degradation or quenching of the viral GFP signal by flow cytometry over time , in the presence or absence of bafilomycin A , that would be induced if the virus accessed an acidic compartment . Finally , to confirm that the macropinocytic pathway we had been inhibiting in our flow cytometry assay does in fact lead to bona-fide infection of the DCs , we measured viral gene expression in the presence of representative inhibitors . LatA , mβCD , EGTA/AM , rottlerin and wortmannin all blocked immediate early gene transcription for both MV and EV ( Fig . 8 ) . Thus VACV is taken up by macropinocytosis into a compartment that is distinct from the endolysosomal pathway in DCs and does not depend on low pH to release virus cores into the cytoplasm where viral gene transcription takes place . Elucidating the mode of uptake of VACV by DCs is necessary in order to fully understand the biology of the virus and also vaccine systems that involve VACV vectors . VACV infection of DCs induces apoptosis , but this is somewhat delayed , not occurring until 48 h after infection with WR strain . Infection in DCs is abortive and limited to the production of early proteins but direct presentation of viral antigens by infected DCs can be detected in the lymph nodes between 6–24 h hours following infection [50] , [51] . It is highly likely that epidermal and perhaps dermal DCs are infected in vivo , in addition to keratinocytes , and contribute to direct priming of CD8+ CTLs . Expression of early viral genes may also trigger cytoplasmic pattern-recognition receptors in DCs and influence subsequent antigen presentation to bystanders . Furthermore , in the case of virus entry that does not result in “productive” infection ( in the sense of viral gene transcription ) , the compartment the virus enters in DCs will also determine whether MHC class II loading and presentation occurs . Thus the route of VACV entry into these cells is of critical importance to understanding the immunobiology of VACV . With respect to future VACV-based vaccines , MV is the likely important form of the virus . However , a replication-competent vaccine would lead to the production of EV in target cells at the site of vaccination and as these particles are thought to be responsible for long-range spread of the virus within the body and are more resistant to antibody neutralisation , DC capture and presentation of this form of VACV to T cells may play an important role in containing and limiting the infection . Thus both virus forms need to be studied . The present study builds on the previous report of Drillien et al [26] , who observed MV inside vesicles in MDDCs , to further define the entry pathway of VACV in these specialised antigen presenting cells . We have shown that VACV is taken up by MDDCs via an endocytic pathway that is independent of clathrin , caveolin , dynamin and flotillin but is dependent on ATP , actin , intracellular calcium , host cell membrane cholesterol and PI ( 3 ) K . The pathway is not mediated by CLRs and does not deliver VACV to early endosomes or lysosomes or progress to an acidic pH . For EV , this pathway is predominantly macropinocytosis . However , MV was consistently more resistant to entry inhibitors and whilst macropinocytosis contributed to a proportion of MV entry , this form of VACV likely uses multiple entry pathways in MDDCs including other clathrin- and caveolin-independent endocytic pathways . Our knowledge of the intricacy of endocytic pathways utilised by mammalian cells is rapidly expanding . Along with the well-defined clathrin- and caveolin-dependent pathways characterised by their requirement for dynamin , additional dynamin-independent pathways , separated by their dependence on various small GTPases ( Rac1 , Cdc42 , ARF6 ) are beginning to be defined [4] , [5] . Macropinocytosis and the CLIC pathway fall into the latter category . Phagocytosis is generally discriminated from other forms of endocytosis by the size of the particle being ingested and by morphological features–the extension of pseudopods around the particle rather than the invagination of the cell membrane , and the close-fitting nature of the phagosome due to multiple receptor-particle interactions . With dimensions of 250–350 nm , VACV falls between the generally accepted upper size limit of endocytosis ( 100 nm ) and just below the lower size limit of phagocytosis ( 500 nm ) . Macropinosomes however can range in size from a few hundred nanometers up to several micrometers in diameter [38] . In addition to the size restrictions on clathrin- and caveolin-mediated endocytosis , our data has ruled out these modes of uptake for VACV entry in MDDCs . The cholesterol inhibitor Fil , which does not affect clathrin-mediated endocytosis [52] , did have an effect on the entry of both MV and EV and we found expression of caveolin-1 to be undetectable at the protein level in MDDCs , consistent with previous observations [53] . Finally , both clathrin- and caveolin-mediated endocytosis require dynamin for the scission of endosomes from the plasma membrane whereas our results indicate that dynamin is not required for VACV entry in MDDCs . Dynamin is also required for phagocytosis although its role is in the release of secretory vesicles that supply new membranes to the growing pseudopods . In macropinocytosis , the closure and scission of macropinosomes is thought to be carried out by CtBP-1/BARS and regulated by Pak1 activity [42] . There are conflicting reports about the dependence of VACV on dynamin during fluid-phase uptake in HeLa cells . One study found that MV entry was sensitive to Dynasore , DynII siRNA and the dominant negative DynI K44A mutant ( but not the dominant negative DynII K44A mutant ) , concluding that dynamin was essential for VACV entry [45] , whereas others found similarly that the DynII mutant had no effect on MV entry in the same cell type , but nor did similar concentrations of Dynasore and thus concluded that MV entry was independent of dynamin [23] . In MDDCs , we found the use of small molecule dynamin inhibitors to be more effective than transfection with siRNA or dominant negative mutants and our results with Dynasore and Bis-T-23 were consistent with the latter report , indicating a dynamin-independent uptake mechanism . Several lines of evidence point towards a macropinocytic uptake mechanism for VACV in DCs . The dependence on ATP , actin , membrane cholesterol and PI ( 3 ) K as well as independence from dynamin are all consistent with this pathway . Furthermore , macropinocytosis has been shown to depend on a slow rise in the intracellular Ca2+ concentration in MDDCs [46] so the acute sensitivity of both MV and EV to treatment with the intracellular Ca2+ chelator , EGTA/AM , but not non-membrane permeable EGTA , is also consistent with this pathway . We and others [48] have shown that rottlerin is a more specific inhibitor of macropinocytosis in MDDCs than either DMA or EIPA . Rottlerin was originally described as a specific inhibitor of the delta subunit of protein kinase C however it has since been shown to affect multiple kinases via a complex , indirect mechanism and is likely not to be a specific kinase inhibitor at all [54] , [55] . Currently its molecular target is unknown although it does affect dynamic actin reorganisation , preventing the spreading of DCs [48] . As mentioned above , macropinocytosis depends on a slow rise in the intracellular Ca2+ concentration [46] and interestingly , rottlerin is known to be a potent activator of the large conductance voltage , Ca2+-activated K+ ( BK ) ion channel . This channel belongs to the same family as the voltage-gated K+ ( Kv ) channel which is responsible for regulating the influx of Ca2+ into DCs in response to maturation stimuli [56] . By activating the BK channel , rottlerin stimulates a massive outflow of current in heart and nervous tissue [57] . It is tempting to speculate that if rottlerin acts on the S4 domain that is common to both BK and Kv channels it could potentially prevent the influx of Ca2+ that is required for macropinocytosis to proceed , accounting for its inhibitory effect on VACV entry . Finally , both MV and EV colocalised with dextran in macropinosomes . Even though the majority of dextran is taken up via mannose receptor-mediated endocytosis , approximately 25% is macropinocytosed and cannot be blocked by mannan [38] , [48] . Since mannan has no effect on the entry of MV or EV , colocalisation between the virus and dextran is likely to occur in macropinosomes . The trafficking of macropinosomes is currently poorly understood although the destination for macropinocytosed cargo seems to depend on the nature of the cargo itself . While macropinosomes have been shown to deliver ovalbumin to distinct compartments that acquire the lysosomal protein Lamp1 and MHC class II [38] , others have shown that macropinocytosed beads and dextran enter a compartment that acquires the early endosomal antigen EEA1 but they do not go on to acquire Lamp1 or MHC class II [46] . The subsequent trafficking of viruses known to enter cells via macropinocytosis has not been examined . We found that VACV does not enter the classical endolysosomal pathway in DCs , as evidenced by its lack of colocalisation with early and late endosomal and lysosomal markers . DCs maintain a neutral or only mildly acidic pH in early phagosomes and macropinosomes [58] , [59] enabling the storage of antigen taken up in the periphery while the DC migrates to the lymph node . Consistent with this entry pathway are our data that suggest VACV does not access an acidic compartment or rely on low pH to enter the cytoplasm in DCs . Furthermore , the marked difference in the kinetics of entry of both VACV forms , particularly EV , between DCs and BS-C-1 cells may relate to the capacity of DCs to retain antigen during migration . Finally , although VACV has been shown to bind to cell-surface glycosaminoglycans , this interaction has proven to be cell-type dependent and previous work suggests that the VACV receptor ( s ) expressed on primary haematolymphoid cells may differ from epithelial cell lines since immune sera containing antibodies which blocked VACV binding to monocytes and activated T cells did not block binding to cell lines [17] . Furthermore , the receptor for VACV on T cells can be removed by trypsin [17] , as we saw with MDDCs , whereas trypsinisation of cell lines does not reduce VACV binding or infection [9] . A growing number of viruses have been shown to utilise CLRs expressed on DCs ( some of which are sensitive to trypsin , such as DC-SIGN [31] ) for entry , including HIV-1 [60] , adenovirus serotype 5 [61] , measles virus [62] , hepatitis C virus [63] , cytomegalovirus [64] and others . Most of the CLRs expressed on DCs contain cytoplasmic internalisation motifs [65] serving to enhance internalisation , degradation and subsequent presentation of antigen to T cells . Our finding that VACV , most notably EV with multiple glycosylated proteins in its envelope [8] , does not bind to CLRs distinguishes it from these other viruses and extends its capacity for immune evasion . In conclusion , both MV and EV forms of VACV utilise macropinocytosis for entry into MDDCs . Whilst this is the predominant entry mechanism for EV , MV was less sensitive to perturbations in cellular cholesterol levels and shut down of macropinocytosis , which suggests that it may utilise more than one dynamin-independent endocytic pathway . Our study is the first demonstration that EV can enter cells via a mechanism other than fusion with the plasma membrane . These results lay the foundation for further investigations in animal models to determine the significance of DC macropinocytosis of both MV and EV in vaccinia pathogenesis and use of vaccinia recombinants as vaccine candidates , for example , by examining the in vivo effects of amiloride or wortmannin-induced inhibition of macropinocytosis in mice on antigen presentation by various myeloid DC subsets [66] . Further elucidation of the fate of VACV inside DCs will contribute not only to our understanding of the biology of VACV interactions with the immune system but also the efficacy of vaccines employing VACV vectors and should assist their rational design . The following were kind donations: MV-neutralising murine monoclonal antibody ( mAb ) 7D11 , directed against the MV protein L1R from B . Moss ( NIH , Bethesda , MD; with permission from A . Schmaljohn , USAMRIID , Frederick , MD; [67] ) . Murine mAb AB1 . 1 , directed against the MV protein D8 from G . L . Smith ( Imperial College , London , UK ) and rat mAb 19C2 , directed against the EV protein B5 from J . Krijnse-Locker ( EMBL , Heidelberg , Germany [68] ) . Anti-GFP rabbit polyclonal Ab was from Molecular Probes ( Eugene , OR ) , DC-SIGN mAb ( AZN-D1 ) was from Beckman-Coulter ( Fullerton , CA ) , flotillin-1 ( Flot-1 ) rabbit polyclonal Ab was from Abcam ( Cambridge , UK ) and Flot-1 ( clone 18 ) , mannose receptor ( MR; 19 . 2 ) , caveolin-1 ( Cav-1; 2234 ) , EEA1 ( clone 14 ) and Lamp2 ( H4B4 ) mAbs , goat anti-mouse IgG ( GAM ) -PE and streptavidin-PE were purchased from BD Pharmingen ( Franklin Lakes , NJ ) . Goat anti-rabbit Ig ( GAR ) -FITC was from Sigma-Aldrich ( St . Louis , MO ) . GAM-546 , GAR-546 and donkey anti-rat IgG ( DAR ) -594 were purchased from Molecular Probes . GAM-IRdye-680 was from LI-COR Biosciences ( Lincoln , NB ) . Monocyte-derived DCs ( MDDCs ) were generated by culturing human CD14+ cells , positively selected from PBMCs using magnetic microbeads ( Miltenyi Biotec , Gladbach , Germany ) , in RPMI/10% FCS ( RF10 ) with 7 . 5 ng/mL IL-4 and GM-CSF ( ProSpec , Rehovot , Israel ) for 6 days [69] . A WR strain VACV with EGFP tagged to a core protein , vA5L-GFP-N ( kindly donated by G . L . Smith , Imperial College , London [70] ) was used for both MV and EV preparations . MV stocks were grown in RK13 cells for 48 h as previously described [71] and purified on a discontinuous 16–32% Optiprep ( Axis-Shield , Oslo , Norway ) gradient in a SW28 rotor ( Beckman Coulter ) at 28 000 rpm for 1 h at 4°C . Purified MV banded at the 28–32% interface which was harvested and pelleted on a 50% Optiprep cushion in a SW41 Ti rotor ( Beckman Coulter ) at 14 000 rpm for 45 min . The purity of the virus stock was confirmed by immunofluorescence and electron microscopy and SDS-PAGE followed by a general protein stain and western blotting for D8 and GFP proteins ( Fig . S1 ) . MV was always sonicated for 45s at 130W to disrupt any aggregates prior to infecting cells . Fresh EV stocks were grown for each experiment in BHK-21 cells as described previously [14] . Supernatants were harvested after 24 h , clarified by low speed centrifugation at 1200 rpm for 10 min to remove cellular debris and concentrated by 3 rounds of centrifugation through 100 kDa Amicon Ultra-15 filters ( Millipore , Billerica , MA ) at 2000 rpm for 20 min at 4°C . Any contaminating MV and damaged EV were neutralised with the 7D11 mAb at 1∶400 for 1 h at 37°C . Viruses were titered by plaque assay on BS-C-1 cells . The percentage of intact EV was calculated as the ratio of the viral titres in the presence:absence of 7D11 mAb ( Fig . S2 ) and the presence of intact EV was confirmed by immunofluorescence microscopy as previously described ( Fig . S3; [72] ) . MDDCs were spinoculated with vA5L-GFP MV ( MOI 20 ) or EV ( MOI 0 . 5–5 ) , unless otherwise stated , at 650 g for 1 h at 4°C . As passive binding of VACV to MDDCs at 4°C is minimal , we used spinoculation to enhance both MV and EV binding and enable the study of entry events . Spinoculation was not found to be detrimental to cell viability , consistent with previous reports [14] . Following spinoculation , cells were retained on ice or resuspended in warm RF10 and incubated at 37°C for the indicated time to allow bound virus to enter the cells . Residual surface-bound virus was removed by treatment with 0 . 5% trypsin for 10 min at 37°C and cells were washed once in RF10 then twice more in ice cold PBS . Inhibitors were purchased from Sigma-Aldrich ( St . Louis , MO ) unless otherwise specified . Ethyleneglycol-bis ( β-aminoethyl ) -N , N , N′ , N′-tetraacetoxymethyl ester ( EGTA/AM ) was from Calbiochem ( San Diego , CA ) . Bis-T-23 and Dyngo7a ( Dynasore ) were developed in-house [73] . MDDCs were pre-treated in serum-free media in the absence or presence of inhibitor for the times and concentrations indicated . Cells were then subjected to the virus entry assay , with spinoculation and virus entry occurring in the presence of the inhibitor , and fixed in 4% paraformaldehyde ( PFA ) . The percentage of GFP-positive cells was analysed by flow cytometry and expressed as a percentage of the no drug control ( designated as 100% entry ) . For depletion of ATP , MDDCs were washed and resuspended in glucose-free RPMI ( Invitrogen ) with the addition of either 10 mM D-glucose ( no drug control ) or 10 mM D-deoxyglucose ( Sigma-Aldrich ) and 10 mM sodium azide to prevent glycolysis . Depletion of >90% of ATP was confirmed using an ATP Determination Kit ( Molecular Probes ) according to the manufacturer's instructions . Depletion of cellular cholesterol was confirmed using an Amplex Red assay kit ( Molecular Probes ) according to the manufacturer's instructions . For inhibition of transferrin or Lucifer Yellow uptake , MDDCs pre-treated with dynamin or macropinocytosis inhibitors as described above were then incubated with warm media containing 5 µg/mL Alexafluor-647-labelled transferrin ( Tf-647; Molecular Probes , Eugene , OR ) or 200 µg/mL Lucifer Yellow ( Sigma-Aldrich ) respectively for 15 min at 37°C . Cells were placed on ice to halt endocytosis and washed three times with ice-cold PBS . Surface-bound transferrin was removed by an ice-cold acid wash ( 0 . 2 M CH3COOH , 0 . 5 M NaCl , pH 2 . 8 ) for 15 min . MDDCs were then fixed in 4% PFA and analysed by flow cytometry . The mean fluorescence intensity ( MFI ) of the sample minus the background MFI ( unpulsed cells ) was expressed as a percentage of the no drug control MFI . For inhibition of CLR-mediated virus binding cells were incubated in ice-cold binding buffer ( RPMI 1640 , 10 mM HEPES , 1% BSA; pH 7 . 4 ) with mannan , EGTA , D-mannose or neutralising anti-DC-SIGN mAb at the concentrations indicated for 40 min at 4°C . Except EGTA treated samples , cells were washed in ice-cold binding buffer to remove excess inhibitor . EGTA-treated samples were not washed in order to maintain calcium-depleted conditions . Cells were then spinoculated with vA5L-GFP MV ( MOI 50 ) or EV ( MOI 5–10 ) at 4°C , washed three times in ice-cold PBS and fixed with 4% PFA for analysis by flow cytometry . Alternatively , cells were resuspended in DNA lysis buffer for qPCR . Biotinylated [31] , monomeric HIV-1 gp120 ( SLCA-1 primary R5 strain [74]; kindly provided by Dr . J . Arthos , National Institutes of Health , Bethesda , MD ) was used at 10 µg/mL in the same binding assay and detected with streptavidin-PE ( 0 . 5 µg/mL ) . For inhibition of HIV-1 infection , cells treated with inhibitors as above were infected with HIV-1 ( BaL strain ) at MOI 10 for 3 h at 37°C then washed and cultured for 72 h followed by qPCR analysis . Cells were lysed and RNA extracted using a RNeasy Plus Mini Kit ( Qiagen , Valencia , CA ) according to the manufacturer's instructions . RNA was reverse transcribed into cDNA using a High Capacity cDNA Reverse Transcription Kit ( Applied Biosystems , Foster City , CA ) . Copies of the VACV DNA genome or viral transcripts were detected by primers to the virally encoded GFP ( fwd: 5′-GACGTAAACGGCCACAAGTT-3′; rev: 5′-GAACTTCAGGGTCAGCTTGC-3′ ) or immediate early genes E3L ( ORF number VACV059 in Western Reserve strain; fwd:5′-TATCCGCCTCCGTTGTCATA-3′; rev:5′-CGAAGGAGCTACTGCTGCAC-3′ ) and B2R ( ORF number VACV184 in Western Reserve strain; fwd:5′-TGGAGCACTGCTGCCTATGT-3′; rev:5′-CTCGTACCCGATTCCGCTTA-3′ ) ( www . poxvirus . org ) using Platinum SYBR Green qPCR SuperMix-UDG ( Invitrogen ) in a Corbett Research Rotor-Gene ( Corbett Life Sciences , Sydney , Australia ) with the following cycling conditions: 50°C for 2 min , 95°C for 10 min , 40 cycles of 95°C for 15 sec and 60°C for 1 min and normalised to GAPDH as previously described [75] . HIV-1 DNA copies were quantified by detecting HIV-1 LTR-gag DNA using primers and a molecular beacon [76] and normalised to albumin copy number as previously described [75] . Cav-1 primers: Fwd: 5′-ACAGCCCAGGGAAACCTC-3′ . Rev: 5′-GATGGGAACGGTGTAGAGATG-3′ . Cells were lysed at 10×106/mL ( 10 mM HEPES , 150 mM NaCl , 1% Triton X-100 , 10 mM CaCl2 and 100 mg/L protease inhibitor cocktail ( Sigma-Aldrich ) ) at 4°C for 1 h . The soluble fraction was analysed for Flot-1 and insoluble fraction for Cav-1 . Lysates were separated by SDS-PAGE ( 12% gel ) and transferred to nitrocellulose membranes ( Amersham Pharmacia Biotech , Arlington Heights , IL ) . Membranes were blocked overnight with Odyssey blocking buffer ( LI-COR ) and probed with Flot-1 mAb ( 1∶500 ) or Cav-1 mAb ( 1:5000 ) and GAM-IRdye-680 . Membranes were imaged using the Odyssey Infra-red Imaging System ( LI-COR ) . NIH/3T3 cells were used as a positive control . For flow cytometric analysis , MDDCs or NIH/3T3 cells were permeabilised and stained with Flot-1 pAb ( 5 µg/mL ) followed by GAR-FITC ( 10 µg/mL ) or Cav-1 mAb ( 5 µg/mL ) followed by GAM-PE ( 10 µg/mL ) . The percentage of antigen-positive cells was analysed by flow cytometry . Data are presented as means ± SEM and n represents the number of experiments in independent donors . The statistical software packages SPSS for Windows , Version 14 , and S-PLUS Version 6 . 2 were used to analyse the data for the VACV entry inhibition studies . Linear mixed effects models were used to quantify the dose response of the log transformed outcome to different drugs . Two-tailed tests with a significance level of 5% were used throughout .
Vaccinia virus ( VACV ) is a relative of the smallpox virus and was used for many decades as a successful vaccine that contributed to the eradication of smallpox . Today , through genetic recombination technology , VACV shows potential as a modern vaccine for many unconquered diseases including HIV and cancer . Dendritic cells ( DCs ) are a specialised subset of immune cells that initiate adaptive immune responses and exploiting the interaction between VACV and DCs , which has not been well studied , may be a key to improving the efficacy of these vaccines . In this study we investigated the mechanisms by which VACV binds to and enters DCs . Here , we examined both the abundant mature virus form of VACV as well as the less common , poorly studied extracellular form . We found that VACV does not bind to the common pathogen-uptake C-type lectin receptors expressed on DCs and that the virus enters DCs via macropinocytosis—a fluid-phase uptake process . Furthermore , the virus is not delivered to the conventional endolysosomal antigen processing pathway in these cells . Our study provides new insights into VACV biology and into possible mechanisms of action of VACV as a recombinant viral vaccine vector which may assist in their rational design in the future .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "infectious", "diseases/viral", "infections", "virology/host", "invasion", "and", "cell", "entry", "immunology/innate", "immunity" ]
2010
A Differential Role for Macropinocytosis in Mediating Entry of the Two Forms of Vaccinia Virus into Dendritic Cells
Despite extensive theory , little is known about the empirical accumulation and evolutionary timing of mutations that contribute to speciation . Here we combined QTL ( Quantitative Trait Loci ) analyses of reproductive isolation , with information on species evolutionary relationships , to reconstruct the order and timing of mutations contributing to reproductive isolation between three plant ( Solanum ) species . To evaluate whether reproductive isolation QTL that appear to coincide in more than one species pair are homologous , we used cross-specific tests of allelism and found evidence for both homologous and lineage-specific ( non-homologous ) alleles at these co-localized loci . These data , along with isolation QTL unique to single species pairs , indicate that >85% of isolation-causing mutations arose later in the history of divergence between species . Phylogenetically explicit analyses of these data support non-linear models of accumulation of hybrid incompatibility , although the specific best-fit model differs between seed ( pairwise interactions ) and pollen ( multi-locus interactions ) sterility traits . Our findings corroborate theory that predicts an acceleration ( ‘snowballing’ ) in the accumulation of isolation loci as lineages progressively diverge , and suggest different underlying genetic bases for pollen versus seed sterility . Pollen sterility in particular appears to be due to complex genetic interactions , and we show this is consistent with a snowball model where later arising mutations are more likely to be involved in pairwise or multi-locus interactions that specifically involve ancestral alleles , compared to earlier arising mutations . New species evolve via the accumulation of genetic changes that confer ecological differences and , in sexually reproducing organisms , reproductive isolating barriers . Of these barriers , hybrid sterility and inviability are thought to be due to deleterious interactions between mutations , at two or more loci , that have arisen and fixed in diverging lineages ( ‘Dobzhansky-Muller Incompatibilities’ [DMIs]; [1]–[3] . After several decades of intense empirical interest , the genetic basis of these loci is starting to be understood . In many cases , Quantitative Trait Locus ( QTL ) mapping has identified chromosomal regions that contribute to the expression of reproductive isolation at specific reproductive stages ( e . g . male sterility ) among lineages e . g . , [4]–[12] . In fewer cases , the molecular loci and specific mutations responsible for the expression of hybrid problems have been identified ( reviewed in [13] , [14] ) . Despite these emerging data , most studies have yet to reveal the precise origin and historical accumulation of hybrid sterility and inviability loci across a genome through time . These data are critical for understanding both the evolutionary dynamics of lineage divergence and the underlying genetics of speciation . Distinguishing the isolation-causing mutations that arose early between diverging lineages is essential for identifying mechanisms that predominate during speciation itself , rather than after divergence is substantially complete . Whether incompatibilities that arise early versus later in species divergence have different genetic properties ( e . g . , effect sizes , kinds of mutational change , and classes of genes ) or evolutionary dynamics remains unknown . Understanding the historical origin of isolation loci among species across a whole genome also enables empirical tests of analytical predictions about the temporal accumulation of these mutations , and the nature and complexity of their underlying genetic interactions [15]–[18] . For example , mathematical theory predicts that isolation-causing interactions ( DMIs ) should accumulate at a pace that is faster than linear with time ( i . e . , the ‘snowball effect’ , [15] ) – a prediction that requires data on the number of isolation loci in species pairs that span a range of divergence times [3] . Similarly , patterns of incompatibility sharing across species pairs can be used to estimate the relative frequencies of different types of incompatibilities , including derived–derived versus derived–ancestral incompatibilities [19] ( and see below ) . These data in turn enable the dynamics and genetics of reproductive isolation to be compared with other well-understood evolutionary processes , such as adaptation [20] . Empirical studies of the evolutionary accumulation of isolation loci are currently limited to two approaches; individually , neither approach is able to assign the origin of all known reproductive isolation loci in a genome to specific evolutionary branches of a phylogenetic tree . First , some studies have inferred the history of nucleotide changes in individual genes known to contribute to reproductive isolation ( reviewed in [13] ) . These analyses have revealed patterns consistent with repeated nucleotide substitutions at the target locus , in some cases in more than one lineage , e . g . , [21]–[26] . Such studies can identify evolutionary branches along which many or most of these mutations have occurred . However , because the specific molecular loci underlying reproductive isolation phenotypes are unknown in most cases , these analyses remain uncommon . Moreover , they cannot assess genome-wide patterns of isolation accumulation among species because they are almost always limited to the analysis of single loci . Alternatively , other studies have examined the genome-wide pattern of accumulation of all detectable loci contributing to reproductive isolation ( i . e . DMIs ) , using QTL data from two or more species crosses from the same closely related group , e . g . , [27]–[29] . Such comparative QTL data can evaluate general patterns of evolutionary accumulation of DMIs with genetic distance ( e . g . , the ‘snowball effect’; [30] , [31] ) or the classes of genetic interactions that underpin reproductive isolation , e . g . [32] . However , these analyses do not assign individual isolation mutations to particular evolutionary branches , and therefore cannot address the order in which specific causal mutations arose during the history of divergence between species . One alternative to these approaches is to combine information from comparative mapping data , and phylogenetic relationships among species involved in these mapping experiments , to infer the order and timing of evolutionary changes responsible for reproductive isolation [20] . Comparative mapping in different species pairs can reveal two classes of isolation QTL: those that are unique to individual species crosses , and those localized to the same chromosomal region in more than one species pair ( co-localized/shared QTL ) . Loci unique to a single species pair must have evolved along evolutionary branches that are unique ( unshared ) among the species in the comparison; in contrast , a QTL that is shared among multiple species pairs must involve a genetic change along an evolutionary branch that is shared by all species involved in the comparison [20] , [30] ( Figure S1 ) . Although this reasoning is straightforward , inferences from ‘shared’ reproductive isolation loci rely on the assumption that these co-localized QTL are evolutionarily homologous , that is—they are caused by the same underlying mutational change . However , because QTL regions frequently span multiple genes , QTL co-localization could also occur because different isolation-causing mutations happen to occur in close proximity [27] . To draw strong inferences about evolutionary events from comparative mapping data , therefore , requires experiments that directly assess whether co-localized sterility QTL are indeed homologous or not . Whether mutations are identical ( i . e . occur in the same locus ) can be experimentally evaluated by testing for genetic complementation when combined via crossing . Analogous ‘tests of allelism’ can be performed to assess whether co-localized QTL are homologous , e . g . , [33] , as long as these loci act recessively . In the case of co-localized ( and recessively acting ) sterility QTL from different species pairs , if a hybrid that combines both QTL shows restored ( rescued ) fertility , the underlying mutation ( s ) are inferred to be different because sterility has been complemented ( Figure 1 ) . Conversely , when fertility remains low in hybrids , either the underlying genetic lesion occurs in the same locus or additional interactions between these loci contribute to retaining low hybrid fertility ( see Results and Discussion ) . Cross-species tests of allelism can therefore clarify whether co-localized QTL are homologous , without requiring specific knowledge of the underlying molecular lesions . We have previously mapped QTL for hybrid pollen and/or seed sterility in several interspecific crosses among Solanum species [7] , [27] , [30] . Because of karyotypic co-linearity and common markers between these species , we can delineate chromosomal regions in which a QTL for the same sterility trait appears in more than one species pair [27] . In this study , we evaluate evidence for homology at three such co-localized hybrid sterility QTL using tests of allelism , and find different histories for each locus . With these data , and data on QTL that are unique to each species pair , we infer the timing and pattern of accumulation of all known sterility-causing mutations among these three species . We then evaluate the consistency of these findings with current theory on the evolutionary accumulation of reproductive isolation genes , including incompatibilities based on interactions between loci that have sequentially fixed along a lineage and/or that involve multi-locus interactions . In addition to examining the properties of earlier versus later fixing mutations , our data supports models of non-linear ( ‘snowballing’ ) accumulation of the loci underlying both seed and pollen sterility , although the details of this non-linear accumulation differ between the two postzygotic isolation traits . Interpreting these findings in light of theoretical predictions , our results suggest that these traits are underpinned by different classes of genetic interaction , and possibly fixed by different evolutionary dynamics . Our analysis examined loci contributing to reproductive isolation among three species in the plant genus Solanum ( Solanum lycopersicum ( SL ) , S . pennellii ( SP ) , and S . habrochaites ( SH ) ) , whose phylogenetic relationships are well understood ( Figures 2–4 and Text S1 ) . Previous QTL mapping experiments in crosses between SL and SH [7] and between SL and SP [27] identified 8 and 7 QTL , respectively , associated with hybrid pollen sterility , and at least 4 and 4 QTL , respectively , associated with hybrid seed sterility ( Table S1 ) . In both mapping experiments , QTL were detected using introgression lines ( ILs ) , where short chromosomal regions from a donor species ( either SH or SP ) were introgressed into an otherwise isogenic recipient species ( SL ) background . Individual ILs in which fertility is significantly reduced are inferred to contain an allele ( QTL ) from the donor species that causes sterility when interacting with the recipient species' genetic background . Therefore , each QTL corresponds to one side of a DMI ( the donor allele from either SP or SH ) ; these experiments are not able to identify the location of the SL locus ( or loci ) with which this allele is interacting . Of the sterility QTL detected in these two experiments , three QTL appeared to be chromosomally co-localized ( Table 1 ) : one associated with reduced pollen fertility ( pf7 . 2 ) and two with reduced seed fertility ( sss1 . 2 , sss2 . 1 ) . All three loci act fully or partially recessively ( Table 1 ) . Although true complementation tests conventionally require that loci are fully recessive [34] , complementation tests can be successfully implemented for incompletely recessive loci when the heterozygous phenotype can be distinguished from the homozygous recessive phenotypes [35] as is the case for our three loci ( Text S1 ) . For partially recessive sterility loci , the expectations are equivalent to a conventional test of allelism ( Figure 1 ) : in the absence of complementation , fertility of the trans heterozygote will be indistinguishable from the ( low fertility ) homozygous recessive parental lines; in contrast , complementation is indicated by rescued fertility in the trans heterozygote up to at least the fertility of the more fertile heterozygous genotype . For each of these QTL , we crossed ILs that contained the relevant chromosomal region from each of SH and SP ( ILHH and ILPP respectively ) , in an otherwise SL genetic background ( Figure 1 ) . We compared the average pollen and seed fertility of the resulting F1 SH-SP QTL heterozygotes ( i . e . , ILHP and ILPH ) , to the pollen and seed fertility of SH or SP QTL homozygotes ( ILHH and ILPP ) and of the isogenic SL parent . For completeness , we assayed both pollen and seed fertility in every line ( results for the non-focal fertility measure are discussed in Text S2 ) . At each of the three target loci , we detected a strong genotype effect on fertility ( p<0 . 0001 , ANOVA; Table S2 and Text S2 ) . In addition , each locus showed different patterns of fertility in tests of allelism , including no evidence of complementation , complete complementation ( fertility restoration ) , and more complex patterns of fertility response ( Table 2 and Table S2 ) . Based on these observations , we can make inferences about the historical accumulation of reproductive isolation mutations at each of these QTL . For each of the three apparently co-localized QTL examined here , we can infer when the underlying mutation ( s ) evolved . Loci that are unique to a single species pair—sss1 . 2 . 2 and sss2 . 1—are inferred to have evolved on branches that are not shared between the two species pairs; therefore , the mutations underlying these two loci are assigned the SP-specific branch—the only branch exclusive to the SP×SL cross in these two pairs ( Figures 2C , 3C and 4C ) . In comparison , we assign our two inferred homologous alleles—pf7 . 2 and sss1 . 2 . 1—to the branch shared by both SP and SH after their split from their MRCA with SL ( Figures 2C and 3C ) . This placement assumes that the observed sterility effects are the result of mutations that arose ( i . e . were derived ) along the lineage that gave rise to SP/SH . The alternative is that sterility between SP/SH and SL at these shared loci is due to ‘derived-ancestral’ interactions [15] , where the shared SH/SP allele represents the ancestral state at this locus . Such derived-ancestral interactions arise when multiple mutations occur sequentially along one evolutionary branch , so that later derived mutations arise upon a genetic background of loci that have already experienced new ( derived ) substitutions . For each of our shared QTL to be due to derived-ancestral interactions , both the causal mutation and the mutation at the other locus/loci with which it interacts must occur on the SL-specific branch . However , at least two lines of evidence indicate that this alternative scenario does not describe the evolutionary history of pf7 . 2 and sss1 . 2 . 1 ( Text S2 ) . In particular , in QTL mapping experiments with two additional species that are more closely-related to SL ( Figure S3 ) , we do not detect pollen or seed sterility loci at these chromosomal locations; these other species should also manifest these QTL when crossed to SL , if the causal mutations were derived along the terminal branch leading to SL . The alternative is that SL shares the same derived alleles at both pf7 . 2 and sss1 . 2 . 1 with these 2 other species . However , this requires that both substitutions underlying each putative derived-ancestral interaction must have arisen and fixed along an extremely short evolutionary branch shared by these three species , but not by SH or SP ( Figure S3 ) , a hypothesis that is less parsimonious than assuming a single derived mutation for each locus along the much longer shared SH/SP branch ( Text S2 ) . In addition to the three co-localized QTL examined in our tests of allelism , earlier mapping studies [7] , [27] revealed 13 pollen and 5 seed sterility QTL that were unique to each interspecific cross ( Table S1 ) . Using the same logic as for lineage-specific mutations above , mutations underlying these additional pollen and seed sterility QTL can be assigned to either SP or SH terminal branches , depending upon the cross in which the loci were identified . With these data and the results of our tests of allelism , we are therefore able to assign every known sterility locus among these two species pairs to a mutation event on a specific evolutionary branch , conservatively assuming that each QTL is underpinned by one mutation ( Figure 5 ) . Finally , note that making general inferences from the resulting patterns of shared versus non-shared isolation loci relies on the assumption that we have not systematically failed to detect co-localized QTL due to low power in our previous mapping experiments . This assumption appears to be reasonable; we find that even with a substantially more permissive statistical threshold for identifying QTL in each original mapping experiment ( see Text S1 ) , we do not uncover disproportionately more co-localized QTL than are detected with the more stringent standard cutoffs originally used to identify the QTL analyzed here ( Table S8 ) . Our data on the phylogenetic distribution of shared and unique sterility-causing loci ( Figure 5 ) can be used to address several questions about the genome-wide accumulation of mutations that underlie the expression of hybrid sterility . First , we can assess whether ‘earlier’ versus ‘later’ arising mutations differ in their average phenotypic effect size on DMIs . Second , these data can be used to evaluate the temporal distribution of mutations contributing to pollen and seed sterility on our tree , given estimates of relevant branch lengths for this tree . Finally , based on patterns of incompatibility sharing , we can evaluate evidence for alternative models of incompatibility evolution using statistical comparisons in a phylogenetic context [19] . Implementing our cross-species tests of allelism and drawing general inferences from patterns of homologous and unique isolation loci relies on particular assumptions—about the expression of fertility phenotypes and our power to detect these loci in our mapping populations—that appear to be reasonable in our experiment ( see Results ) . Several additional assumptions about the nature of evolutionary transitions underlying our QTL also appear to be reasonable , but will require knowledge of the underlying mutations for final confirmation . In particular , we assume that loci identified as homologous in our tests of allelism are not due to independent mutations in the same underlying gene . If recessive sterility effects are due to independent change of function mutations within the same locus , these mutations are expected to complement in our experiments . However , tests of allelism will not be able to differentiate homologous from non-homologous mutations in the same gene , if these different mutations have identical phenotypic effects . For sterility loci , this is most likely when the causal changes are loss-of-function mutations; if two such null mutations independently occurred in the same locus , a test of allelism would indicate the underlying alleles were the same ( i . e . no fertility rescue would be observed in the ILHP and/or ILPH genotypes ) . Several factors indicate that this scenario is unlikely to explain our data . Foremost , there are no known cases where hybrid sterility effects arise from interactions between loci with simple loss-of-function mutations . Theoretically , most models of hybrid incompatibility are based on sterility arising from dysfunctional interactions between loci that continue to have functional roles on their own native genetic background [1]–[3] . Empirically , of the molecular loci currently known to cause hybrid sterility , almost all are functional on their own genetic background but dysfunctional on a hybrid background ( reviewed in [13] , [14] , [38] , [39] ) . However , there are some cases where gene duplication followed by loss events has led to the placement of ( still functional ) homologous loci in different chromosomal locations in different species . This ‘gene movement’ based on divergent resolution of duplicates in alternative lineages can lead to the segregation of null genotypes in recombinant hybrid populations , e . g . , [40]–[42] and reviewed in [14] , as predicted by one model of incompatibility evolution [43] , [44] . However , for gene movement or convergent loss-of-function mutations to explain our observations for ‘shared’ loci here , there must have been two independent gene movements , two independent loss-of-function mutations , or an independent movement and loss-of-function mutation , at the same locus in two different lineages ( SH and SP ) . This is unlikely to be the case , certainly for both of the loci ( pf7 . 2 , sss1 . 2 . 1 ) that we infer share homologous sterility alleles . Given this , and the large number of loci that could potentially contribute to dysfunctional sexual development in hybrids , it is more parsimonious to infer that co-localized sterility loci that show phenotypes consistent with allelism ( i . e . that do not complement ) , are underpinned by the same mutation rather than two independent mutations in the same locus . This inference can be confirmed with further fine-mapping and ultimate identification of the underlying loci . Similar logic indicates that it is more parsimonious to infer that loci identified in only one species cross are due to a single lineage-specific change , rather than an initially shared change that has been secondarily lost or ameliorated in one lineage , especially as the accumulation of postzygotic sterility loci is generally considered be irreversible [45] . Differentiating earlier versus later evolving mutations involved in DMIs , by placing the evolution of these changes on specific evolutionary branches , provides both specific and general insight into the historical progression and evolutionary dynamics of speciation . The early-evolving mutations inferred here ( pf7 . 2 and sss1 . 2 . 1 ) , for example , can be targeted for further genetic and functional characterization to examine the nature of changes that specifically accompanied the first stages of divergence among our species , and evaluate whether these differ from later-evolving substitutions . More generally , we can also use these empirical data to evaluate hypotheses about the genetic and evolutionary mechanisms underpinning divergence and speciation processes . At least three substantive conclusions about these processes emerge from our data: Tests of allelism can be used to assess whether isolation alleles detected between specific species are homologous with co-localized QTL detected in other crosses . Using this approach , in conjunction with data on loci that are unique to single species pairs , we infer the phylogenetic timing of mutations underlying all known reproductive isolation loci among three Solanum species . With these data , we determine which loci are associated with mutations that arose early versus late in lineage divergence between these species , compare properties of these loci , and observe that many of these isolation-associated mutations arose on more recent evolutionary branches . Using new phylogenetically informed analyses , we find clear support for the theoretical prediction that reproductive isolation loci accumulate non-linearly over evolutionary time . Moreover these analyses suggest that different sterility phenotypes having different underlying genetic architectures: seed sterility data are consistent with isolation due to pairwise epistasis , whereas pollen sterility data are consistent with more complex epistasis among loci that have experienced sequential fixations in one or both lineages . Therefore , while overall patterns of isolation accumulation fit a theoretical framework in which sterility is due to genetic interactions between alleles in diverging lineages , the complexity and nature of these interactions might differ depending upon the specific traits involved and the dynamics acting on these traits during their evolution . Estimated branch lengths for our three species tree were drawn from a whole clade ( 13 species , plus one outgroup ) ultrametric tree generated using RAxML Pthreads 7 . 0 . 0 [36] , based on 18 previously published loci [37] ( Figure S2 ) . Results reported for RAxML ultrametric branch lengths ( Tables S6 and S7 ) are indistinguishable from analyses using the alternative Bayesian tree-building method MrBayes [37]; in particular , median branch length values in the MrBayes data are identical to mean branch length estimates from the RAxML analysis . Variability in estimation of the phylogeny was incorporated in two ways . For our assessment of whether isolation-causing mutations were linearly proportionate to branch lengths , standard deviations for branch lengths on the RAxML tree were obtained from 100 bootstrap replicates , using the topology from the best RAxML partitioned tree ( Text S1 ) . Branch length standard deviation estimates were used to evaluate the effect of substantial estimation error on our inferences ( Table S6 and Text S2 ) . For our comparison of phylogenetic models of incompatibility accumulation , we estimated branch lengths using trees drawn from the posterior distribution of our MrBayes analysis [37] . This posterior was represented by sampling every 100 generations from a Markov chain running for 10 , 000 , 000 generations , discarding the first 25% of trees as burn-in . Since the mathematical description of incompatibility accumulation assumes substitutions accumulate at a constant rate between different branches , we used a penalized-likelihood method , as implemented in R/ape , to enforce a molecular clock on the branch lengths drawn from the posterior . For each fertility measure ( SSS or PF ) within each QTL pairing , we ran a nested ANOVA with genotype ( 4 or 5 levels , depending upon whether the ILPH genotype could be made—Text S1 ) , and maternal parent nested within genotype . In every case we detected a significant effect of genotype ( Results , Table S2 ) ; in no case did we detect a significant effect of maternal parent ( Table S2 ) . We used least-squares means ( LSMeans ) contrasts ( Tukey HSD tests of all pairwise contrasts ) to assess the fertility of ILPH and ILHP genotypes relative to fertility of the homozygous IL parents ( ILPP , ILHH ) and the recurrent SL parent . For completeness , we assessed patterns of fertility for both pollen and seed fertility phenotypes , regardless of whether the original QTL was identified for PF or SSS; only results for cases where we have an expectation of potential homology are reported in the main text . Because hybrid sterility generally acts partially or fully recessively [27] , a significant increase in fertility in ILHP and/or ILPH genotypes , in comparison to one or both parental ILs , is consistent with rescue/complementation of the sterility phenotype , and therefore the inference that underlying loci are not homologous . Bootstrap analyses to compare early versus late effect sizes , and binomial resampling to evaluate the pattern of accumulation of mutations over time , were performed in R ( R Development Core 2009 ) using scripts as described in [64] ( page 385 and 365 , respectively ) . Analyses of phylogenetically explicit models of incompatibility accumulation were performed using custom Python scripts as described in [19] . Prior simulations suggest there is low power to distinguish alternative non-linear models in datasets with few ( <20 ) isolation QTL [19]; these comparisons are particularly prone to Type 2 error ( false negatives , or incorrect acceptance of the simpler model ) . Simulations parameterized with data from this study similarly suggest that our comparisons have a higher propensity of returning false negatives when comparing simpler to more complex models ( Results ) ; nonetheless , these simulations also suggest greatest support for non-linear models of sterility accumulation . Therefore , although we have relatively few loci to fit such models here , our inference that sterility data support more complex ( non-linear ) models is robust .
The evolution of reproductive barriers between species , like inviability and sterility in hybrids , continues to fascinate and puzzle evolutionary biologists . However , very few studies have successfully identified the genes responsible for these barriers , or when the underlying mutations appeared during species' evolutionary history of divergence . Differentiating whether specific isolation-causing mutations evolved early versus late in the divergence history of lineages can reveal important insights into the mechanisms of speciation—how new species are formed . Here we infer the evolutionary timing of these loci using data on the chromosomal location of genes that cause reduced hybrid pollen and seed fertility among three species in the wild tomato group , and information on their evolutionary relationships . With genetic crosses that combine these sterility loci from different lineages , we evaluate whether sterility effects are due to the same mutational change ( s ) —earlier in the history of evolutionary divergence among these species—or to independent mutational changes—later in their evolutionary divergence . We show that most sterility loci separating species are unique to a single species pair , and most isolation-causing mutations arose on recent evolutionary branches . Our data are consistent with mathematical models that predict that these loci should ‘snowball’ between species as they diverge .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biotechnology", "plant", "genomes", "quantitative", "traits", "genetic", "complementation", "genome", "analysis", "speciation", "trait", "locus", "analysis", "plant", "genomics", "genetic", "interactions", "genomics", "plant", "genetics", "evolutionary", "theory", "evolutionary", "genetics", "macroevolution", "phenotypes", "heredity", "gene", "identification", "and", "analysis", "genetics", "biology", "and", "life", "sciences", "computational", "biology", "evolutionary", "biology", "plant", "biotechnology", "evolutionary", "processes" ]
2014
Interspecific Tests of Allelism Reveal the Evolutionary Timing and Pattern of Accumulation of Reproductive Isolation Mutations
Cell-to-cell communication in bacteria is a process known as quorum sensing that relies on the production , detection , and response to the extracellular accumulation of signaling molecules called autoinducers . Often , bacteria use multiple autoinducers to obtain information about the vicinal cell density . However , how cells integrate and interpret the information contained within multiple autoinducers remains a mystery . Using single-cell fluorescence microscopy , we quantified the signaling responses to and analyzed the integration of multiple autoinducers by the model quorum-sensing bacterium Vibrio harveyi . Our results revealed that signals from two distinct autoinducers , AI-1 and AI-2 , are combined strictly additively in a shared phosphorelay pathway , with each autoinducer contributing nearly equally to the total response . We found a coherent response across the population with little cell-to-cell variation , indicating that the entire population of cells can reliably distinguish several distinct conditions of external autoinducer concentration . We speculate that the use of multiple autoinducers allows a growing population of cells to synchronize gene expression during a series of distinct developmental stages . In a process called quorum sensing , bacteria communicate with one another using extracellular signaling molecules called autoinducers . Quorum sensing allows groups of bacteria to track their cell numbers , synchronize gene expression on a population-wide scale , and thereby carry out collective activities . In quorum sensing , bacteria produce , release , and detect autoinducers that accumulate in a cell-density–dependent manner , and , thus , autoinducer concentration serves as a proxy for cell number . Quorum-sensing systems are widespread in the bacterial world , existing in both Gram-negative and Gram-positive bacteria , and quorum sensing is used to control such diverse functions as bioluminescence , virulence-factor secretion , biofilm formation , conjugation , and antibiotic production [1–3] . Typically , Gram-negative bacteria use acyl-homoserine lactones and Gram-positive bacteria use peptides as autoinducers . To our knowledge , these two kinds of molecules most often promote intraspecies cell–cell communication , because a particular acyl-homoserine lactone or particular peptide can be detected only by the bacterial species that produces it [2] . In addition , a non–species-specific autoinducer called AI-2 , which is a family of interconverting molecules all derived from the same precursor 4 , 5-dihydroxy 2 , 3-pentanedione , is produced and detected by a large variety of both Gram-negative and Gram-positive bacteria [4 , 5] . Interestingly , many bacterial species use more than a single autoinducer molecule for quorum sensing . For example , Gram-negative bacteria ( e . g . , Rhizobium ) can use multiple homoserine lactones and likewise , Gram-positive bacteria ( e . g . , Bacillus ) can use several peptides for communication [2 , 6] . These bacteria have evolved sophisticated quorum-sensing circuits to detect and integrate the information contained in multiple autoinducers . It remains a mystery how and why bacteria integrate multiple autoinducer signals and what additional information multiple autoinducers reveal about the cells' environment that one autoinducer cannot reveal [7] . Furthermore , while in principle , quorum sensing enables bacteria to act in synchrony , the behavior of the entire population is ultimately dictated by events inside single cells . Recent single-cell studies of gene expression in bacteria have revealed that noise is inevitable even for isogenic cells in essentially homogeneous environments , and that noise can result in heterogeneous phenotypes within a population [8–14] . Likewise , in quorum sensing , noise could make individual cells behave differently from one another even if they receive identical autoinducer inputs . To understand quorum-sensing signal integration and , ultimately , the evolution of cooperative behaviors at the population level , it is imperative to understand how cells behave individually . Specifically , do cells respond in unison or do they maintain population diversity ? Bulk measurements—which focus on the population's response—generally mask the behavior of individual cells and thus lose information about cell-to-cell variation . To fully understand the molecular mechanism underlying quorum sensing as well as the general principles underlying bacterial communication and cooperation , we must study this process at the single-cell level . To begin to explore the above questions , we investigated the network of the model quorum-sensing bacterium Vibrio harveyi , the first bacterium shown to use more than one autoinducer for quorum sensing [15 , 16] . V . harveyi has a particularly ideal system in which to undertake these studies because the components of the quorum-sensing circuit have been defined ( Figure 1A ) and the autoinducers are known and in hand . V . harveyi produces and detects three autoinducers: AI-1 ( 3-hydroxybutanoyl homoserine lactone ) , CAI-1 ( [S]-3-hydroxytridecan-4–1 ) , and AI-2 ( [2S , 4S]-2-methyl-2 , 3 , 3 , 4-tetra hydroxytetrahydrofuran borate ) [6 , 17 , 18] . AI-1 is only produced by V . harveyi , CAI-1 is produced by V . harveyi as well as other Vibrios , and as discussed , AI-2 is produced by many bacterial species . Thus AI-1 , CAI-1 , and AI-2 could provide information about the numbers of V . harveyi , Vibrios , and total bacteria in the vicinity , respectively . The three autoinducers are detected extracellularly by their cognate transmembrane receptors: LuxN , CqsS , and LuxPQ , respectively [19] . Information from the autoinducer-sensing pathways is transduced through shared components LuxU and LuxO [20–22] and five small regulatory RNAs ( sRNAs ) [23 , 24] to the master quorum-sensing regulator LuxR [25] ( Figure 1A ) . LuxR activates and represses genes including those required for bioluminescence , siderophore production , type III secretion , and metalloprotease production [2 , 26–28] . Here we report the quantitative single-cell fluorescence-microscopy studies of V . harveyi quorum sensing , which have allowed us to define the mechanism of quorum-sensing autoinducer signal integration . Our studies revealed highly uniform behavior in individual cells , suggesting that the V . harveyi quorum-sensing circuit is designed to tightly synchronize the population response to autoinducers . This network operates in stark contrast to other regulatory circuits ( e . g . , such as that underpinning sporulation in Bacillus subtilis ) , which appear designed to generate diversity among the members of the population [29–32] . We also discovered that information from the different autoinducers is integrated in a strictly additive way , with an unexpected balance between the signaling strengths of the different autoinducers , allowing the population as a whole to distinguish multiple states of autoinducer concentration . These results have important implications for the developmental cycle of V . harveyi and possibly for other bacteria that use multiple autoinducers . Each autoinducer-detection pathway contributes uniquely to the overall V . harveyi integrated quorum-sensing response . Thus , to understand how cells communicate , understanding the signaling properties of the individual quorum-sensing pathway is imperative . Toward this end , we measured dose responses of individual cells of the LuxN+ mutant responding to AI-1 . LuxN+ mutant cells were grown in series-diluted concentrations of exogenous AI-1 , and the distributions of PQrr4-GFP intensities of individual cells at each AI-1 concentration were obtained ( Figure 2 ) . A gradual increase in the mean PQrr4-GFP intensity distribution occurred with decreasing AI-1 concentration , reflecting increasing kinase activity of LuxN , and , consequently , increasing LuxO-P concentration . While we observed heterogeneity in PQrr4-GFP expression over the population , the distribution of PQrr4-GFP intensities remained single-peaked with moderate variance around the population average at all AI-1 concentrations ( cell-to-cell variation was somewhat smaller after normalizing by mCherry intensity; see Figure S2 ) . This result suggests that all the V . harveyi cells respond identically to AI-1 , which promotes well-coordinated cellular behavior across the population . The shift in the mean PQrr4-GFP intensity between zero and saturating AI-1 is obviously larger than the standard deviation within the population at any AI-1 concentration , suggesting that cell-to-cell variation , or noise , in quorum sensing is low enough to allow the cells to reliably mount distinct responses to low and high AI-1 concentrations . We performed similar individual-cell dose–response experiments on the V . harveyi LuxPQ+ mutant strain to determine the signaling properties of the AI-2 pathway . For comparison , in Figure 3A we show dose–response curves for both the LuxN+ and LuxPQ+ mutant strains to AI-1 and AI-2 , respectively . Means and standard deviations over a population of cells are reported for each strain . Similar to the results shown in Figure 2 , at all autoinducer concentrations the normalized PQrr4-GFP-intensity distributions are single-peaked , with standard deviation over the mean always smaller than 0 . 4 . For each data point , the population sample consists of 100 individual cells , thus the standard error of the mean is one-tenth of the standard deviation of the population . Each dose–response curve can be described by a simple Hill function αAI + βAI/ ( 1 + [AI]/KAI ) with Hill coefficient equal to one . The inhibition constants for AI-1 and AI-2 are KAI-1 = ( 6 . 9 ± 0 . 5 ) nM and KAI-2 = ( 6 . 4 ± 0 . 5 ) nM , respectively . Note that a 1 nM concentration is approximately one molecule of autoinducer in the volume of a single V . harveyi cell , indicating an extremely sensitive response of V . harveyi cells to autoinducers . The LuxN+ strain has approximately 50% higher PQrr4-GFP levels than the LuxPQ+ strain at low autoinducer concentrations where LuxO-P and PQrr4-GFP are maximal . However , the two strains have similar residual levels of PQrr4-GFP , which remain measurable above background at saturating autoinducer concentrations . The above experiments allowed us to determine the signaling response of the LuxN pathway to AI-1 and that of the LuxPQ pathway to AI-2 when each pathway is present alone . We likewise wondered how the cells respond to AI-1 and AI-2 when the two pathways are present together . To examine this , we performed experiments analogous to those above with the V . harveyi LuxN+ LuxPQ+ strain in the presence of combinations of AI-1 and AI-2 . Surprisingly , we found that although the amplitudes of the autoinducer responses are different when the two quorum-sensing pathways are present individually ( Figure 3A ) , the amplitudes of the AI-1 and AI-2 responses are nearly identical when the two pathways are present simultaneously ( Figure 3B ) . In particular , the dose–response curves for AI-1 ( blue ) and AI-2 ( red ) almost overlap , both in the case when one autoinducer is present alone and in the case when a saturating amount of the other autoinducer is also present . Critically , the overlap of these curves depends on the extremely similar amplitudes of the responses as well as the similar inhibition constants for AI-1 and AI-2 as observed in Figure 3A . The very similar amplitudes of the two autoinducer dose–response curves demonstrate that each autoinducer-sensing pathway contributes approximately half of the total response . Figure 3B clearly shows that when both pathways are present ( e . g . , in the LuxN+ LuxPQ+ strain ) , each autoinducer alone is only capable of partial inhibition of PQrr4-GFP expression . When AI-1 and AI-2 concentrations are increased together , with similar concentrations of each autoinducer present , the resulting dose–response curve of PQrr4-GFP expression covers the entire dynamic range ( yellow-green curve ) . The PQrr4-GFP distribution is always single-peaked , and noise in GFP expression is always moderate , with the standard deviation over the mean no more than 40% . Again , we take this to mean that despite the existence of noise in the quorum-sensing pathway , individual cells are able to discriminate several distinct states . For example , the PQrr4-GFP distributions do not substantively overlap for these three cases: when both AI-1 and AI-2 are below 1 nM , when both are around 10 nM , and when both are above 100 nM . Thus , it appears that individual V . harveyi cells can accurately determine the level of external autoinducers . This result suggests that , in principle , V . harveyi cells can not only detect low and high cell-density states with low and high autoinducer concentrations , but also some intermediate cell-density states represented by intermediate autoinducer concentrations . To obtain a more comprehensive view of the autoinducer response of the LuxN+ LuxPQ+ strain , we explored a grid of possible combinations of AI-1 and AI-2 concentrations . In this way , the complete dose–response surface was obtained ( Figure 3C ) . This surface , displaying average PQrr4-GFP production , is almost mirror-symmetric with respect to the equal AI-1 and AI-2 diagonal; i . e . , the PQrr4-GFP expression is almost invariant with respect to exchange of AI-1 and AI-2 concentrations . Notably , there are at least three distinct states of the output PQrr4-GFP level: high ( both AI-1 and AI-2 concentrations are low , indicated by the red area in Figure 3C ) , intermediate ( one autoinducer concentration is low and the other is high , indicated by the two green areas ) , and low ( both AI-1 and AI-2 concentrations are high , indicated by the blue area ) . This surface confirms that more than two quorum-sensing states can be deciphered by the cells . However , interestingly , under these conditions , high AI-1/low AI-2 is apparently not distinguished from low AI-1/high AI-2 ( see Discussion ) . For a signal-integration circuit such as the quorum-sensing circuit in V . harveyi that involves multistep , bidirectional , biochemical reactions , one might expect the two signals to be integrated in a complicated nonlinear manner . Surprisingly , however , we found quite the opposite . That is , AI-1 and AI-2 signal integration is simply additive . The dose–response surface of the LuxN+ LuxPQ+ strain can be accurately described by the additive function where the γ's and K's are fitting parameters . The inhibition constants have the same values as in the individual pathways: KAI-1 = 6 . 9 nM and KAI-2 = 6 . 4 nM ( Figure 3A and 3B ) . As shown in Figure 3D , the average PQrr4-GFP expression values obtained from Equation 1 agree with the measured values over the entire dose–response surface . The two noncooperative Hill functions correspond to the individual responses of the LuxN and the LuxPQ pathways , respectively . Therefore , we conclude that LuxN and LuxPQ make independent , additive contributions to GFP levels presumably via additive contributions to LuxO-P . Although the two autoinducer signals are combined additively with approximately equal weights in their input to the circuit , we find that the two pathways contribute differently to the noise in PQrr4-GFP expression . As shown in Figure 4A , the LuxPQ+ strain ( with no LuxN receptor ) has significantly larger relative noise , i . e . , larger cell-to-cell variation , than does the LuxN+ strain ( with no LuxPQ receptor ) for the same mean PQrr4-GFP level . Apparently , signaling through the LuxPQ receptor introduces more noise to the circuit than does signaling through the LuxN receptor . This difference is confirmed by the distinct noise levels observed for the LuxN+ LuxPQ+ strain treated with either saturating AI-1 or saturating AI-2 ( Figure 4B ) . In the LuxN+ LuxPQ+ strain , the mean PQrr4-GFP levels are nearly identical under these two conditions , but the relative noise is almost a factor of two larger when only LuxPQ contributes kinase activity ( AI-1 saturating ) than when only LuxN contributes kinase activity ( AI-2 saturating ) . Indeed , as shown in Figure 4B , noise in the LuxN+ LuxPQ+ strain is at its absolute maximum when only LuxPQ contributes kinase activity . Our observation that the LuxN and LuxPQ pathways contribute independently and additively to PQrr4-GFP expression implies that the kinase activities of LuxN and LuxPQ must be regulated by the autoinducers . We draw this conclusion from the following simple model for the signaling pathway leading to PQrr4-GFP expression: We assume that LuxN and LuxPQ are the dominant kinases and phosphatases for LuxU , that phosphotransfer between LuxU and LuxO is reversible , and that PQrr4-GFP expression is a linear function of LuxO-P concentration [O-P] . The final assumption follows from the observed additivity of PQrr4-GFP expression with respect to AI-1 and AI-2 , which is difficult to understand unless [O-P] is in the linear regime of the qrr4 promoter driving gfp , i . e . , the maximal [O-P] is far below the level required to half saturate the promoter activity . The kinetic equations describing this model are where [U-P] is the LuxU-P concentration , and KN , KPQ , PN , and PPQ are the total cellular kinase and phosphatase activities of LuxN and LuxPQ , respectively . At steady state , the time derivatives in Equation 2 can be set to zero , yielding where [O]tot is the total concentration of LuxO . To explain the observed broad range of additivity of PQrr4-GFP expression with respect to the autoinducers , Equation 3 must be separable into two terms , one of which depends only on AI-1 and the other only on AI-2 . This is possible if the autoinducers regulate the receptor kinase activities KN and KPQ , but not if the autoinducers regulate only the receptor phosphatase activities PN and PPQ , since the latter appear only in the denominator of Equation 3 . Indeed , for additivity to be achieved , the denominator of Equation 3 must be approximately constant , which implies one of two scenarios: ( 1 ) only the kinase activities of LuxN and LuxPQ are regulated by autoinducers while phosphatase activities are not , and the kinase and phosphatase activities satisfy KN + KPQ << k−/k+ · ( PN + PPQ ) , implying that LuxO-P levels are far from saturation , i . e . , [O‐P] << [O]tot; and ( 2 ) the kinase and phosphatase activities are both regulated , but their sum is independent of autoinducer concentration such that KN + KPQ + k−/k+ · ( PN + PPQ ) remains constant . Unlike the first scenario , the second scenario requires fine-tuning of reaction rates and therefore seems less likely . While the signaling pathways leading to LuxO-P are likely to include some processes not considered in our simple model ( e . g . , intrinsic dephosphorylation of LuxU-P and LuxO-P ) , our qualitative conclusions—in particular that the kinase activities of LuxN and LuxPQ must be autoinducer regulated—are robust to such quantitative corrections . Since the amplitudes of the responses to AI-1 and AI-2 are almost identical in the LuxN+ LuxPQ+ strain ( Figure 3B ) , the maximum total kinase activities of the two receptors LuxN and LuxPQ must be nearly the same ( i . e . , KN KPQ ) . However , for the strains expressing only a single receptor type , the peak PQrr4-GFP expression is 50% higher for the LuxN+ than for the LuxPQ+ strain ( Figure 3A ) . This apparent discrepancy can be readily accounted for if the total phosphatase activity of LuxPQ is higher than that of LuxN , i . e . , PPQ > PN ( including possible differences in receptor concentration ) . Living cells monitor their environment using a variety of signal-transduction systems , ranging from simple two-component systems in prokaryotes to highly complex signal-transduction networks in mammalian cells . Since environmental cues are always numerous , the ability to integrate multiple signals is indispensable if cells are to behave appropriately . However , the mechanisms and logic by which cells integrate environmental signals remain , by and large , poorly understood . Here we have quantitatively analyzed the integration of multiple autoinducer signals by the model quorum-sensing bacterium V . harveyi using single-cell fluorescence microscopy . Our studies reveal a unified response across the population , with moderate cell-to-cell variation . We find that signals from two distinct autoinducers , AI-1 and AI-2 , are combined strictly additively in a single phosphorelay pathway , with each autoinducer contributing nearly equally to the total response . Moreover , the cell-to-cell variation in response is small enough that the entire population of cells can reliably distinguish at least three distinct conditions of external autoinducer concentration . We used GFP under the control of the chromosomal sRNA Qrr4 promoter as a reporter of the activity of the quorum-sensing signaling pathway ( Figure 1 ) . In all our strains , the GFP distribution was always single-peaked at all autoinducer concentrations , with cell-to-cell standard deviation no more than 40% of the mean , suggesting that populations of V . harveyi cells respond coherently to autoinducer signals . By contrast , genes in some other bacterial systems are known to have bimodal ( i . e . , two-peaked ) expression distributions . In many cases , bimodal gene expression is also hysteretic ( i . e . , cells remain for a long time in one state of expression ) , which constitutes a form of cellular “memory . ” For example , bimodal distributions in gene expression enable sporulation and competence in B . subtilis [29–32] , stringent response in mycobacteria [34] , and induction of the lac operon in Escherichia coli [35 , 36] . In all these cases , bimodality and hysteresis are believed to provide advantages to the organism by enabling phenotypic diversity within isogenic populations . In general , hysteresis in gene expression requires some form of positive feedback . The lack of bimodality in our engineered strains of V . harveyi is expected since there is no positive-feedback loop in the circuit controlling Qrr sRNA expression in these cells . Since our engineered strains lack both the downstream transcription factor LuxR and the autoinducer synthases , there exists the possibility that the sRNAs or LuxR could feed back positively to the synthases and produce a bistable circuit in wild-type cells . In quorum sensing , bistability has only been reported for a rewired LuxIR circuit in V . fischeri [37] . In this case , the positive feedback and the resulting bistability and hysteresis occur at the population level and divide the entire population into two separate subpopulations , each with a unique phenotype . Our consistent observation of a narrowly peaked distribution of quorum-sensing responses strongly suggests that V . harveyi cells respond in unison to the presence of autoinducer signals . For quorum-sensing cells , in contrast to bacteria undergoing competence , sporulation , or the stringent response , operating as a coherent population appears to be more important than maintaining phenotypic diversity . An outstanding question is why V . harveyi and related species use multiple autoinducer signals , but funnel all the information into a single pathway . We can envision two main possibilities ( potentially in combination ) : The multiple autoinducers could reveal information about the community composition ( e . g . , which species are present and in what abundance ) , or the multiple autoinducers could reveal information about the development stage of the community ( e . g . , the growth stage of a biofilm ) . In support of the first possibility , the three autoinducers used by V . harveyi have distinct ranges of species specificity: intraspecies for AI-1 , within Vibrios for CAI-1 , and across many species for AI-2 [7] . Thus , different combinations of the three autoinducers could indicate different compositions of a bacterial community . In our experimental conditions , however , we found that cells could not distinguish between high AI-1/low AI-2 and high AI-2/low AI-1 ( Figure 3B and 3C ) . This result argues for the second possibility , namely that different combinations of autoinducers represent different stages of community development . For example , if a growing V . harveyi community typically accumulates AI-2 before AI-1 , then the signaling contour in Figure 3C would always be traversed along the right edge , and cells could reliably interpret an intermediate signaling strength as a condition of high AI-2/low AI-1 , since the opposite condition of high AI-1/low AI-2 would rarely , if ever , be encountered . In much of eukaryotic development ( e . g . , embryogenesis ) , the rate of development is fixed and driven by a clock [38] , obviating the need for a signal representing the stage of development . However , without the support of a surrounding organism , the rate of development of a bacterial community depends on unpredictable environmental conditions , such as nutrient availability , and therefore some means of determining the stage of development is required so that cells in the community can behave appropriately . Recent models of biofilm growth suggest that communities may be mixed at early stages , but that at later stages competition for nutrients by overgrowth of neighboring cells can result in large domains of cells descended from a single progenitor , and therefore composed of a single species [39] . If so , generic signals such as AI-2 may be most informative at early stages of biofilm growth , while species-specific signals such as AI-1 may be reserved for later stages . We are currently exploring the order of accumulation of the V . harveyi autoinducers AI-1 , CAI-1 , and AI-2 to test whether different autoinducer combinations could signal different stages of community development . Given that the autoinducer signals are combined in one pathway in V . harveyi , why should the signals be combined additively , as we observe for AI-1 and AI-2 ? Simple alternatives would be for saturating autoinducer levels to be combined in “logic gates , ” such as AND , in which both autoinducer signals would be required for a full response , or OR , in which either signal would be sufficient for a full response . However , these logic gates have only two possible output states: on or off . In contrast , the addition of the two autoinducer signals allows for more than two output states of the signaling pathway , and therefore potentially allows for more than two expression states of quorum-sensing regulated genes . Indeed , we discovered three distinct levels of signaling strength , represented by the heights of the plateaus in Figure 3C . Moreover , the standard deviation of PQrr4-GFP expression across the population of cells was sufficiently small ( Figure 4B ) so that the entire population can apparently distinguish the three distinct plateau heights . This means that , in principle , every cell in the population can distinguish three external autoinducer conditions: both autoinducers low , both autoinducers high , and a third condition in which one autoinducer is high and the other is low . The reliability with which cells can distinguish among these three conditions is increased by the equal spacing of the plateau heights as shown in Figure 3C . Given a uniformly distributed input of autoinducer concentration and the observed level of noise ( i . e . , cell-to-cell variation in PQrr4-GFP expression ) , a significantly unequal spacing of the plateau heights would lead to overlapping distributions of PQrr4-GFP expression for the two more closely spaced plateaus . The implication is that noise might then cause some cells to misinterpret external conditions and regulate quorum-sensing genes inappropriately . The need for all cells to reliably distinguish among multiple autoinducer conditions may therefore explain not only the additivity of the quorum-sensing pathway , but also why the contributions of the AI-1 sensor LuxN and the AI-2 sensor LuxPQ to the total kinase activity are so nearly equal—equal kinase activities mean equally spaced plateau heights , which in turn mean that individual cells are less likely to confuse one autoinducer condition with another . The existence of multiple quorum-sensing output states potentially underpins diverse patterns of quorum-sensing regulated gene expression . For example , in previous studies , the quorum-sensing circuit of V . harveyi was found to act as an autoinducer “coincidence detector” ( i . e . , requiring both AI-1 and AI-2 ) for full induction of bioluminescence [19 , 40] . Thus , in the present context , the three distinguishable levels of signaling output ( indicated by Qrr4 promoter activity ) appear to be collapsed by downstream signal-processing events to two levels of bioluminescence . More generally , the target genes of quorum sensing could be tuned to different signaling output levels so that only particular classes of genes are switched ON/OFF at early , middle , or late stages of community development . Alternatively , some genes could have graded expression between these different developmental stages . The requirement for multiple distinct output states might also explain our observation of a graded , rather than switch-like , response of the Qrr4 promoter . Specifically , our dose–response data are well described by a noncooperative , n = 1 Hill function response to both autoinducers . Cooperativity would have resulted in an n > 1 Hill function and therefore a more switch-like response of PQrr4-GFP to autoinducers . During the signaling process , cooperativity could in principle have arisen from the binding of autoinducers to receptors , transfer of phosphate among the protein components in the phosphorelay , and/or binding of phosphorylated LuxO to DNA . Our results suggest that in fact all of these steps are noncooperative , despite the fact that the receptors are likely dimers [22] and that LuxO may function as a tetramer or octamer [Tu KC , unpublished data] . Indeed , a graded noncooperative response of Qrr expression to autoinducers is essential for the existence of multiple , distinguishable quorum-sensing states , as a switch-like response of the Qrr expression would have allowed for only two states . Based on a simple kinetic model for signaling ( Equation 2 ) , we have argued that the kinase activities of LuxN and LuxPQ are regulated by autoinducers , whereas for most two-component receptors , it is still an open question whether the kinase or phosphatase or both activities are regulated by input stimuli . Previously , LuxN receptors have been successfully modeled as switching between two states: the ON ( kinase dominant ) and OFF ( phosphatase dominant ) states [41 , 42] . Each receptor has intrinsic kinase and phosphatase rates depending only on the state in which the receptor exists . Extending this model to LuxPQ , the total cellular kinase activities KN and KPQ consist of a major contribution from those receptors in the ON state with little or no contribution from those in the OFF state . From the constraints set by additivity , we conclude that the phosphatase activities PN and PPQ are unregulated ( i . e . , receptors have the same phosphatase rates in both the ON and OFF states ) . Note that autoinducer concentrations only affect the thermal balance between ON and OFF states , and therefore the kinase and phosphatase activities are regulated only via the biasing of receptors between states ( of course , the total kinase and phosphatase activities also depend on receptor concentrations ) . The low levels of PQrr4-GFP expression with saturating AI-1 in the LuxN+ strain , saturating AI-2 in the LuxPQ+ strain , and saturating AI-1 plus AI-2 in the LuxN+ LuxPQ+ strain indicate that kinase rates in the OFF states are much smaller than those in the ON states for both LuxN and LuxPQ . By decreasing the fraction of receptors in the ON state , autoinducers reduce the total kinase activity of the quorum-sensing receptors in V . harveyi . ( See Text S1 for more details . ) Regulation of the kinase activities of LuxN and LuxPQ appears to be necessary to achieve three equally spaced levels of LuxO-P ( Equation 3 ) . The requirement for kinase regulation in V . harveyi quorum sensing therefore appears to stem from the need to combine multiple input signals into more than two distinguishable output levels of LuxO-P . One prediction from this analysis is that the sensor CqsS , which was not present in our strains , is likely to also have its kinase activity regulated by its autoinducer CAI-1 . Moreover , CqsS is likely to contribute additively to total kinase activity and with a strength comparable to that of LuxN and LuxPQ , resulting in four maximally distinguishable levels of kinase activity and therefore four distinguishable autoinducer conditions . The similarity of the responses to AI-1 and AI-2 is striking , not only in the amplitudes but also in the inhibition constants . We speculate that V . harveyi usually encounters similar amounts of AI-1 and AI-2 , and the responses of receptors have been optimized to match the natural dynamic range of autoinducer concentrations . It has been demonstrated that single mutations in the receptors LuxN and LuxPQ can result in dramatic changes in their inhibition constants [22 , 42] , so the similar values for AI-1 and AI-2 may represent an evolved optimum . We also quantified the noise in PQrr4-GFP expression in our three reporter strains . Noise is an inherent feature of signal transduction and gene expression both in prokaryotes and eukaryotes . Due to the low copy number of cellular components and the stochastic nature of biochemical reactions , fluctuations are inevitable . Large fluctuations might be deleterious for processes requiring precise control but beneficial for those providing phenotypic diversity . In quorum sensing , bacterial cells detect population cell density to coordinate their behavior on a community-wide scale . Low noise in quorum-sensing signal transduction might therefore benefit the population of cells by allowing all cells to behave correctly and in unison at each stage of community development . Indeed , we observed low noise in PQrr4-GFP expression in all our strains . At all autoinducer concentrations the standard deviation over the mean was less than or close to 0 . 4 ( Figure 4 ) . In other systems , the dominant source of cell-to-cell variation in gene expression has been attributed to extrinsic noise , e . g . , differences among cells in concentrations of general purpose cellular components such as RNA polymerases and ribosomes [8] . In the quorum-sensing circuit we have studied , the noise we observed is also likely due to extrinsic factors rather than to biochemical noise in phosphotransfer or transcription and translation of PQrr4-GFP . The most likely source of the noise we observed is fluctuations in concentrations of the pathway components , such as the receptors LuxN and LuxPQ and the response regulator LuxO . The noisier response in LuxPQ pathway is very likely caused by variations in the copy number of the LuxPQ receptors , which suggests that there could be some additional regulation of receptor expression in the quorum-sensing circuit . All V . harveyi strains used in this study were derived from the wild-type strain BB120 [43] and grown aerobically at 30 °C in Autoinducer Bioassay ( AB ) broth . E . coli S17–1λpir was used for general DNA manipulation and grown with aeration at 37 °C in LB ( Luria-Bertani ) broth . The relevant strains and plasmids are listed in Table S1 . DNA manipulation was performed using standard procedures [44] . Phusion DNA polymerase was used for PCR reactions . dNTPs , restriction enzymes , and T4 DNA ligase were obtained from New England Biolabs . DNA purification kits were provided by Qiagen . E . coli was transformed by electroporation using a Bio-Rad Micro Pulser . Plasmids were introduced into V . harveyi by conjugation [15] and exconjugants were selected using the antibiotic resistances carried on the plasmids together with polymyxin B . A cat-resistance cassette from pKD3 [45] was cloned into vector pCMW1 [7] downstream of gfp at the BamH1 site , making pTL3 . The GFP-Cmr fragment from this construct was subsequently amplified by PCR and recombined using the λ red technique [45] into a cosmid to replace the wild-type qrr4 gene , producing pTL20 . Lastly , PQrr4-GFP-Cmr was introduced onto the chromosome to replace qrr4 by allelic recombination . Ptac-mCherry was amplified from the vector pEVS143-mCherry containing an IPTG inducible mCherry gene and cloned into pKD13 [45] at the NheI site , resulting in pTL82 . The cosmid , pTL83 , was constructed using the λ red technique by recombining the Ptac-mCherry-Kanr fragment into the intergenic region downstream of the entire lux operon . Final insertion of Ptac-mCherry-Kanr onto the V . harveyi chromosome was accomplished by allelic recombination . To construct the various V . harveyi sensor mutants , pKM780 carrying ΔluxS::Cmr , pJMH291 carrying ΔluxN::Cmr , pDLS100 carrying ΔluxPQ::Cmr , pJMH244 carrying ΔcqsS::Cmr , and pKM705 carrying ΔluxR::Kanr were used to sequentially delete the corresponding wild-type genes by allelic recombination . Following each gene deletion , the plasmid pTL18 containing an IPTG-inducible FLP recombinase , derived from pEVS143 and pCP20 [45] , was introduced into the V . harveyi strain to eliminate the antibiotic resistance marker on the chromosome . For dose–response experiments , V . harveyi strains LuxN+ ( TL87 ) , LuxPQ+ ( TL88 ) , and LuxN+ LuxPQ+ ( TL89 ) were grown in AB medium for 8∼12 h . Growth was monitored by measuring optical density at 600 nm . Cultures were diluted to OD600 = 10−6 ∼ 10−7 , and exogenous autoinducers were added at the specified concentrations . Following growth to steady state ( 13∼14 h; OD600 = 0 . 005 ∼ 0 . 05 ) , cells were concentrated by centrifugation and maintained on ice until measurements were made . One μl of cell culture was spread on a glass slide and covered with a 1% AB agarose pad as well as a coverslip . Phase-contrast and fluorescent images were taken at room temperature using a Nikon TE-2000U inverted microscope . Custom Basic code was written to control the microscope . Images were acquired using a 100× oil objective and a cooled CCD camera ( −65 °C , Andor iXon ) . Segmentation of individual cells was performed on phase-contrast images . Background and cellular auto-fluorescence values were subtracted from the green and red channels , respectively . Total fluorescence intensity of each cell was obtained by summing all pixels and fractions of pixels in the segmented cell region . Normalized GFP values for each cell were calculated by normalizing total green to total red fluorescence intensity .
Although bacteria are unicellular , the individual cells communicate with each other via small diffusible molecules . This communication process , known as quorum sensing , allows groups of bacteria to track the density of the population they are in , synchronize gene expression across the population , and thereby carry out collective activities similar to those of cells in multi-cellular organisms . Many bacterial species use multiple signaling molecules , but it remains a mystery why multiple signals are required and how the information encoded in them is integrated by bacteria . To explore these questions , we studied a model quorum-sensing bacterium Vibrio harveyi . Using single-cell fluorescence microscopy , we quantified quorum-sensing responses and analyzed the mechanism of integration of multiple signals . Surprisingly , we found that information from two distinct signals is combined strictly additively , with precisely equal weight from each signal . Our results revealed a coherent response across the population with little cell-to-cell variation , allowing the entire population of bacterial cells to reliably distinguish multiple environmental states . We argue that multiple signals and multiple response states could be used to distinguish distinct stages in the development of a bacterial community .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biophysics", "microbiology" ]
2009
Quantifying the Integration of Quorum-Sensing Signals with Single-Cell Resolution
In eukaryotes , GTP-bound ARF GTPases promote intracellular membrane traffic by mediating the recruitment of coat proteins , which in turn sort cargo proteins into the forming membrane vesicles . Mammals employ several classes of ARF GTPases which are activated by different ARF guanine-nucleotide exchange factors ( ARF-GEFs ) . In contrast , flowering plants only encode evolutionarily conserved ARF1 GTPases ( class I ) but not the other classes II and III known from mammals , as suggested by phylogenetic analysis of ARF family members across the five major clades of eukaryotes . Instead , flowering plants express plant-specific putative ARF GTPases such as ARFA and ARFB , in addition to evolutionarily conserved ARF-LIKE ( ARL ) proteins . Here we show that all eight ARF-GEFs of Arabidopsis interact with the same ARF1 GTPase , whereas only a subset of post-Golgi ARF-GEFs also interacts with ARFA , as assayed by immunoprecipitation . Both ARF1 and ARFA were detected at the Golgi stacks and the trans-Golgi network ( TGN ) by both live-imaging with the confocal microscope and nano-gold labeling followed by EM analysis . ARFB representing another plant-specific putative ARF GTPase was detected at both the plasma membrane and the TGN . The activation-impaired form ( T31N ) of ARF1 , but neither ARFA nor ARFB , interfered with development , although ARFA-T31N interfered , like ARF1-T31N , with the GDP-GTP exchange . Mutant plants lacking both ARFA and ARFB transcripts were viable , suggesting that ARF1 is sufficient for all essential trafficking pathways under laboratory conditions . Detailed imaging of molecular markers revealed that ARF1 mediated all known trafficking pathways whereas ARFA was not essential to any major pathway . In contrast , the hydrolysis-impaired form ( Q71L ) of both ARF1 and ARFA , but not ARFB , had deleterious effects on development and various trafficking pathways . However , the deleterious effects of ARFA-Q71L were abolished by ARFA-T31N inhibiting cognate ARF-GEFs , both in cis ( ARFA-T31N , Q71L ) and in trans ( ARFA-T31N + ARFA-Q71L ) , suggesting indirect effects of ARFA-Q71L on ARF1-mediated trafficking . The deleterious effects of ARFA-Q71L were also suppressed by strong over-expression of ARF1 , which was consistent with a subset of BIG1-4 ARF-GEFs interacting with both ARF1 and ARFA . Indeed , the SEC7 domain of BIG5 activated both ARF1 and ARFA whereas the SEC7 domain of BIG3 only activated ARF1 . Furthermore , ARFA-T31N impaired root growth if ARF1-specific BIG3 was knocked out and only ARF1- and ARFA-activating BIG4 was functional . Activated ARF1 recruits different coat proteins to different endomembrane compartments , depending on its activation by different ARF-GEFs . Unlike ARF GTPases , ARF-GEFs not only localize at distinct compartments but also regulate specific trafficking pathways , suggesting that ARF-GEFs might play specific roles in traffic regulation beyond the activation of ARF1 by GDP-GTP exchange . ARF GTPases and their guanine-nucleotide exchange factors ( ARF-GEFs ) play essential roles in the formation of membrane vesicles that transport cargo proteins from donor to acceptor compartments within the endomembrane system . Sometimes called molecular switches , ARF proteins cycle between an inactive GDP-bound form and an active GTP-bound form [1 , 2] . In mammals , ARF GTPases are grouped in three classes . Class-I ARFs ( Arf1-3 ) are activated by large ARF-GEF GBF1 and required for the recruitment of COPI coat protein complex to the Golgi stack , resulting in the formation of COPI-coated vesicles for retrograde traffic from the Golgi stack to the endoplasmic reticulum ( ER; [3] ) . However , GBF1 can also activate the class-II GTPase Arf5 [4] . Mammalian BIG1 and BIG2 appear to activate Arf1 and Arf3 at the trans-Golgi network ( TGN ) , recruiting adaptor protein complex AP-1 for the formation of clathrin-coated vesicles in TGN-plasma membrane secretory traffic [3] . Thus , class-I ARFs mainly regulate secretory traffic . Although class-I and class-II ARFs act interchangeably at the Golgi stack , Arf3 seems to play a specific role there [5] . In addition to the large ARF-GEFs , there are small ARF-GEFs such as cytohesin or ARNO , which activate Arf1 as well as the endocytosis-related GTPase Arf6 , the only member of class III . However , Arf6 is also activated by a medium-sized Arf6-specific ARF-GEF named EFA6 [3 , 4] . Besides ARFs , there are ARF-like ( Arl ) or Arf-related ( Arfrp1 ) proteins , which perform diverse biological functions including formation of tubulin heterodimers [4 , 6] . The situation is less clear in flowering plants . Early bioinformatic surveys of the Arabidopsis genome revealed 19 genes coding for ARF or ARF-LIKE ( ARL ) proteins [7–9] . Notably , class-I ARFs are conserved across the eukaryotes whereas class-II and class-III ARFs appear absent from plants . On the other hand , there are at least two additional seemingly plant-specific putative ARF classes named A and B , however their biological roles are unknown . Another peculiarity of plants is the absence of small and medium-sized ARF-GEFs , which play essential roles in ARF activation in non-plant eukaryotes [3 , 10] . Instead , the conserved group of large ARF-GEFs has increased to three GBF1-like proteins ( GN , GNL1 and GNL2 ) and 5 BIG1-like proteins ( BIG1 to BIG5 ) in Arabidopsis [1 , 2] ) . Arabidopsis ARF-GEFs localize at distinct compartments and regulate specific trafficking pathways . GN mediates polar recycling of the auxin-efflux carrier PIN1 from endosomes to the basal plasma membrane , resulting in polar auxin transport [11] . Both GN and GNL1 mediate retrograde traffic of COPI vesicles from the Golgi stack to the ER [12] . GNL2 is a pollen-specific counterpart of GN , which also can substitute for both GN and GNL1 when expressed from the GN promoter [13] . Of the 5 BIGs , BIG1-4 are functionally overlapping ARF-GEFs that mediate the late-secretory pathway from the TGN to the plasma membrane as well as trafficking to the vacuole and to the cell division plane [14] . BIG5 ( also known as MIN7 and BEN1 ) is involved in pathogen response and in endosomal trafficking [15–18] . Here we address the problem of specificity in the interaction of ARFs with ARF-GEFs as regards the regulation of distinct trafficking pathways . Our results indicate that all ARF-GEFs of Arabidopsis interact with class-I ARFs and that only class-I ARFs , but not ARFs of the two other classes A and B , are essential for viability . Class-A ARFs are conserved within the plant lineage and appear to be activated by a subset of BIG ARF-GEFs with dual substrate specificity for ARFA and ARF1 but they are not vital . The single class-B ARF might have originated from an ARF1 gene duplication event late in flowering plant evolution , and blocking its activation has no deleterious effect . In conclusion , ARF-GEFs seem to play specific roles in traffic regulation beyond the activation of ARF1 by GDP-GTP exchange . The Arabidopsis genome codes for 19 proteins annotated as ARF or ARF-LIKE ( ARL ) GTPases ( Fig 1A and S1 Table; see also [8 , 9] ) . To define ARFs as opposed to ARLs , we initially identified orthologs across all five major clades of eukaryotes ( Archaeplastida , SAR , Excavata , Amoebozoa , Opisthokonta ) because the counterparts in mammals and yeast have been functionally characterized ( S1A Fig and S2 Table ) . This distinguished class-I ARFs ( 6 ARF1 isoforms ) from 5 ARL classes comprising ARL1 , ARL2 , ARL5 , ARL8 ( 4 isoforms ) , and ARFRP1 ( Figs 1A and S1A and S1 and S2 Tables ) . For example , analysis of ARL2 function in Arabidopsis confirmed a conserved role of this protein in tubulin dimer formation [19] . Two ARLs were originally classified as ARFs: ARL1 was known as ARF3 ( or ARFC1b ) whereas ARL5 was named ARFC1 ( a ) [8] . In contrast , the remaining 5 ARF-related proteins are largely confined to the plant lineage , functionally undefined and were considered candidate ARFs representing 3 different classes: 2 class-A ARFs , 1 class-B ARF , and 2 class-D ARFs ( S1A Fig and S1 and S2 Tables ) . These classes differ in evolutionary age: Unlike class-I ARFs , class-A ARFs are restricted to the green lineage ( Archaeplastida , although not present in Rhodophyceae ) , ranging from algae to flowering plants , but not present in the related eukaryotic clade of SAR , the other subgroup of Diaphoretickes ( S1A Fig and S2 Table ) . Class-B ARFs originated late in dicot flowering plant evolution , being confined to the order of Brassicales which includes Arabidopsis ( S1 Table ) . No ARFB-related sequences were identified in the basal angiosperm Amborella , the basal dicot Aquilegia or the secondarily simplified monocot Spirodela ( S1 Table ) . There was an ARF sequence in the excavate Giardia lamblia ( GL50803_7789 ) that grouped with Arabidopsis ARFB but was more closely related to ARF1 than ARFB ( e-97 and e-78 , respectively; S1A Fig and S2 Table ) . The two closely related class-D ARF proteins appear confined to the Arabidopsis family named Brassicaceae ( S1 and S2 Tables ) , suggesting that ARFD originated only recently . Although we detected an Ectocarpus EsArlX with low sequence identity to both ARF1 and ARFD of Arabidopsis , there was no such ArlX in the other SAR subclades–diatoms , oomycetes and Alveolata ( S1 Fig and S2 Table ) . With ARL1 being the eukaryotically conserved ARL protein most closely related to ARF1 by sequence , ARFs might be expected to be comparably related to ARF1 ( blastP e-values: ARF1s among themselves , -102; the other groups to ARF1: ARFB , -70; ARL1 , -65; ARFA , -63; ARL5 , -55; ARFD , -46; ARL2 , -39 ) . Class-D proteins were excluded from further consideration because of their late origin in flowering plant evolution and their distant relatedness to ARF1 . We thus focused our study on ARFA and ARFB , in addition to ARF1 . The 6 class-I ARFs share at least 97% sequence identity , suggesting redundant functions [20] . They are less divergent than the human class-I ARFs . Two Arabidopsis ARF1 isoforms–ARFA1a and ARFA1d –are identical in sequence . Moreover , the most divergent ARF1 isoform ARFA1b is expressed in haploid pollen and not in somatic tissues [21] . The remaining 4 isoforms of Arabidopsis ARF1s are polymorphic at amino acid residues 6 ( 2G , 2A ) and 179 ( 2S , 1N , 1G ) . Consistently , all ARF1 isoforms were detected by immunostaining with specific antiserum raised against class-I member ARFA1c ( designated ARF1A1c by TAIR; https://www . arabidopsis . org/ ) , which also cross-reacted with ARF1 from maize [22] . ARF1-YFP was localized by live-cell imaging and double labeling with specific markers to the Golgi stacks and trans-Golgi networks ( TGN ) ( Fig 1B–1I; see S1C Fig for quantitative assessment of co-localization ) , which was also confirmed by immunogold labeling and EM localization ( Fig 1Z and 1A1 ) and by immunolocalization of ARF1 with anti-ARF1 antiserum [23] . The two class-A members also share high sequence identity with each other ( 94% ) , suggesting redundancy within this class . ARFA-YFP was localized to the TGN and , less strongly , Golgi stacks by live-cell imaging and by immunogold labeling and EM localization ( Figs 1J–1Q and 1B1 and S1C ) . The single class-B ARF fused to YFP ( ARFB-YFP ) was detected at the plasma membrane and also co-localized with the TGN marker VHA-a1-RFP but not with the Golgi marker wave22-mCherry ( Figs 1R–1Y and S1C; see also an earlier report on plasma-membrane localization of ARFB-YFP transiently expressed in tobacco leaf cells and protoplasts [24] ) . Thus , ARF1 and ARFA overlapped in their detectable subcellular localization at the Golgi stacks and the TGN whereas ARFB appeared to be present at both the plasma membrane and the TGN . Unlike ARLs , true ARFs are activated by ARF-GEFs . We therefore assayed ARF1 , ARFA and ARFB for their ability to interact with the previously characterized Arabidopsis ARF-GEFs ( S1B Fig; [1 , 11–14] ) . To explore the presumed interactions in planta , we performed immunoprecipitation experiments in the presence of the fungal toxin brefeldin A ( BFA ) with YFP-tagged ARFs representing the three classes I , A and B plus YFP-tagged RABG3f GTPase as a control for non-specific interaction , and subjected the immunoprecipitates to mass spectrometry ( S3 Table ) . BFA is known to inhibit the GDP-GTP exchange reaction , freezing the abortive complex of ARF•GDP with BFA-sensitive ARF-GEF on the membrane [25] . Analysis of the data revealed that ARF1 interacted with all ARF-GEFs expressed in seedlings ( BIG1-5 , GN and GNL1 but excluding pollen-specific GNL2 ) whereas ARFA only interacted with BIG5 . ARFB appeared to interact with BIG5 and , less strongly , also with BIG1 and BIG2 . Only background levels of ARF-GEFs were detected in the RABG3f immunoprecipitate which instead contained RAB-GDI and retromer subunit VPS35 isoforms A and B ( S3 Table ) . Thus , the interaction data suggest that conserved ARF1 is likely activated by all ARF-GEFs whereas ARFA and ARFB might be activated by a specific subset of post-Golgi ARF-GEFs . To determine the function of the various ARF classes , we generated transgenic plants overexpressing ARF-T31N-YFP or ARF-Q71L-YFP in an inducible or conditional manner . The T31N mutant ARF GTPases are unable to undergo GDP-GTP exchange . These inactive ARFs will bind tightly to , and thus block , cognate activating ARF-GEFs . Since ARF-GEFs are limiting , overexpression of ARF-T31N will titrate out interacting ARF-GEFs . In contrast , ARF-Q71L is thought to slow down GTP hydrolysis , keeping the ARF GTPase in an active , GTP-bound form . Active ARF GTPases will interact with effector proteins and likely titrate out interacting coat proteins by blocking the uncoating process [26] . Both ARF variants should thus have deleterious , albeit different , effects on membrane trafficking . Using an estradiol ( Est ) -inducible promoter [27] , we analyzed the effects of ARF1 , ARFA or ARFB on seedling root growth and seed germination ( Fig 2A–2P ) . When transferred from -Est to +Est plates the roots of ARF1-T31N-YFP seedlings did not grow anymore whereas root growth of ARFA-T31N-YFP and ARFB-T31N-YFP seedlings was not affected , although the latter two variants were also well expressed ( Fig 2A , 2O–2P ) . The analysis of seed germination resulted in similar effects ( Fig 2B–2N ) . ARF1-T31N-YFP seeds did not germinate on +Est plates whereas germination of ARFA-T31N-YFP and ARFB-T31N-YFP seeds was unaffected ( Fig 2B–2D , compare with 2E , 2F , 2G–2H ) . In conclusion , only ARF1-T31N-YFP overexpression caused clear-cut mutant phenotypes , suggesting that only ARF1 is essential for normal development . Hydrolysis-impaired ARF1-Q71L-YFP has been used to interfere with secretory and vacuolar traffic in plant cells [28–30] . Est-inducible ARFB-Q71L-YFP was well expressed but had no adverse effects on seedling root growth nor on seed germination ( Fig 2A , 2M , 2N , 2O and 2P ) . In contrast , Est>>ARFA-Q71L-YFP seed germination was ( largely ) blocked on estradiol plates , which resembled the situation in Est>>ARF1-T31N-YFP ( Fig 2K and 2L , compare with Fig 2C and 2D ) or when secretion was inhibited as a result of inactivation of early or late secretory ARF-GEFs , respectively [12 , 14] . In addition , root growth of Est>>ARFA-Q71L-YFP transgenic seedlings was blocked upon transfer to estradiol plates ( Fig 2A ) . Thus , ARFA-Q71L-YFP had developmental consequences comparable to ARF1-T31N-YFP and inactivation of ARF-GEFs GNL1 and GN or BIG1-4 . Interestingly , ARF1-Q71L-YFP caused essentially the same developmental defects as did ARF1-T31N-YFP or ARFA-Q71L-YFP ( Fig 2A , 2I and 2J , compare with Fig 2C , 2D , 2K and 2L ) . Since ARFA and ARF1 had strong influence on seedling development , we tested whether expression of inhibitory mutant forms of ARFA and ARF1 variants also affects embryo development . Therefore , we expressed the T31N and Q71L forms with the GAL4>>UAS two-component expression system involving the strong RPS5A ribosomal protein gene promoter [31] . ARF1-T31N-YFP caused early embryo arrest , with cells displaying cytokinesis defects , which indicates an essential role of ARF1-mediated trafficking from fertilization onward ( S2A–S2L Fig ) . In contrast , RPS5A-driven overexpression of ARFA-T31N-YFP had no obvious phenotypic effects in embryogenesis ( S2M–S2O Fig ) . Two-component expression of either ARF1-Q71L-YFP or ARFA-Q71L-YFP interfered with embryogenesis , although with some delay as compared to the early effect of ARF1-T31N-YFP ( S2P–S2U and S2V–S2X Fig , compare with S2G–S2L Fig ) . These data indicate that ARF1 plays a crucial role in embryo development . In contrast , ARFA might not be essential since expression of ARFA-T31N-YFP had no influence on embryo development . To address the lack of deleterious effects in ARFA-T31N and ARFB-T31N , we analyzed knockout or nearly complete knockdown mutants . Single and double knockouts of the two ARFA genes by T-DNA insertion did not cause any major abnormality ( S2Y and S2Z Fig ) . No such knockout was available for the single ARFB gene . Instead , six transgenic lines expressing artificial microRNA ( amiRNA ) directed against ARFB mRNA from the RPS5A promoter were generated ( RPS5A::amiR ( ARFB ) ) and all those lines showed a strong reduction of ARFB transcript level whereas ARFA mRNA was not affected ( S2B1 Fig ) . However , the strong reduction of ARFB function did not result in any morphological abnormality ( S2A1 Fig ) . These observations suggest that both class-A and class-B ARFs have no essential roles . To explore the possibility that ARFA and ARFB might have overlapping functions , we strongly co-expressed ARFA-T31N-YFP and ARFB-T31N-YFP in the same plants , which , however , did not yield any obvious mutant phenotype ( S2C1 Fig ) . The same lack of deleterious phenotypic effect was also observed in mutant plants lacking ARFA transcripts because of genetic double knockout and ARFB transcripts because of expression of artificial microRNA ( RPS5A::amiR ( ARFB ) ) ( S3 Fig ) . In conclusion , only ARF1 appears to be directly required for essential endomembrane traffic in plants whereas abolishing the activity of both ARFA and ARFB had no detectable effect . Since ARFA-T31N had no obvious biological effect we tested whether the T31N mutation behaved as expected by inhibiting cognate ARF-GEF ( s ) that mediate ARFA activation . To this end , we transiently expressed mutant versions–T31N and Q71L –of class-A ARF GTPase in protoplasts and analyzed them for inhibitory effects in a quantitative secretion assay , as had been done for ARF1 [30] . In our secretion assay , ARFA-Q71L inhibited secretory trafficking whereas ARFA-T31N had no inhibitory effect ( Fig 2Q ) . To clarify why ARFA-T31N had no effect in contrast to ARFA-Q71L , we co-expressed rising concentrations of activation-impaired ARFA-T31N together with a constant amount of hydrolysis-impaired ARFA-Q71L . This resulted in concentration-dependent suppression of the inhibitory effect of ARFA-Q71L , with 10-fold excess of ARFA-T31N fully restoring secretion to the control level ( Fig 2R ) . These observations suggest that ARFA-T31N is likely to block the activation of ARFA-Q71L by cognate ARF-GEFs . To substantiate this conclusion , we tested an ARFA-T31N , Q71L double mutant construct in the quantitative secretion assay . This double mutant did not interfere with secretion of amylase ( Fig 2S ) . Moreover , the same double mutant also suppressed the inhibitory effect of ARFA-Q71L in a concentration-dependent manner ( Fig 2S ) . We then analyzed the in-planta effects of Est>>ARFA-T31N , Q71L-YFP double mutant transgene . In contrast to the Est>>ARFA-Q71L-YFP single mutant , the double mutant did not interfere with any developmental processes when induced by estradiol treatment ( S4 Fig ) . Thus , ARFA might act in a non-essential trafficking pathway . Alternatively , ARFA activation might be carried out by ARF-GEFs with dual substrate specificity for ARFA and ARF1 and these overlap functionally with ARF-GEFs that do not activate ARFA but only ARF1 and thus cannot be inhibited by overexpression of ARFA-T31N . This latter idea is supported by the observation that rising concentrations of ARF1 suppressed the inhibitory effect of ARFA-Q71L on secretion in the protoplast assay ( Fig 2R ) . Additional support comes from the analysis of the interaction of ARFs with ARF-GEFs and in-vitro GDP-GTP exchange assays ( see below ) . We analyzed the effects of the activation-impaired forms ARF1-T31N-YFP and ARFA-T31N-YFP in trafficking pathways that require specific ARF-GEFs . Est-induced expression of ARF1-T31N interfered with early secretory traffic . The COPI subunit γCOP remained cytosolic and the Golgi marker N-ST-YFP was relocated to the ER ( Figs 3A–3D and S5A and S5B ) . These defects resembled the outcome of treating ARF-GEF knockout mutant gnl1 with BFA to inactivate the functionally overlapping BFA-sensitive ARF-GEF GNOM in Golgi-ER retrograde trafficking [12] . Blocking of retrograde Golgi-ER traffic results in interference with anterograde secretory traffic . Consistently , plasma membrane-targeted SNARE protein SYP132 was trapped in the ER in ARF1-T31N-expressing lines ( S5C–S5F Fig ) . Similarly , the cytokinesis-specific Qa-SNARE KNOLLE was trapped in the ER , rather than accumulating at the forming cell plate , which resulted in binucleate cells ( S5J–S5M Fig ) . In addition , secretory-mCherry-HDEL , which was held back in the ER lumen , revealed abnormal morphology of the ER , comparable to the appearance of ER in the gnl1 mutant allele ermo1 ( S5R–S5U Fig; [32 , 33] ) . Ultrastructural analysis of cells overexpressing ARF1-T31N confirmed abnormalities of ER organization and disintegration of Golgi stacks , which resembled the ultrastructural phenotype of BFA-treated gnl1 mutant cells ( Fig 4A–4E; [12] ) . In contrast , ARFA-T31N-YFP overexpression had no deleterious effects on ER morphology or ER-Golgi traffic ( Figs 3E–3G , 4H and 4I and S5G–S5I , S5N–S5Q , S5V–S5X ) . ARF1-T31N-YFP also interfered with post-Golgi trafficking . The coat protein clathrin remained in the cytosol rather than associating with the TGN , which is consistent with the requirement of ARF-GEFs BIG1-4 for recruiting the clathrin adaptor-protein complex AP-1 to the TGN ( Fig 3H–3K; [14] ) . Also , secretion of the polysaccharide xyloglucan , which is made in the Golgi stack and delivered to the extracellular space , was impaired , resulting in intracellular accumulation of xyloglucan ( S6A–S6L Fig ) . Moreover , the TGNs were slightly enlarged , and there were additional TGNs ( Fig 4I ) . Endocytosis was also impaired by Est-induced overexpression of ARF1-T31N-YFP . BFA treatment was used to visualize the endocytosed lipophilic dye FM4-64 , which accumulated in BFA compartments in wild-type seedling root cells but not in cells overexpressing ARF1-T31N-YFP ( Fig 3O–3R ) . H4::RFP-PEN1 , another marker for endocytosis , was retained at the plasma membrane in BFA-treated ARF1-T31N-YFP-expressing seedling roots , rather than accumulating in BFA compartments ( S5Y–S5B1 Fig ) . In contrast , expression of ARFA-T31N-YFP had no deleterious effect on post-Golgi secretory or endocytic trafficking ( Figs 3L–3N , 3S–3U and S6S–S6U ) . The role of ARF1 in recycling was analyzed by treating seedlings with estradiol and BFA for 6 h followed by BFA washout for 2 h . In this way , endocytosed trafficking-marker protein first accumulated in the BFA compartments and subsequent washout of BFA would reveal either recycling to the plasma membrane or , if that was interfered with , retention of the marker in the BFA compartment . H4::RFP-PEN1 accumulated in BFA compartments before BFA washout ( Fig 3V–3Y ) . After BFA washout , the marker still labeled endosomes in ARF1-T31N-expressing lines rather than being recycled to the plasma membrane ( Fig 3C1–3F1 ) . A role of ARF1 in vacuolar trafficking was revealed by expression of the AFVY-RFP marker , which accumulates inside the vacuole in wild-type seedling root cells ( Fig 3J1 ) . Expression of ARF1-T31N-YFP blocked trafficking of AFVY-RFP to the vacuole ( Fig 3K1–3M1 ) . In contrast , ARFA-T31N-YFP blocked neither H4::RFP-PEN1 recycling nor vacuolar trafficking ( Fig 3Z–3B1 , 3G1–3I1 and 3N1–3P1 ) . In conclusion , overexpression of ARF1-T31N-YFP interfered with all known trafficking pathways including secretion , endocytosis , recycling or vacuolar traffic . In contrast , ARFA-T31N-YFP did not affect any of those pathways . The hydrolysis-impaired forms ARF1-Q71L-YFP and ARFA-Q71L-YFP both influenced ARF1-dependent trafficking pathways . This was shown by using specific markers , which also revealed different effects between the two Q71L forms and ARF1-T31N-YFP ( Fig 5 , compare with Fig 3 ) . This disparity was further reflected by differences in ultrastructural abnormalities between ARF1-T31N-YFP on one hand and ARF1-Q71L-YFP or ARFA-Q71L-YFP on the other , with the latter resulting in the budding of large vesicles from the Golgi stacks ( Fig 4F , 4G and 4K–4M ) . Coat proteins γCOP and clathrin stayed on the membrane in large aggregates in cells expressing both ARF-Q71L-YFP variants , in contrast to their cytosolic retention in cells expressing ARF1-T31N-YFP ( Fig 5A–5N , compare with Fig 3A–3D and 3H–3K ) . There was no adverse effect on ER morphology , unlike in ARF1-T31N-YFP ( S7A–S7G Fig; compare with S3R–S3U Fig ) . However , the two Q71L ARFs blocked KNOLLE trafficking to the cell division plane ( S7H–S7O Fig ) . Similarly , there was only a slight but noticeable effect on the secretion of SYP132 and xyloglucan ( S7P–S7V , S6M–S6R and S6V–S6X Figs ) . There was no obvious effect on endocytosis of FM4-64 ( Fig 5O–5U ) or Qa-SNARE PEN1 ( S7W–S7C1 Fig ) . An earlier study reported no endocytic uptake of FM4-64 after 3h heat-shock induction of ARF1-QL [20] . The reason for the difference between their results and ours is not clear at present but might be related to different experimental conditions . Recycling of PEN1 to the plasma membrane appeared to be blocked in ARF1-Q71L-YFP and ARFA-Q71L-YFP root cells ( Fig 5V–5B1 ) . In addition , vacuolar trafficking of AFVY-RFP was impaired , resulting in its accumulation in endosomal compartments ( Fig 5C1–5I1 ) . In conclusion , both ARFA-Q71L-YFP and ARF1-Q71L-YFP appeared to interfere with ARF1-dependent trafficking , possibly by depleting necessary effector proteins . Considering the differential effects of ARF1 and ARFA on trafficking pathways , we examined the interaction between the two ARF GTPases and ARF-GEFs by co-immunoprecipitation with protein extracts from seedlings expressing differently tagged ARFs and ARF-GEFs . Co-IPs in both directions yielded comparable results ( Figs 6A–6F and S8A–S8J ) . The interaction between ARF1 and the BFA-sensitive ARF-GEF GNOM was enhanced by BFA treatment of seedling roots ( Figs 6A and 6B and S8B ) . ARF-GEFs GNOM , GNL1 , GN::GNL2 ( GNL2 is normally only expressed in pollen but not in seedlings; [13] ) , BIG3 , BIG4 and BIG5 all co-immunoprecipitated ARF1 ( Figs 6A–6F and S8B–S8J ) . Unlike ARF1 , ARFA was not co-immunoprecipitated with GNOM ( S8E and S8F Fig ) or GNL1 ( S8G Fig ) . Thus , ARF1 interacted with all known ARF-GEFs whereas ARFA did not interact with ARF-GEFs in retrograde Golgi-ER traffic and in GNOM-dependent endosomal recycling to the basal plasma membrane . ARF1-YFP and ARFA-YFP interacted with BIG5 as revealed by co-IP ( Figs 6E and S8D ) . Since the interaction between ARFs and ARF-GEFs takes place on membranes we analyzed the subcellular localization of ARFA in big5 mutant seedlings , which revealed highly cytosolic localization of ARFA-YFP ( Figs 6G–6J and S8K–S8N ) . Furthermore , co-IP also detected weak interaction between BIG4-YFP and ARFA-RFP ( Fig 6F ) . However , no interaction was detected between ARFA-RFP and BIG3-YFP ( S8H Fig ) . Thus , ARFA might be activated by both BIG5 and a subset of the late-secretory ARF-GEFs BIG1-4 . GDP-GTP exchange on ARF proteins is catalyzed by the SEC7 domain of ARF-GEFs [34 , 35] . We have previously shown that GNOM has exchange activity on mammalian ARF1 in vitro in a BFA-sensitive manner [36] . Also , the recombinant SEC7 domain of BIG3 is able to catalyze GDP-GTP exchange of Arabidopsis ARF1 in vitro in a BFA-resistant manner [37 , 38] . However , the same SEC7 domain of BIG3 did not significantly stimulate GDP-GTP exchange of TGN-localized ARFA ( aka ARF8 ) or ARFB ( aka ARF9 ) in vitro [38] . We also tested the in-vitro exchange activity of the recombinant SEC7 domain of TGN-localized BIG5 . BIG5 ( aka MIN7 and BEN1 ) appears to play roles in pathogen response and endocytic trafficking [15–18] . In contrast to BIG3 , BIG5 catalyzed the GDP-GTP exchange on ARFA ( Fig 6K ) . Because BIG5 also interacted with ARF1 in planta , the SEC7 domain of BIG5 appears to have dual ARF substrate specificity . To confirm that the interaction of ARFA with BIG5 reflects a substrate-enzyme relationship , we performed co-immunoprecipitation of BIG5-RFP with ARFA-T31N-YFP and ARFA-Q71L-YFP , respectively , and used co-immunoprecipitation of GNOM with ARF1-T31N-YFP or ARF1-Q71L-YFP as controls . In both cases , the ARF-GEFs only interacted with the activation-impaired T31N form , indicating that the ARFs are used as substrates ( S8I–S8J Fig ) . We then directly tested by in-vitro GDP-GTP exchange assay whether ARFA ( wt ) and the mutant forms ARFA-T31N and ARFA-Q71L are substrates of BIG5 . We also used ARF1 ( wt ) and ARF1-T31N as controls . The SEC7 domain of BIG5 catalyzed GDP-GTP exchange on ARF1 ( wt ) , ARFA ( wt ) and ARFA-Q71L but not on ARF1-T31N nor on ARFA-T31N ( S9 Fig ) . ARFA appeared to be activated faster than ARF1 . In addition , ARFA-Q71L reached a seemingly higher level of activation than ARFA ( wt ) , presumably because GTPγS dissociated more slowly . In contrast , both ARF1-T31N and ARFA-T31N did not show any change over time , resembling the GDP-GTP exchange reaction in the absence of GTPγS ( S9 Fig ) . In conclusion , ARFA-T31N interfered with GDP-GTP exchange essentially like ARF1-T31N and thus , a reason for the lack of biological effect of ARFA-T31N in contrast to ARF1-T31N has to be sought elsewhere ( see Discussion ) . Of the four functionally redundant late secretory ARF-GEFs BIG1 to BIG4 , BIG3 interacted with ARF1 but not with ARFA whereas BIG4 interacted with both ARF1 and ARFA ( see Figs 6F and S8H ) . This observation could in principle explain why strong ARFA-T31N expression had no deleterious effect . To assess the dual-specificity of ARF-GEF BIG4 in planta , we strongly expressed Est>>ARFA-T31N-YFP in a big3 UBQ10::BIG4R-YFP ( engineered BFA-resistant BIG4 [14] ) background . This genetic background in conjunction with brefeldin A ( BFA ) treatment leaves only BIG4 active whereas the functionally overlapping ARF-GEFs BIG1 and BIG2 are inhibited and BIG3 is genetically knocked out . Combined EST and BFA treatment of seedlings resulted in approximately 30% reduction of root growth , suggesting that ARFA-T31N-YFP interfered with the activation of ARF1 in the late secretory pathway required for primary root growth ( S4L Fig ) . The interaction assays suggested that ARF1 is a common substrate of all ARF-GEFs in Arabidopsis . If this is the case , the SEC7 domain might be swapped between ARF-GEFs without affecting the activity of the respective ARF-GEFs . We generated GNL1-BIG3 chimeras with swapped SEC7 domains . In two transgenic lines tested , cis-Golgi-localized GNL1 with the SEC7 domain of the TGN-localized ARF-GEF BIG3 in place of its own was able to rescue gnl1 mutant plants , thus complementing the BFA-sensitive seed germination phenotype and the post-embryonic stunted growth of gnl1 knockout mutant plants ( Fig 7A ) . In three transgenic lines tested , BIG3 with the SEC7 domain of GNL1 in place of its own complemented BFA-sensitive seed germination of big3 knockout mutant and rescued the seed germination defect of big3 mutant seedlings to nearly the same extent as did the parental BIG3 transgene ( Fig 7B ) . In conclusion , the SEC7 domain did not confer specificity of action to ARF1-activating ARF-GEFs . Our results strongly suggest that , in contrast to mammals and yeast , Arabidopsis can successfully carry out essential membrane trafficking with only one class of ARF GTPase , represented by isoforms of ARF1 , and that this single class of ARF GTPase can be activated by all eight ARF-GEFs acting in different trafficking pathways–secretion ( including cytokinesis and vacuolar traffic ) , endocytosis , and recycling ( Fig 8 ) . There are no orthologs of non-plant class-II and class-III ARFs in Arabidopsis or other flowering plants whereas the putative ARFs of the plant-specific classes A and B appear not to be essential . The single ARFB localized mainly to the plasma membrane and has therefore been compared to mammalian Arf6 [24] . However , neither amiR ( ARFB ) nor ARFB-T31N overexpression caused any mutant phenotype and ARFB-Q71L overexpression also had no deleterious effect . Thus , ARFB plays no essential role or its role might be taken over by some functionally overlapping ARF protein . To test for that possibility , we generated estradiol-inducible ARFA-T31N ARFB-T31N co-overexpression plants as well as plants lacking ARFA and ARFB transcripts . Again , there was no deleterious effect . Thus , by whatever criteria used , ARFB protein appears to be of no vital importance . This would be consistent with the phylogenetic analysis indicating that ARFB only arose late in dicot angiosperm evolution and is not present in the vast majority of dicots nor in any of the monocots whose genome has been analyzed , suggesting a specialized role not essential for the majority of trafficking processes . Alternatively , ARFB might not be an ARF GTPase but an ARF-related protein acting in a trafficking-unrelated process . In contrast to ARFA-Q71L , ARFB-Q71L did not interfere with ARF1 trafficking , although by sequence , ARFB is more closely related to ARF1 than is ARFA . Unlike ARFB , ARFA is evolutionarily conserved in the plant lineage . However , the double mutant of arfA ( B1b B1c ) did not show any obvious mutant phenotype and overexpression of ARFA-T31N had no deleterious effect . Thus , ARFA was not required for any essential trafficking pathway . The lack of any deleterious biological effect of ARFA-T31N raised doubts about the functionality of this mutant form of ARFA because one might presume that it ought to block the activation of ARFA and ARF1 if one or more ARF-GEFs activated both ARFA and ARF1 and if ARFA-T31N behaved like ARF1-T31N in its interaction with the SEC7 domain of ARF-GEFs . The in-vitro GDP-GTP exchange assays demonstrated that ARFA-T31N is not activated by the SEC7 domain of BIG5 , although co-immunoprecipitation revealed interaction of ARF-GEF BIG5 with ARFA-T31N but not with ARFA-Q71L . Interestingly , ARFA-Q71L interfered with ARF1-dependent trafficking , suggesting depletion of coat proteins and/or other effectors that are also recruited by ARF1 . ARFA-T31N overexpression blocked the deleterious effect of ARFA-Q71L but , unlike ARF1-T31N , had no deleterious effect on its own . Moreover , T31N acted like an intragenic suppressor of ARFA-Q71L in the ARFA-T31N , Q71L double mutant , and overexpression of this double mutant also blocked the deleterious effects of ARFA-Q71L . Furthermore , strong overexpression of ARF1 was also able to suppress the inhibitory effect of ARFA-Q71L on secretion . Thus , ARFA appears to be activated by some endogenous ARF-GEF ( s ) that also activate ( s ) ARF1 but is/are not essential for activating ARF1 . Indeed , ARFA interacted with BIG5 and BIG4 , both of which also interacted with ARF1 . BIG5 seems to be not essential for plant viability [17 , 18] , and BIG4 acts redundantly with BIG1 , BIG2 and BIG3 in the late secretory pathway [14] . However , the ARF-GEF BIG3 did not interact with ARFA and its SEC7 domain did not activate ARFA but only ARF1 [38] , which would explain why ARFA-T31N cannot block the essential late-secretory pathway to the plasma membrane in interphase and to the cell-division plane in cytokinesis [14] . This conclusion was experimentally supported by demonstrating that ARFA-T31N-YFP expression impaired root growth when only BIG4 of the four functionally redundant late-secretory ARF-GEFs BIG1 to BIG4 was functional . The essential early-secretory pathway between ER and Golgi is most likely not affected by ARFA-T31N because ARF-GEF GNOM , and probably also its paralog GNL1 , does not interact with ARFA . If ARFA is not essential why has it been conserved in plant evolution ? A possible scenario might be that ARFA mediates a trafficking pathway that is non-essential under laboratory conditions because of overlap with a parallel ARF1-dependent trafficking pathway but might become limiting , for example , in fluctuating environmental conditions . Our results strongly suggest that ARF1 is the only functionally required ARF GTPase to mediate all fundamental trafficking pathways ( except SAR1-dependent COPII trafficking for which it is only indirectly required ) in Arabidopsis such that blocking ARF1 function essentially corresponds to knocking out all ARF-GEFs ( Fig 8 ) . Strong expression of ARF1-T31N from fertilization onward arrested embryo development very early , resulting in a multi-nucleate cell , which corresponds to shutting down all membrane trafficking pathways . To break down the global requirement of ARF1 into specific trafficking pathways , we studied the effects of inducible ARF1-T31N overexpression on the subcellular localization of relevant trafficking markers and compared the effects with those of inducibly knocking out specific ARF-GEFs for which we also demonstrated interaction with ARF1 in planta . One result was that ARF1 together with ARF-GEFs GNL1 and GNOM mediates COPI-dependent retrograde Golgi-ER traffic whereas ARF1 together with ARF-GEFs BIG1-4 mediates post-Golgi membrane trafficking from the TGN to the plasma membrane , the vacuole and the cell-division plane . As a consequence , we hypothesized that if indeed ARF1 was the common substrate of all ARF-GEFs regardless of the trafficking pathway , their catalytic SEC7 domains might be interchangeable . We demonstrated this by swapping the SEC7 domains between GNL1 and BIG3 , which gave chimeric proteins that were able to rescue the respective mutants to the same extent as did the parental proteins . Thus , by all available criteria , ARF1 appears to be the only class of ARF GTPase required for the diverse trafficking pathways of flowering plants . In contrast , the ARF-GEFs mediating specific pathways cannot replace each other , suggesting that they might play specific roles in traffic regulation beyond the activation of ARF1 by GDP-GTP exchange and that these functions are exerted by the non-catalytic domains . Arabidopsis thaliana plants were grown on soil or agar plates in growth chambers under continuous light conditions at 23°C . arfB1b mutant line was ordered from INRA ( Flag_289D05; http://www-ijpb . versailles . inra . fr/ ) and arfB1c mutant line from GABI-KAT ( GABI_526B04; http://www . gabi-kat . de ) . arfB1b mutant line was selected on MS plates using Kanamycin; arfB1c mutant line was selected on MS plates using Sulfonamide . The big5 T-DNA line has been described earlier ( AtMIN7 KO #3 [15] ) . Previously published lines that were used in this study: VHA-a1-RFP [39] , Wave22-mCherry [40] , H4::RFP-PEN1 [41] , Est>>AFVY-RFP [14] , N-ST-YFP [42] , sec-mCherry-HDEL [32] , YFP-RABG3f [40 , 43] , GNOM-Myc [11] , GNL1-Myc [12] , GNOM::GNL2-GFP [13] , UBQ10::BIG4-YFP [14] , BIG3::BIG3-YFP [14] . Nicotiana tabacum L . SR1 plants were grown on MS medium supplemented with 2% sucrose , 0 . 5 g l–1 MES and 0 . 8% Agar at pH 5 . 7 in 16/8 h day-night cycles at 22°C . CDS of ARF1 ( ARFA1c ) , ARFB ( ARFB1b and/ or ARFB1c ) and ARFB ( ARFB1a ) were amplified using Sense-Primers containing ApaI restriction site and Antisense-Primers containing AvrII and BamHI restriction sites . Amplified ARF fragments were introduced in pGreen ( Hyg ) -RPS5A-tNos cassette via ApaI and BamHI restriction sites [31] . C-terminal YFP tag was inserted via AvrII restriction site . Site-directed mutagenesis using the following primers was performed to introduce T31N or Q71L mutations: ARF-T31N-YFP and ARF-Q71L-YFP were amplified and cloned into pDONR221 ( Invitrogen ) generating a pEntry clone . Afterwards , LR reaction was performed introducing ARF-T31N-YFP and ARF-Q71L-YFP into a modified β-estradiol inducible pMDC7 vector [44] in which Ubiquitin 10 promoter replaced the original promoter ( kindly provided by Niko Geldner , Univ . Lausanne ) . ARFA ( B1b ) -TN , QL-YFP construct was generated by site-directed mutagenesis on pENTRY-ARFA-TN-YFP using the following primer to introduce Q71L mutation: ARFB1b-Q71L: 5‘GAGGTCTCAGTTTCTCTAGGCCACCAACATCCC 3’ . Afterwards , LR reaction was performed introducing ARFA-T31N , Q71L-YFP into the modified β-estradiol inducible pMDC7 vector [44] including Ubiquitin 10 promoter ( see above ) . T1 plants of RPS5A::ARF-YFP , Est>>ARF-TN-YFP , Est>>ARF-QL-YFP , Est>>ARFA-TN , QL-YFP were selected with hygromycin . Artificial micro RNA of ARFB1a was cloned according to Artificial microRNA Designer: ( http://wmd3 . weigelworld . org/cgi-bin/webapp . cgi; [45] ) using the following primers: The amiRNA precursor fragment was cloned into pGII ( Bar ) -RPS5A-tNos expression cassette [31] . T1 plants were selected using Phosphinotricine . UBQ10::BIG5-YFP was cloned by amplifying BIG5 CDS from a cDNA library , cloned into pDONR221 ( Invitrogen ) and afterwards into UBQ10::YFP destination vector [46] . T1 plants were selected by using phosphinotricine . Generation of SEC7 Swap constructs: PCRs to generate a BIG3-SEC7 fragment with GNL1 sequence overlaps at the borders were performed with the following primers: Expression cassette generation: The vector pFF04 [47] was modified to contain a mas promoter sequence , NLS-GFP , and a 35S terminator sequence . The modified vector was called pFK059 . The mas promoter is bidirectional , regulating transcription of the gene of interest on one side and of NLS-GFP on the other side . The latter can be used as an indirect expression control . The sequences were PCR amplified to introduce restriction sites for cloning with the following primers: RNA was isolated using peqGOLD RNA extraction kit ( VWR ) and cDNA was generated from 1μg RNA using Thermo Scientific Maxima H Minus Reverse Transcriptase Kit ( Thermo Scientific ) . Complete CDS of ARF GTPases ( from start to stop ) were amplified using 0 . 5μl or 1μl of cDNA for PCR . RPS5A::Gal4 activator line was pollinated with UAS::ARF 1-TN-YFP , UAS::ARF 1-QL-YFP , UAS::ARF A-TN-YFP and UAS::ARF A-QL-YFP reporter lines . 3 or 5 days after pollination siliques were opened and ovules were mounted in chloral hydrate solution [48] . Images were taken at the Zeiss Axiophot using a 40x Objective . Five days old seedlings were incubated in 1 ml liquid growth medium ( 0 . 5x MS medium , 1% sucrose , pH 5 . 8 ) containing 20 μM Estradiol ( Sigma Aldrich ) for 5-6h at plant room conditions in 24-well cell-culture plates . Incubation was stopped by fixation with 4% paraformaldehyde in MTSB . Immunofluorescence staining was performed as described [49] or with an InsituPro machine ( Intavis ) [50] . Antibodies used: rat anti-tubulin 1:600 ( Abcam ) , rabbit anti-AtγCOP 1:1000 ( Agrisera ) , rabbit anti-KNOLLE 1:2000 [49] , rabbit anti-clathrin ( 1:600 ) [51] . Alexa633 ( Invitrogen ) or Cy3-conjugated secondary antibodies ( Dianova ) were diluted 1:600 . Live-cell imaging was performed with 2 μM FM4-64 ( Invitrogen , Molecular Probes ) . Estradiol induction was performed using 20μM Estradiol for 5-6h at plant room conditions in 24-well cell-culture plates . Fluorescence images were acquired at the confocal laser scanning microscope TCS-SP8 from Leica or LSM880 from Zeiss , using the 63x water-immersion objectives and Leica or Zen software . Images were generated using PMT , HYD or GaAsP detectors . Airyscan detector ( Zeiss ) was used for images in Figs 3A–3G and 5A–5G . All images were processed with Adobe Photoshop CS3 or CS5 only for adjustment of contrast and brightness . Intensity line profile was performed with Leica software . For thawed cryosection labeling , seedlings were fixed with 4% formaldehyde ( 30 min , RT ) and 8% formaldehyde ( 90–120 min , RT ) , embedded in 10% gelatin and infiltrated with a mixture of 1 . 8 M sucrose and 20% polyvinylpyrrolidone [52] . Infiltrated gelatin blocks were mounted on stubs , frozen in liquid nitrogen and sectioned at -115°C ( 80 nm ) in a Leica UC7/FC7 cryo-ultramicrotome . Thawed cryosections were placed on grids covered with pioloform and carbon for immunolabeling . Unspecific binding sites were blocked with PBS containing 0 . 2% BSA and 0 . 2% milk powder . Sections were labeled with rabbit anti-GFP ( 1:200; [53] ) diluted in blocking buffer and goat anti-rabbit IgG coupled to 6 nm gold ( 1:30; Dianova , Hamburg ) or to ultrasmall gold ( Aurion , Wageningen ) . Gold particles were silver-enhanced using R-Gent ( Aurion ) for 35–40 min . Finally sections were stained with 1% aqueous uranyl acetate and embedded in a thin layer of methyl cellulose containing 0 . 3–0 . 45% uranyl acetate . For resin section labeling with xyloglucan-specific antibodies , 1 mm long seedling root tips were high-pressure frozen ( HPM 010; Bal-Tec , Balzers , Lichtenstein ) in 100 μm planchettes filled with 1-hexadecene ( Merck Sharp and Dohme ) and freeze-substituted in acetone supplemented with 0 . 4% uranyl acetate and 1 . 6% methanol . After 50 h at -90°C , samples were warmed up to -50°C and washed 5x with acetone before they were infiltrated with 25% , 50% , 75% and 2x 100% Lowicryl HM20 at -50°C . Infiltrated samples were UV-polymerized for two days at -50°C . For immunolabeling , 70 nm thin sections were cut ( Leica UC7 ) and mounted on coverslips for FM or slot grids covered with Pioloform for IEM and CLEM . For immunogold labeling of grids , sections were labeled as described above with mouse anti-xyloglucan antibodies ( mAb CCRC-M1 , 1:10; Carbosource Services , University of Georgia ) and goat anti-mouse IgG coupled to 6 nm gold ( 1:30; Dianova , Hamburg ) . In some cases gold particles were silver-enhanced as described above . Resin sections were stained with 1% aqueous uranyl acetate for 4–5 min and lead citrate for 15–20 sec . For fluorescence labeling of coverslips , sections were labeled as described above with mouse anti-xyloglucan antibodies ( 1:10 ) and goat anti-mouse IgG coupled to Cy3 ( 1:400; Dianova , Hamburg ) . Resin sections were stained for DNA with 1 μg/ml Dapi ( 4´ , 6-diamidino-2-phenylindole ) for 5 min and embedded in Moviol containing DABCO ( 1 , 4-diazabicyclo[2 . 2 . 2]octane ) as antifading agent . Background was negligible in control experiments without first antibody . Sections were viewed using a Zeiss Axioimager M2 with a 63x/1 . 40 oil immersion objective . Images were taken with a sCMOS Orca-flash4 . 0 camera ( Hamamatsu ) . Contrast and brightness were adapted using Photoshop software . For simultaneous double labeling with fluorescence and gold markers , sections mounted on slot grids were incubated with mouse anti-xyloglucan antibodies ( 1:10 ) as described above . Thereafter , sections were labeled with goat anti-mouse IgG coupled to 6 nm gold ( 60 min ) , directly followed by incubation with goat anti-mouse IgG coupled to Cy3 ( 60 min ) . There are enough unbound first antibodies left for fluorochrome coupled marker molecules . Slot grids were then stained with DAPI and mounted on a slide under a coverslip ( in 50% glycerol ) with two additional coverslips laterally placed as spacer and fluorescent images were taken ( see above ) . Thereafter , sections were washed with double distilled water and stained with 1% aqueous uranyl acetate ( 5 min ) and in some cases with lead citrate ( 15–30 sec ) . Stained sections were examined in a Jeol TEM ( see below ) . Alignment and overlay of light microscopic and electron microscopic images were performed with Picture Overlay Program ( Jeol ) . For ultrastructural analysis , 1 mm long seedling root tips were high-pressure frozen ( HPM 010 ) in 100 μm planchettes filled with 1-hexadecene and freeze-substituted in acetone supplemented with 2 . 5% osmium tetroxide ( 35 h at -90°C , 6 h at -60°C , 6 h at -30°C , 2 h at 0°C ) . Thereafter samples were washed 5x with acetone ( 0°C ) , before they were infiltrated with 10% , 25% , 50% , 75% , 2x 100% epoxy resin ( Roth , Germany ) . Infiltrated samples were polymerized at 60°C for two days . For ultrastructural analysis , 70 nm thin sections were cut and mounted on slot grids covered with pioloform . Sections were stained with 3% uranyl acetate in 50% ethanol , followed by lead citrate and viewed in a Jeol JEM-1400plus TEM at 120 kV accelerating voltage . Images were taken with a 4K CMOS TemCam-F416 camera ( TVIPS ) . Contrast and brightness were adapted using Photoshop software . Arabidopsis seedlings ( 5–6 days old ) were ground in liquid nitrogen and suspended in lysis buffer ( 50mM Tris pH 7 . 5 , 150mM NaCl , 2mM EDTA , 1% Triton X-100 ) supplemented with protease inhibitors ( cOmplete EDTA-free , Roche ) . The cell lysate was cleared by centrifugation at 10 , 000 x g for 15 min at 4°C . The supernatant was filtered through two layers of Miracloth ( Calbiochem ) and incubated with α-Myc-agarose beads ( Sigma ) or GFP-Trap beads ( Chromotek ) or RFP-Trap beads ( Chromotek ) for binding in cold room for 2 . 5-3h . The agarose beads , after binding , were washed 2–4 times with wash buffer ( 50mM Tris pH 7 . 5 , 150mM NaCl ) containing 0 . 1% Triton , followed by 1–2 washes using wash buffer lacking Triton and boiled in 2x Laemmli buffer . To perform immunoprecipitation in the presence of brefeldin A ( BFA ) , Arabidopsis seedlings were treated with BFA ( 50 μM ) for 2h before grinding . In addition , BFA ( 50μM ) was also added to all buffers during immunoprecipitation . For MS analysis , YFP-tagged GTPases ( ARF and RABG3f ) were immunoprecipitated in the presence of brefeldin A ( BFA ) using GFP-Trap beads ( Chromotek ) . The beads were washed 1x with wash buffer ( 50mM Tris pH 7 . 5 , 150mM NaCl ) containing 0 . 5% Triton and 3x with wash buffer containing 0 . 1% Triton . Proteins bound to the beads were eluted by boiling in 2x Laemmli buffer . To express ARF-T31N and ARF-Q71L isoforms for immunoprecipitation , 5–6 days old seedlings were incubated in liquid MS medium ( 0 . 5x MS medium , 1% sucrose , pH 5 . 8 ) containing 20 μM Estradiol ( Sigma Aldrich ) for 6h at plant room conditions . The seedlings were subsequently snap frozen in liquid nitrogen and stored at -80°C . Proteins were separated on SDS-PAGE , transferred to the PVDF membrane ( Millipore ) and detected using one of the following antibodies: α-GFP ( mouse , 1:1 , 000 , Roche ) , α-RFP ( rat , 1:1 , 000 , Chromotek ) , α-Myc ( 1:1 , 000 , Sigma ) , α-ARF1 ( rabbit , 1:2 , 000 , Agrisera ) , α-GN-SEC7 ( rabbit , 1:2 , 500 ) [37] , and POD-conjugated secondary antibodies . Chemiluminescence signal was acquired using Fusion Fx7 detection system ( PEQlab , Erlangen , Germany ) . Eluted proteins were purified using SDS PAGE ( Invitrogen ) . Coomassie-stained gel pieces were excised and in-gel digested using Trypsin as described previously [54] . Extracted peptides were desalted using C18 StageTips [55] and subjected to LC-MS/MS analysis that was performed on an Easy nano-LC ( Thermo Scientific ) coupled to an LTQ Orbitrap XL mass spectrometer ( Thermo Scientific ) as described elsewhere [56] . The peptide mixtures were injected onto the column in HPLC solvent A ( 0 . 1% formic acid ) at a flow rate of 500 nl/min and subsequently eluted with an 127 minute segmented gradient of 5–33-50-90% of HPLC solvent B ( 80% acetonitrile in 0 . 1% formic acid ) at a flow rate of 200 nl/min . The 10 most intense precursor ions were sequentially fragmented in each scan cycle using collision-induced dissociation ( CID ) . In all measurements , sequenced precursor masses were excluded from further selection for 90 s . The target values were 5000 charges for MS/MS fragmentation and 106 charges for the MS scan . Acquired MS spectra were processed with MaxQuant software package version 1 . 5 . 2 . 8 [57] with integrated Andromeda search engine [58] . Database search was performed against a target-decoy Arabidopsis thaliana database obtained from Uniprot , containing 33 , 431 protein entries and 285 commonly observed contaminants . In database search , full specificity was required for trypsin . Up to two missed cleavages were allowed . Oxidation of methionines and N-terminal acetylation were specified as variable modifications , whereas carbamidomethylation on cysteines was defined as a fixed modification . Initial mass tolerance was set to 4 . 5 parts per million ( ppm ) for precursor ions and 0 . 5 dalton ( Da ) for fragment ions . Peptide , protein and modification site identifications were reported at a false discovery rate ( FDR ) of 0 . 01 , estimated by the target/decoy approach [59] . The iBAQ algorithm was enabled to estimate quantitative values by dividing the sum of peptide intensities of all detected peptides by the number of theoretically observable peptides of the matched protein [60] . Expression of SEC7BIG3 and its ARF substrates , production of recombinant proteins , and fluorescence measurements were performed as described [38] . The catalytic SEC7 domain of BIG5 ( residues 587–791 ) was cloned into pET30a vector ( Merck ) for expression in E . coli . For expression of ARFs , DNA fragments corresponding to residues 18–181 of ARF1 isoforms ( ARF1-WT , ARF1-T31N ) and to residues 18–192 of ARFA ( ARFB1b ) isoforms ( ARFA-WT , ARFA-T31N and ARFA-Q71L ) were PCR-amplified from respective templates and cloned into pET30a vector using NcoI and XhoI . The following primers were used for amplification of ARF1-WT and ARF1-T31N: ARF1d17_pET30_F , CCTTCCATGGGTATGCGTATTCTGATGGTT; ARF1d17_pET30_R , CCTTCTCGAGTTATGCCTTGCTTGCGATGTT . The following primers were used for amplification of ARFA-WT , ARFA-T31N and ARFA-Q71L: ARFAd17_pET30_F , CCTTCCATGGGTATGAGGGTCGTTATGCTG; ARFAd17_pET30_R , CCTTCTCGAGTTAAAACGAGTGGCCAACC . The recombinant proteins were expressed in BL21 ( DE3 ) strain of E . coli by inducing with 0 . 05mM IPTG for 24h at 18°C . The histidine-tagged ( 6XHis ) proteins were purified using HisPur Ni-NTA resin ( Thermo Scientific ) according to the manufacturer´s instructions . The in-vitro exchange assay was performed as described [61] . Briefly , 25μM histidine tagged ARF protein solution in GDP exchange buffer ( 20mM HEPES-NaOH ( pH7 . 5 ) , 50mM NaCl , 0 . 5mM MgCl2 , 5mM EDTA , 1mM DTT ) was added with 24-fold molar excess of GDP ( Sigma ) and the reaction mixture was incubated for 90min at 20°C . The reaction was stopped by addition of MgCl2 to a final concentration of 10mM and a subsequent incubation for 30min at 20°C . Afterwards , the buffer of the protein sample was exchanged to the nucleotide exchange buffer ( 40mM HEPES-NaOH ( pH 7 . 5 ) , 50mM NaCl , 10mM MgCl2 , 1mMDTT ) . For SEC7BIG5 mediated exchange measurements , 1μM of ARF proteins in nucleotide exchange buffer and 50nM SEC7BIG5 were used . The exchange reaction was initiated by adding 66μM GTPγS at 37°C . The measurement of tryptophan fluorescence was carried out using FS5-Spectrofluorometer ( Edinburgh Instruments ) at the excitation and emission wavelength of 298nm and 340nm , respectively [38] . Protoplasts were prepared and electrotransfected as previously done [47] . Harvesting and analysis of medium and cell samples as well as calculation of the secretion index was performed as described [62] . To investigate primary root growth , 5–6 days old seedlings were transferred to plates with 20 μM Estradiol and or 5μM BFA and analyzed after 2 additional days using ImageJ . For analysis of seed germination , seeds were sown out on 20μM Estradiol or 5μM/7μM BFA containing MS-medium . Images were taken after 5 days of growth . Full-length protein sequence of ARFA1c , ARFB1b and ARFB1a and ARFD was used to search for related sequences from different plant species with sequenced genomes that are available at the NCBI ( https://blast . ncbi . nlm . nih . gov/Blast . cgi ) or phytozome homepage ( http://www . phytozome . net/ ) . ARF sequences from different species were aligned and the phylogenetic tree was drawn with CLC software . Full-length protein sequence of GNOM , GNL1 , GNL2 , BIG1-BIG5 , HsGBF1 , HsBIG , HsBIG2 ScGea1 , ScGea2 and ScSec7 were aligned and the phylogenetic tree was drawn with CLC .
Membrane traffic plays an important role in cellular homeostasis , cell-cell communication , nutrient uptake and organismal interaction , delivering membrane proteins as well as secreted proteins to their sites of action and degradation . This requires sorting of proteins into forming membrane vesicles , which then bud from a donor compartment and eventually fuse with an acceptor compartment , releasing their cargo . Formation of vesicles is initiated by ARF GTPase activation through an interacting ARF guanine-nucleotide exchange factor ( ARF-GEF ) on the donor membrane , resulting in the recruitment of specific coat proteins . In mammals , different classes of ARF GTPases are activated by diverse ARF-GEFs . In contrast , much less is known in plants , although there appears to be only a single family of large ARF-GEFs , and only one ARF class represented by ARF1 isoforms is conserved . Instead , there are plant-specific putative ARFs , which however , are functionally uncharacterized . Here we show that only ARF1 is required for normal development of Arabidopsis and can mediate all specific trafficking pathways whereas the other putative ARFs are not essential . Furthermore , ARF1 interacts with all ARF-GEFs acting in specific trafficking pathways . Our results thus suggest that ARF-GEFs rather than ARFs likely contribute to the specificity of membrane trafficking in plants .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "cell", "physiology", "vesicles", "enzymes", "brassica", "enzymology", "hormones", "model", "organisms", "immunoprecipitation", "experimental", "organism", "systems", "seedlings", "co-immunoprecipitation", "plants", "cellular", "structures", "and", "organelles", "estradiol", "arabidopsis", "thaliana", "research", "and", "analysis", "methods", "animal", "studies", "proteins", "guanosine", "triphosphatase", "membrane", "trafficking", "precipitation", "techniques", "cell", "membranes", "biochemistry", "eukaryota", "plant", "and", "algal", "models", "hydrolases", "cell", "biology", "lipid", "hormones", "biology", "and", "life", "sciences", "organisms" ]
2018
A single class of ARF GTPase activated by several pathway-specific ARF-GEFs regulates essential membrane traffic in Arabidopsis
The zinc finger antiviral protein ( ZAP ) is a mammalian host restriction factor that inhibits the replication of a variety of RNA viruses , including retroviruses , alphaviruses and filoviruses , through interaction with the ZAP-responsive elements ( ZRE ) in viral RNA , and recruiting the exosome to degrade RNA substrate . Hepatitis B virus ( HBV ) is a pararetrovirus that replicates its genomic DNA via reverse transcription of a viral pregenomic ( pg ) RNA precursor . Here , we demonstrate that the two isoforms of human ZAP ( hZAP-L and -S ) inhibit HBV replication in human hepatocyte-derived cells through posttranscriptional down-regulation of viral pgRNA . Mechanistically , the zinc finger motif-containing N-terminus of hZAP is responsible for the reduction of HBV RNA , and the integrity of the four zinc finger motifs is essential for ZAP to bind to HBV RNA and fulfill its antiviral function . The ZRE sequences conferring the susceptibility of viral RNA to ZAP-mediated RNA decay were mapped to the terminal redundant region ( nt 1820–1918 ) of HBV pgRNA . In agreement with its role as a host restriction factor and as an innate immune mediator for HBV infection , ZAP was upregulated in cultured primary human hepatocytes and hepatocyte-derived cells upon IFN-α treatment or IPS-1 activation , and in the livers of hepatitis B patients during immune active phase . Knock down of ZAP expression increased the level of HBV RNA and partially attenuated the antiviral effect elicited by IPS-1 in cell cultures . In summary , we demonstrated that ZAP is an intrinsic host antiviral factor with activity against HBV through down-regulation of viral RNA , and that ZAP plays a role in the innate control of HBV replication . Our findings thus shed light on virus-host interaction , viral pathogenesis , and antiviral approaches . Hepatitis B virus ( HBV ) is the etiological agent of human hepatitis B . Despite the fact that most adulthood HBV infections are transient , approximately 5–10% of infected adults and more than 90% of infected neonates develop a life-long chronic infection , constituting a substantial public health burden affecting an estimated 350 million individuals worldwide . HBV carriers suffer from a high risk of cirrhosis , primary hepatocellular carcinoma , and other severe clinical sequelae [1]–[5] . HBV is a noncytopathic , hepatotropic virus belonging to the hepadnaviridae family . The virion is an enveloped icosahedral nucleocapsid containing a partially double stranded relaxed circular ( RC ) DNA genome of 3 . 2 kb . Upon infection of hepatocytes , the viral RC DNA enters the nucleus and converts into an episomal covalently closed circular ( ccc ) DNA , which serves as the template for all viral RNA transcripts , including precore mRNA ( 3 . 5∼3 . 6 kb ) , pregenomic ( pg ) RNA ( 3 . 5 kb ) , surface ( envelope ) mRNA ( 2 . 4 and 2 . 1 kb ) , and X mRNA ( 0 . 7 kb ) . After nuclear export , cytoplasmic pgRNA is translated into viral capsid proteins and polymerase ( pol ) , followed by in situ binding of pol to a stem loop structure termed epsilon ( ε ) at the 5′ terminus of pgRNA , which in turn triggers encapsidation of the pol/pgRNA complex . Viral double stranded DNA synthesis then occurs , inside of the nucleocapsid , in an asymmetric fashion . Viral pol reverse transcribes pgRNA into minus strand DNA , followed by plus strand DNA synthesis and circularization into the RC DNA genome . The mature cytoplasmic nucleocapsid is then packaged by viral envelope proteins and secreted as a progeny virus . Alternatively , the newly synthesized RC DNA can be transported to the nucleus to amplify the cccDNA reservoir , thereby maintaining a chronic state of HBV infection . ( Reviewed in [2] , [6] , [7] ) It is generally accepted that host functions determine virus tropism and replication fitness [8] , [9] . HBV reproduction requires liver enriched transcription factors ( i . e . HNF4 and RXRα ) as well as more ubiquitous host factors , such as chaperon protein Hsp90 that coordinates the assembly of the pol/pgRNA complex [10]–[13] . The reproduction of HBV is also restricted by intrinsic and extrinsic host factors and stimuli . Specific hormones and inflammatory cytokines/chemokines have been shown to suppress HBV replication both in cultured cells and in vivo [14]–[20] . It is also clear that the balance between viral replication and host immunity determines the course of viral infection . Rigorous HBV specific polyclonal cytotoxic T lymphocytes and humoral responses can clear viral infection , whereas the lesser responses can cause chronic liver disease without actually eliminating the virus [21] , [22] . In coordination with adaptive immune responses , host innate immunity also plays a critical role in the control of viral replication [23] . Central to this cellular response is the secretion of interferons ( IFN-α/β ) , which act on target cells to induce an array of interferon stimulated genes ( ISGs ) that limit virus infection [24] . Although considerable evidence suggests that HBV has evolved strategies to evade or antagonize host innate defenses [25]–[29] , viral replication is still somewhat suppressed by IFN in laboratory studies and clinical treatments [15] , [16] , [30] , [31] . The intracellular antiviral response elicited by IFN targets multiple steps in the HBV life cycle , including HBV RNA synthesis [31]–[33] , pgRNA encapsidation [34] , and the turnover rate of viral proteins and nucleocapsids [35] , [36] . Therefore , it is of interest to identify host proteins that impede HBV replication under homeostatic or inducible conditions . The zinc finger antiviral protein ( ZAP , also known as ZC3HAV1 ) was originally discovered in rat as a host antiretroviral factor that prevents cells from infection by Moloney murine leukemia virus ( MMLV ) [37] . The antiviral spectrum of rat ZAP ( rZAP ) has been expanded to other kinds of RNA viruses , including certain alphaviruses ( Sindbis virus and Ross River virus ) and filoviruses ( Ebola virus and Marburg virus ) [38]–[40] . Human ZAP exists in long and short isoforms ( hZAP-L and hZAP-S , respectively ) derived from alternative mRNA splicing , with hZAP-L containing an additional C-terminal poly ( ADP-ribose ) polymerase ( PARP ) domain [41] . Both hZAP isoforms have antiviral effects against several RNA viruses , including MMLV , Semliki Forest virus , HIV-1 and xenotropic murine leukemia virus-related virus ( XMRV ) [41]–[43] . However , rZAP does not inhibit the replication of vesicular stomatitis virus , yellow fever virus , poliovirus , or herpes simplex virus 1 , indicating that the antiviral activity of ZAP is highly reliant on virus-specific features [38] . Along these lines , mechanistic studies revealed that rZAP binds to its viral RNA substrate through its N-terminal zinc finger motifs , and in turn recruits a host RNA processing complex , specifically the exosome , to degrade the viral RNA [44]–[46] . The viral RNA motif responsible for the binding of ZAP is called the ZAP-responsive element ( ZRE ) , which has been mapped to the 3′-LTR of MMLV [44] , 5′-UTR of HIV-1 nef mRNA [42] , 3′-UTR of XMRV [43] , and multiple fragments in Sindbis virus [44] . Although these ZREs are all more than 500 nucleotides long , there is no significant degree of sequence homology or common structural similarity in these ZREs [42]–[44] , [46] . Recently , ZAP was shown to inhibit murine gammaherpesvirus 68 ( MHV-68 ) M2 mRNA expression [47] . This is the first report that ZAP possesses antiviral activity against a DNA virus . Since mRNA intermediate ( s ) is an essential component for DNA viruses to fulfill their life cycle , it is possible that ZAP might specifically target certain DNA virus encoded mRNA for degradation to inhibit virus replication . Based upon a defining feature , that a reverse transcription step is involved in hepadnavirus DNA replication , HBV has been classified as a member of the pararetroviruses , a groups of viruses which have evolutionary relationships with retroviruses [7] , [48] . As a well-known antiretroviral host factor , it is of interest to examine whether ZAP also restricts HBV replication . In addition , cellular ZAP mRNA can be upregulated under interferon treatment or certain virus infection , suggesting ZAP may play a role in the innate defenses of virus infection [49]–[52] . Moreover , previous reports suggested that HBV mRNA down-regulation is involved in the antiviral state elicited by the activation of innate immune response [32] , [53] . Therefore , we also studied the potential function of ZAP in the innate control of HBV replication . Herein , we report that ectopic expression of ZAP can markedly suppress HBV replication in human hepatocyte-derived cells , primarily through posttranscriptional down-regulation of viral RNA in the cell nuclei . The zinc-finger-motifs-containing N-terminus is the functional antiviral domain of ZAP , and the integrity of the tetra-partite zinc fingers confers the optimal antiviral activity against HBV . Furthermore , we observed a physical interaction between ZAP and HBV RNA in the immunoprecipitation assay , and the HBV ZRE was mapped to the terminal redundant region of viral RNA . In addition , both hZAP-L and hZAP-S exhibit a basal level expression in primary human hepatocytes and hepatocyte-derived cells , and the levels of the short isoform could be further induced by IFN treatment or expression of beta interferon promoter stimulator 1 ( IPS-1 ) . Knock down experiment revealed that the basal level of ZAP limits HBV replication , and ZAP plays a partial role in IPS-1-induced HBV RNA destabilization . Our results thus demonstrated that ZAP is a host intrinsic antiviral factor against HBV , and suggested that ZAP plays a role in the innate control of HBV replication . The inclusion of HBV in ZAP's antiviral spectrum will not only contribute to a better understanding of ZAP biology and virus-host interaction , but may ultimately lead to development of novel strategies utilizing host functions for hepatitis B therapeutics . As shown in Fig . 1A , overexpression of both human ZAP ( -L or -S ) and the N-terminus of rat ZAP ( rN-ZAP ) led to a significant reduction of HBV DNA replication in HepG2 cells ( middle panels ) . This was achieved primarily through reducing the steady state levels of viral pgRNA ( top panels ) , which is the template for HBV DNA synthesis . The doublet bands of pgRNA contain the full-length HBV pgRNA of 3 . 5 kb ( lower band ) and a longer form of pgRNA transcripts ( upper band ) terminated at an additional polyadenylation site in the vector sequences from pHBV1 . 3 or pCMVHBV ( data not shown ) . The less significant inhibitory effect against HBV replication by ZAP-L was likely due to its lower level of expression ( bottom panel ) . Both hZAP-L and -S exhibited antiviral activity , indicating that the C-terminal PARP domain in hZAP-L is dispensable . Reduction of HBV RNA by ZAP expression was independent of the promoter driving transcription of HBV pgRNA ( HBV authentic core promoter in pHBV1 . 3 , CMV-IE promoter in pCMVHBV ) , although an apparent lower degree of inhibition in the CMV-IE driven samples was likely due to overall higher RNA expression levels and ZAP may work stoichiometrically , which the ratio between the amount of HBV RNA and ZAP determines the degree of inhibitory effect of ZAP . The statistical analyses of ZAP-mediated HBV RNA reduction from multiple repeated experiments are depicted in Fig . 1B . These observations indicate that ZAP may posttranscriptionally promote HBV pgRNA decay , or perhaps inhibit a common transcription factor ( s ) shared by both viral promoters . ZAP's antiviral activity against HBV was not limited to HepG2 or hepatocyte-derived cells . Expression of ZAP also efficiently reduced HBV RNA in hepatoma Huh7 cells and in human embryonic kidney 293T cells ( Fig . S1 ) , suggesting that liver-specific host factors are not absolutely required for ZAP's antiviral function . In addition , along with pgRNA reduction , the levels of 2 . 4 kb and 2 . 1 kb HBV mRNA , which share 100% sequence identity with the 3′ portion of pgRNA , were also reduced upon ZAP expression ( Fig . 1 and S1 ) . Considering that the two subgenomic RNA entities might contain both surface antigen mRNA and putative spliced pgRNA [54] , we further demonstrated that ZAP-S was able to reduce viral surface mRNAs in Huh7 cells transfected with vectors expressing them alone ( Fig . S2 ) . In order to determine whether ZAP-mediated down-regulation of HBV RNA was due to a transcriptional or posttranscriptional mechanism , we first ruled out the possibility that ZAP may degrade the transfected HBV plasmids . As shown in Fig . S3 , while ZAP-S expression reduced the levels of HBV DNA replication , the cotransfected HBV plasmid signal revealed by Dpn I digestion and DNA hybridization was equivalent to the control ( Fig . S3A ) . In addition , overexpression of ZAP-S reduced viral RNA and DNA in the HBV stable cell line HepDES19 , in which HBV RNA is transcribed from an integrated transgene ( Fig . S3B ) . Collectively , these observations suggested that ZAP expression does not alter the amount or stability of HBV RNA transcription templates . Next , promoter reporter assays demonstrated that ZAP-S did not significantly affect the activities of HBV core promoter and CMV-IE promoter ( Fig . 2A ) , and even boosted HBV S1 and S2 promoter activities ( Fig . 2B ) . Thus , we speculated that ZAP-mediated HBV RNA reduction was not due to a transcriptional inhibition , if any , but rather through accelerating HBV RNA decay . To further confirm the above hypothesis , we directly measured the decay kinetics of HBV RNA in the absence and presence of ZAP overexpression . Briefly , HepDES19 cells were transfected with control vector or plasmid ZAP-S in the absence of tetracycline ( to induce HBV RNA transcription ) ; after 36 h , tetracycline was added back to the medium to shut down de novo transcription of HBV pgRNA from the transgene , and the decay kinetics of HBV RNA were determined in a time course study . As shown in Fig . 3B–C , the velocity of HBV RNA degradation in HepDES19 cells was faster in the presence of overexpressed ZAP-S than that in the control experiment , suggesting that ZAP promotes HBV RNA degradation . Thus , we concluded that ZAP-mediated HBV RNA reduction is through posttranscriptional downregulation of HBV RNA stability . This is consistent with the previous observations that ZAP reduced viral RNA in a posttranscriptional manner [37]–[39] , [42] . Previous studies showed that rat ZAP shuttles between the nucleus and the cytoplasm in a CRM1-dependent manner [55] . We first examined the intracellular distribution of hZAP-S in human hepatocyte-derived cells . Immunofluorescence microscopy ( Fig . 4A ) and cell fractionation experiments ( Fig . 4B , C ) demonstrated that hZAP-S was present in both cytoplasm and nucleus , and that hZAP-S-mediated HBV mRNA decay was primarily a nuclear event , although the possibility that ZAP also reduces HBV RNA in the cytoplasm cannot be ruled out . It has been previously shown that rN-ZAP prevented retroviral RNA accumulation in the cytoplasm without affecting the nuclear viral mRNA level in rat fibroblast cells [37] . The observed purge of HBV mRNA in the nucleus by hZAP-S indicated that the cell nucleus contains all the necessary machinery for ZAP-mediated RNA degradation , although this phenomenon may be specific to HBV and/or hepatocytes . ZAP contains four putative CCCH-type zinc finger motifs ( ZF ) in its N-terminal 254 amino acid ( a . a . ) portion , which is highly conserved among rat , mouse and human ZAP isoforms ( Fig . 5A ) [37] , [41] , [44] , [56] . The conformation and spatial disposition of these four ZF have been recently delineated in the crystal structure of rN-ZAP [57] . Previous studies demonstrated that rN-ZAP retains the antiviral function and the C-terminal region of rZAP is dispensable for ZAP's antiviral activity [37] , [46] , which is consistent with our observation that expression of rN-ZAP was sufficient to reduce HBV mRNA ( Fig . 1 ) . In order to determine if the N-terminal portion of hZAP possesses an anti-HBV function similar to the full length ZAP , the N-terminal 254 a . a . homologue of hZAP was expressed in HBV transfected HepG2 cells ( Fig . 5A ) . The results showed that hN-ZAP reduced HBV RNA to a similar extent as both hZAP-S and rN-ZAP did ( Fig . 5B ) , suggesting that the N-terminus of hZAP is the functional antiviral domain against HBV . Among the four zinc-finger motifs within the N-terminus of rat ZAP , it has been reported that disruption of the second and fourth zinc fingers abolished ZAP's activity against retroviral RNA , whereas disruption of the first and third zinc fingers only slightly lowered its activity [44] . To determine the requirement of each zinc finger in hZAP-mediated HBV RNA reduction , amino acid mutation was introduced into each zinc finger motif of ZAP-S to disrupt the CCCH-type zinc finger structures individually or all together according to the previous studies [44] ( Fig . 5A ) . The mutant ZAP-S proteins were coexpressed with HBV in HepG2 cells and their effects on viral RNA and DNA were analyzed . While disruption of each individual zinc fingers , specifically ZAP-S H86K , C88R , C168R , H191R , partially decreased the antiviral activity of hZAP-S ( Fig . 5C ) , ablation of the entire four zinc fingers ( ZAP-SΔ4ZFs ) completely abolished ZAP-mediated HBV RNA decay ( Fig . 5D ) , indicating that each zinc finger contributes to the anti-HBV function of ZAP , and the optimal antiviral activity of ZAP requires the integrity of all the four zinc fingers . Interestingly , increased steady state levels of ZAP-S were observed when the zinc finger motifs were mutated ( Fig . 5C and D , bottom panels ) , indicating that the zinc finger motifs may influence the stability of ZAP . Host CCCH-type zinc finger-containing proteins have been reported to be able to bind specific RNA species [58]–[60] , and rN-ZAP has been shown to be capable of binding to MMLV and Sindbis virus RNA fragments [44] . The observed zinc finger-dependent reduction of HBV RNA by hZAP suggested that the protein may interact with HBV RNA as well . To test this hypothesis , a cell based co-immunoprecipitation assay was performed . As shown in Fig . 6 , with HBV expression alone serving as a negative control ( lane 1 ) , immunoprecipitation of HA-tagged wildtype ZAP-S from the lysate of HBV cotransfected HepG2 cells pulled down HBV pgRNA and subgenomic RNAs ( lane 2 ) , but HBV RNA was not co-precipitated with ZAP-SΔ4ZFs even though equivalent pull-down levels of mutant and wildtype ZAP were detected by Western blot ( lane 3 , compared to lane 2 ) . Immunoprecipitation with anti-FLAG antibodies did not capture any ZAP protein and HBV RNA ( data not shown ) . These data , in combination with the results from Fig . 5 , support the notion that ZAP binds to HBV RNA through zinc finger motifs , and such protein-RNA interaction is required for the antiviral activity of ZAP against HBV . The above observations demonstrated that HBV RNA is regulated posttranscriptionally by ZAP , and that ZAP physically interacts with HBV RNA , suggesting that ZAP targets specific HBV RNA sequences for degradation . Such RNA sequences , specifically ZAP-responsive elements ( ZREs ) , have been previously identified in certain retrovirus , filovirus , and alphavirus RNA genomes [39] , [42]–[44] , [61] . However , while sequence homology exists among identified retroviral ZREs , neither sequence identities nor secondary structure similarities have been found between ZREs from different viruses [43] , and HBV pgRNA does not display apparent sequence homology to any of those known ZREs ( data not shown ) . To detect potential HBV ZRE ( s ) that confer susceptibility to ZAP-mediated viral RNA degradation , we scanned the entire 3 . 5 kb HBV pgRNA genome . To this end , 14 internal deletion clones and 3 terminal deletion clones of the HBV genome were constructed to express HBV RNA fragments ( Fig . 7A ) , and their sensitivities to ZAP-mediated RNA reduction were analyzed . Albeit the RNA expression levels varied among different constructs , most likely due to the absence of potential cis-elements maintaining HBV RNA stability , pgRNAs with consecutive internal deletions ( nt 2009-3182/1-1574 ) remained sensitive to ZAP-S , implying that the ZRE exits in the terminal regions of HBV RNA ( Fig . 7B ) . Interestingly , when the terminal redundancy ( TR , nt 1820–1918 ) was removed from either the 3′ ( pg-Δ3TR ) or 5′ ( pg-Δ5TR ) terminus of pgRNA , the truncated pgRNA was still vulnerable to ZAP-S ( Fig . 7C , comparing lane 2 to 1 , lane 6 to 5 , respectively ) ; however , with removal of both TR from pgRNA , ZAP-S no longer reduced the level of truncated pgRNA ( Fig . 7C , comparing lane 4 to3 ) , indicating that one copy of the terminal redundant sequences is sufficient to confer the susceptibility of HBV pgRNA to ZAP-mediated degradation . Thus , the HBV ZRE maps to the TR sequences of HBV RNA . To further confirm the functionality of the HBV ZRE , the TR region was inserted into the reporter plasmid EnII/Cp-Luc , either at the upstream ( EnII/Cp-TR-Luc ) or downstream ( EnII/Cp-Luc-TR ) non-coding region of the firefly luciferease mRNA within the multiple-cloning sites , or into both flanking regions ( EnII/Cp-TR-Luc-TR ) ( Fig . 8A ) . The plasmids were transfected into HepG2 cells individually , or cotransfected with plasmids expressing ZAP-S or ZAP-SΔ4ZFs , and luciferase activities were measured . As shown in Fig . 8B , insertion of HBV TR into the luciferase mRNA non-coding regions resulted in significant reduction of luciferase activity by ZAP-S expression , but not ZAP-SΔ4ZFs . Therefore , the HBV TR sequence and zinc finger motifs dependent RNA down-regulation by ZAP has been demonstrated . It has been reported that expression of the hZAP ( -L , -S ) mRNA occurs in a wide variety of tissues , including both germline and somatic cells [41] . To determine the protein expression profile of hZAP in hepatocyte-derived and other established cell lines , we tested hZAP antibodies from different commercial sources and obtained one with specificity for both hZAP-L and -S detection in Western blot assay . As shown in Fig . 9 , both transfected and endogenous ZAP isoforms were detected in a panel of cell lines tested in this study , including HeLa , 293T , hepatocyte-derived HepG2 and Huh7 cells ( Fig . 9A ) , and primary human hepatocytes ( PHH ) ( Fig . 9D ) . While HBV replication did not alter the expression levels of ZAP-L and -S in HepG2 and Huh7 cells ( Fig . 9B ) , the expression of ZAP-S , but not the -L isoform , was upregulated in these two cell lines and primary human hepatocytes under IFN-α treatment or IPS-1 expression ( Fig . 9C–D ) , suggesting that ZAP-S is an hepatic interferon stimulated gene ( ISG ) in response to the activation of cellular innate immunity . The preferential induction of ZAP-S by IFN-α or IPS-1 in hepatocytes is consistent with a recent report showing ZAP-S mRNA , rather than the full-length ZAP-L , was further induced by 5′-triphosphate-modified RNA in 293T cells [62] . We also found that ZAP-S mRNA was selectively induced in HepG2 cells upon IFN-α treatment or IPS-1 expression ( Fig . 9E ) , indicating a ZAP-S mRNA-specific splicing event . The mechanisms underlying differential regulation of the splicing of ZAP mRNA precursor by innate signaling remain unclear . Chronic hepatitis B is associated with inflammatory cytokine production upon the activation of host immunity , and the dynamic balance between host immune responses and virus replication is thought to determine the disease progression [21] , [22] . It is generally acknowledged that cytokine-induced intrahepatic genes play indispensable roles in controlling HBV replication [63]–[65] . To investigate the role of ZAP in chronic HBV infection , we analyzed the levels of ZAP mRNA in liver biopsy samples obtained from chronic hepatitis B patients . According to the natural history of HBV infection , those patients were grouped into three phases ( or types of immune responses ) , specifically immune tolerant phase , immune active phase , and inactive phase [66] ( Table S1 ) . As summarized in Fig . S4 , comparing to immune tolerant and inactive carriers , patients in the immune active group have significantly elevated expression levels of both ZAP-L and -S mRNA in liver , and the upregulation of ZAP-S mRNA is more remarkable than ZAP-L . Generally , HBV patients in immune active phase exhibit episodes of hepatitis over a period of months or years as the immune system attempts to clear the infection , resulting in the decline of viral loads [67] ( Table S1 ) . Thus , we speculate that the upregulation of ZAP may play a role in immune control of HBV replication in chronic infection . Host cells are able to sense viral components through an array of pattern recognition receptors ( PRRs ) , leading to the activation of innate cellular defense responses to combat virus infection [23] . We previously reported that activation of PRR-elicited innate immune signaling by ectopic expression of PRR-associated adaptor proteins , such as the adaptor of RIG-I-like helicases , IPS-1 ( also known as MAVS/Cardif/VISA ) [68]–[71] , significantly inhibited HBV replication in both HepG2 and Huh7 cells [53] . The primary IPS-1-mediated antiviral effect is to reduce the levels of HBV RNA and involves posttranscriptional mechanisms of viral RNA decay [53] . It is well known that the RIG-I/IPS-1 complex regulates host gene expression ( i . e . IFN-β ) through two major signal transduction cascades , the IRF3 and NF-κB pathways ( Fig . S5 ) [69] , [72] , [73] . In the previous study , we demonstrated that the inhibition of HBV replication by IPS-1 appears to be mediated by intracellular antiviral pathway ( s ) , rather than the secretion of antiviral cytokines such as IFN-α/β . Furthermore , we found that activation of the downstream NF-κB pathway , but not the IRF3 pathway , is essential for IPS-1-mediated HBV RNA reduction in HepG2 cells; whereas activation of both pathways is required for IPS-1 to destabilize HBV RNA in Huh7 cells [53] . The differential requirements of the IRF3 and NK-κB pathways by IPS-1-mediated HBV RNA reduction in HepG2 and Huh7 cells are shown in Fig . 10 ( Top panels ) . Considering that 1 ) IPS-1 induces ZAP-S expression in both cell lines ( Fig . 9 ) , 2 ) ZAP is capable of targeting HBV RNA for degradation ( Fig . 1 , 3 ) , and 3 ) the sequences responsible for IPS-1-mediated antiviral response were previously mapped within the approximately 1 kb region at the 3′ terminus of HBV RNA [53] , which contains HBV ZRE , we hypothesized that ZAP might be an end effector in the IPS-1-elicited anti-HBV state . To test this hypothesis , we first analyzed the dependency on IRF3 or NF-κB signaling of IPS-1-induced ZAP expression in hepatocyte-derived cells . As shown in Fig . 10 , IPS-1 expression led to an upregulation of ZAP-S in both HepG2 and Huh7 cells ( Fig . 10A/B , bottom panels , comparing lane 2 to 1 ) . While inhibition of IRF3 by dominant negative ( DN ) -IRF3 only blocked IPS-1-induced ZAP-S expression in Huh7 cells ( Fig . 10B , bottom panels , comparing lane 3 to 2 ) , antagonizing the NF-kB pathway by DN-IκBα attenuated IPS-1-mediated ZAP-S induction in both cell lines ( Fig . 10A/B , bottom panels , comparing lane 4 to 2 ) . Such differential dependency on IRF3 and NF-κB of IPS-1-regulated ZAP-S expression perfectly matches the cell type-dependent signaling pathway requirement for IPS-1-elicited HBV RNA reduction . We then attempted to knock down the cellular expression level of ZAP . The Huh7 line was selected for the knock down experiments because higher sequential transfection efficiency can be achieved in comparison to HepG2 cells . As shown in Fig . 11 , ZAP-specific siRNA reduced the basal levels of both ZAP-L and -S by more than 50% , together with a significant increase of HBV RNA expression ( Fig . 11A , comparing lane 2 to 1; Fig . 11B ) , suggesting that the basal level of ZAP is a robust host restriction factor for HBV . However , knock down of ZAP only partially attenuated the antiviral effect of IPS-1 , indicating that while ZAP plays a role in IPS-1-elicted HBV RNA reduction , additional IPS-1-induced host end-effectors with similar or distinct antiviral mechanisms against HBV RNA likely are required for IPS-1 to exert maximal antiviral activity . Serving as an intrinsic host antiviral factor , ZAP has been reported to inhibit the infection of a variety of RNA viruses , including MMLV , HIV-1 , XMRV , certain alphaviruses and filoviruses [37]–[39] , [42] , [43] . ZAP was initially identified in rat , and the conserved homologues have since been cloned from mouse , human and other primates [37] , [41] , [62] . The cross-species expression and broad tissue distribution of ZAP indicate that it has been evolutionarily preserved in mammals , suggesting a long history of active antiviral activities in host-pathogen interactions . However , ZAP is not a universal antiviral factor , as HSV-1 and yellow fever virus are resistant [38] . It had been speculated that ZAP exclusively antagonizes certain RNA viruses , until a recent report demonstrating that ZAP regulates murine gammaherpesvirus 68 latent infection by reducing viral M2 mRNA [47] . In this report , we demonstrated that ZAP inhibits the replication of HBV , a DNA pararetrovirus belonging to Hepadnaviridae family , primarily through down-regulation of viral mRNA . Our findings thus further expand the antiviral spectrum of ZAP and provide more information for a better understanding of ZAP biology . ZAP mediates an antiviral function through direct binding to viral RNA , resulting in RNA degradation . The RNA binding activity of ZAP is managed by the N-terminal portion of the protein , which contains four tandem CCCH-type zinc finger motifs [44] . Interestingly , the antiviral activity of rat ZAP was first discovered using a truncated ZAP protein ( r-NZAP ) , which consists only of the four zinc fingers that mediate RNA binding [37] . The human ortholog of ZAP ( hZAP ) gene encodes two protein isoforms that result from alternative splicing of a C-terminal poly ( ADP-ribose ) polymerase ( PARP ) -like domain , which is present in the longer ZAP isoform ( hZAP-L ) , but not the shorter version ( hZAP-S ) . However , both hZAP-L and -S have been shown to inhibit MMLV , Semliki Forest virus , HIV-1 [41] , [42] , and HBV ( this report ) , suggesting that the PARP domain is not essential to support the antiviral activity of ZAP . While the overall protein sequence homology between rZAP and hZAP is about 50% , their N-terminal portion of 254 a . a . share approximately 80% identity , and the four zinc-finger motifs are highly conserved [41] , [56] . In addition , we demonstrated that both rN-ZAP and its human 254 a . a . homolog ( hN-ZAP ) are able to reduce HBV RNA , which further confirmed that the N-terminus of ZAP is the functional antiviral domain . Among the four zinc finger motifs in the N-terminal portion of ZAP , the 2nd and 4th zinc fingers plays the major role in inhibition of MMLV by rat ZAP [44] . For HBV , we found that each of the four zinc fingers partially and equally contributes to hZAP-mediated viral RNA decay , and the integrity of all four zinc fingers is required for ZAP to achieve a maximal inhibition of HBV ( Fig . 5 ) . In addition , we demonstrated that ZAP is able to interact with HBV RNA in a co-immunoprecipitation assay , and disruption of the full set of zinc finger motifs completely abolished the binding of ZAP to HBV RNA ( Fig . 6 ) . Recently , the crystal structure of rN-ZAP has been solved [57] . The overall structure of rN-ZAP molecule resembles a “tractor-like” shape , with the four zinc finger motifs forming a large putative RNA-docking cleft comprised of two cavities . Further structural and functional analysis revealed that multiple positively-charged residues scattered in the CCCH-type zinc finger motifs also coordinately contribute to the formation of RNA-binding grooves . The structural complexity of the RNA-binding domain suggests that ZAP may bind to different target RNA slightly differently , and thus the contribution and requirement of each zinc finger motif may vary with the binding of different RNA substrates [57] . Previous mutagenesis and structure studies suggested that ZAP forms a homodimer for its RNA binding and antiviral activities , and the ZAP self-interacting domain largely overlaps with its antiviral zinc finger motifs [57] , [74] . In this report , we demonstrated that the nonfunctional hZAP mutant ( ZAP-SΔ4ZFs ) failed to bind HBV RNA ( Fig . 6 ) , and did not exhibit dominant-negative effect on endogenous or overexpressed wild-type ZAP ( Fig . 5D , Fig . S6 ) , favoring the notion that the zinc finger-mediated ZAP self-association is required for ZAP to directly target RNA for degradation . ZAP binds to specific viral RNA through the recognition of a so-called ZAP responsive element ( ZRE ) [44] , [46] . Among the ZREs previously mapped in viral RNA genomes , including MMLV , HIV-1 , XMRV , and certain alphaviruses and filoviruses , no obvious common RNA sequences or structural motifs could be identified , although they are all more than 500 nt long [39] , [42]–[44] , [46] . Herein , we mapped the HBV ZRE to the 100 nt terminal redundancy region ( nt 1820–1918 ) of HBV mRNA , which is present at both termini of viral pgRNA and at the 3′ end of viral subgenomic RNAs . The presence of a ZRE in the HBV genome further confirms that ZAP- mediated HBV RNA reduction is due to posttranscriptional regulatory mechanisms , similar to the reported antiviral mechanism of ZAP against other viruses . However , alignment of HBV ZRE with other individual viral ZREs did not reveal any obvious sequence homology ( data not shown ) , suggesting that a mysterious secondary or tertiary RNA structure may define the common feature of ZRE . A recent SELEX ( Systematic Evolution of Ligands by Exponential Enrichment ) study showed that ZAP-binding aptamers that were 40-nt-long G-rich RNAs with stem-loop structures containing conserved “GGGUGG” and “GAGGG” motifs in the loop region [75] . Interestingly , HBV ZRE contains a stem-loop region ( epsilon ( ε ) , nt 1849–1909 ) which serves as the pgRNA encapsidation signal and as the priming template for virus reverse transcription [6] , [7] , [76] . A sequence of “GGGUGG” ( nt 1888–1893 ) also exists , but , in the upper stem region of the epsilon ( Fig . S7 ) . The HBV TR structure and sequence partially match the proposed criteria of ZRE from the SELEX study . Our preliminary data showed that insertion of ε sequence alone at the 3′ nontranslationed region of the luciferase gene resulted in a significant reduction of luciferase activity when coexpressed with ZAP ( data not shown ) . Future investigations on HBV ZRE will focus on determining the minimal sequence or structural requirements and the key residues for a functional ZRE . Despite acting as a host antiviral factor , the other potential functions of ZAP in regulating host cellular function remain largely elusive . Since ZAP targets viral mRNA for destabilization , it is conceivable that ZAP may also alter the stability of certain cellular mRNA to regulate host gene expression . This notion is supported by previous observations that the mRNA level of the B3GALTL gene was significantly reduced by rNZAP overexpression in rat fibroblast cells [46] . In addition , considering ZAP favors short RNAs with stem-loop structures for affinity binding , it is also possible that ZAP potentially targets host microRNA ( miRNA ) precursors , including pri-miRNA and pre-miRNA with about 70 nt hairpin loop structures [77] , to regulate miRNA processing and maturation . This hypothesis can be investigated by host target prediction using homology searches with the identified viral ZRE sequences , or through microarray analysis of gene profiling after ZAP overexpression or knock down . A previous study reported that hZAP-S associates with RIG-I to stimulate IFN-β production through activation of IRF3 and NF-κB pathways in cell culture , suggesting hZAP-S is able to activate host innate defense machinery for virus inhibition [62] . To explore whether RIG-I signaling is involved in ZAP-mediated HBV RNA decay , we found that overexpression of ZAP-S had little ability to stimulate the IFN-β promoter activity in HepG2 cells ( Fig . S8A ) . Inhibition of IRF3 and NF-κB signaling did not restore the levels of HBV RNA under ZAP-S overexpression ( Fig . S8B ) , suggesting that ZAP-mediated HBV RNA reduction is not largely due to the stimulation of RIG-I pathway , which is consistent with a recent observation that knock down of RIG-I did not abrogate the inhibitory effect on XMRV by ZAP [43] . In contrast , ZAP-S expression can be further induced by activation of the RIG-I pathway through IPS-1 expression , and knock down of ZAP partially attenuated the antiviral activity of IPS-1 , thus indicating that ZAP is one of the contributing end-effectors in the innate control of HBV replication ( Figs . 9–11 ) . In addition , we observed that ZAP-S protein expression was further induced in primary human hepatocytes by IFN-α treatment ( Fig . 9D ) , and the levels of ZAP mRNA were elevated in the livers of hepatitis B patients during the immune active phase ( Fig . S4 ) , implying that ZAP may also play a role in host immune responses against HBV infection in vivo . ZAP does not encode any ribonuclease activity [46] . It has been reported that rat ZAP binds to the ZRE of MMLV RNA and recruits the host RNA processing exosome to degrade the viral RNA substrate from its 3′ end [45] . It is of interest to determine whether the exosome is involved in ZAP-mediated HBV RNA decay . However , our attempts to knock down the exosome subunits , such as EXOSC4 , have not been successful in hepatocyte-derived cells . Alternatively , a chemical inhibitor , Fluorouracil ( 5-FU ) , was employed to inhibit exosome activity in our study . The results showed that 5-FU treatment partially attenuated the viral RNA reduction under ZAP-S overexpression or IFN-α treatment , but only marginally increased the level of HBV RNA in the control group ( Fig . S9 ) . Although a possibility that the attenuated antiviral effect by exosome inhibition was due to a ZAP-independent mechanism could not be completely ruled out , the obvious antiviral attenuation by 5-FU under ZAP-S overexpression and IFN-α induction implied that the exosome activity might be required for ZAP-mediated HBV RNA decay . In fact , previous studies demonstrated that other host enzymes are recruited by ZAP to potentiate retroviral RNA degradation , including RNA helicase p72 and DHX30 for restructuring RNA , polyA ribonuclease ( PARN ) for trimming the polyA tail of mRNA , and cellular decapping complex for initiating the degradation of the target viral mRNA from the 5′ end [42] , [46] , [78] , [79] . Interestingly , HBV ZRE localizes in close proximity to both termini of pgRNA and to the 3′ end of subgenomic RNA , which it may efficiently direct ZAP and its partners to the RNA degradation initiation sites . Whether those co-factors are involved in ZAP-mediated HBV RNA degradation in heptocytes awaits further investigation . It also has been reported that ZAP works in concert with other ISGs to confer maximal protection against virus infection upon IFN treatment [40] , [49] . Rat ZAP-synergistic ISGs for alphavirus inhibition have been identified recently [61] . In our previous work on screening of antiviral ISGs for HBV inhibition , a handful of ISGs that reduce the steady state level of HBV RNA have been identified [31] . Among them , interferon-stimulated gene 20 kDa protein ( ISG20 ) is an exoribonuclease that down-regulates HBV RNA in a posttranscriptional fashion similar to ZAP ( Nie and Guo , unpublished data ) . The detailed molecular mechanisms of ISG20-mediated HBV RNA decay , and its potential synergistic activity on ZAP's anti-HBV function , are currently under way . Taken together , the work reported herein has identified ZAP as a host restriction factor that limits HBV replication . Mechanistic studies of the inhibitory effect of ZAP on HBV replication have important implications for a better understanding of virus-host interaction , host antiviral immunity , and viral pathogenesis during HBV infection . Considering the importance of HBV RNA in the virus life cycle , degradation of viral RNA will result in a dramatic suppression of viral DNA replication and antigen production . Therefore , ZAP-mediated HBV RNA decay can be potentially utilized to develop novel antiviral strategies against HBV through gene delivery of ZAP expression vectors into HBV infected cells . It is also envisaged that small molecules could be discovered to mimic the antiviral function of ZAP , or provoke its antiviral activity , to achieve a beneficial therapeutic value for the management of chronic hepatitis B . All human subjects were recruited with informed written consent . The study was approved by the Institutional Ethics Committee for human studies at Huashan Hospital , Fudan University . All clinical investigations have been conducted according to the principles expressed in the Declaration of Helsinki . Liver biopsies were obtained from 24 hepatitis B patients enrolled in this study ( Table S1 ) . Total mRNA was isolated from liver specimens and the gene expression profiling was performed by using Affymetrix Human U133 Plus 2 arrays at Ebioservice , Inc ( Shanghai , China ) . Microarray data were analyzed using GeneSpring GX 10 ( Agilent ) . The complete microarray dataset will be published separately . In this report , the ZAP gene ( ZAP-L , -S ) expression data are expressed as log2 values with mean ± SD using Graphpad prism 5 . 0 software , a p-value<0 . 05 ( t-test ) is considered significant . Human hepatocyte-derived HepG2 and Huh7 cells and human embryonic kidney 293T cells were obtained from the ATCC and maintained in DMEM/F12 medium ( Mediatech ) supplemented with 10% fetal bovine serum , 100 U/ml penicillin and 100 µg/ml streptomycin . HepDES19 cells were maintained in the same way as HepG2 , but with the addition of 1 µg/ml tetracycline and 400 µg/ml G418 [80] . To initiate HBV replication in HepDES19 cells , tetracycline was withdrawn from the culture medium and the cells were cultured for the indicated time . Cryopreserved primary human hepatocytes were obtained from Triangle Research Labs , LLC ( Research Triangle Park , NC ) ; cells were recovered and cultured according to supplier's protocol . Recombinant human IFN-α2a was purchased from PBL Biomedical Laboratories . 5-fluorouracil ( 5-FU ) , an exosome inhibitor , was purchased from Sigma-Aldrich and dissolved in DMSO ( 10 µg/ml stock ) . HBV ( genotype D , subtype ayw , Genbank accession number V01460 . 1 ) replication competent plasmids , pHBV1 . 3 and pCMVHBV , in which the transcription of viral pgRNA is governed by authentic HBV core promoter and CMV-IE promoter , respectively , were described previously [31] , [53] , [81] . HBV pgRNA internal deletion clones ( pgID-1 to pgID14 ) were constructed on the pHBV1 . 3 backbone by PCR . Plasmids expressing the terminal redundancy ( TR , nt 1820–1918 ) truncated viral pgRNA were obtained by insertion of TR-absent ( either 5′ or 3′ TR , or both ) HBV pgRNA coding sequence into pCDNA3 . 1/V5-His-TOPO vector ( Life Technologies ) ( refer to Fig . 7A for schematic illustration ) . Plasmids pE and pS that encode HBV 2 . 4 kb and 2 . 1 kb mRNA for the expression of HBV envelope proteins were kindly provided by Dr . Volker Bruss ( Institute of Virology , Helmholtz Zentrum München , Germany ) [82] . To construct an HBV core promoter ( Cp ) reporter plasmid , a fragment covering the HBV enhancer II ( EnII ) and Cp region ( nt 1400–1820 ) was PCR amplified from plasmid pHBV1 . 3 and inserted into the SacI and HindIII restriction sites in pGL3-Basic vector ( Promega ) . The generated plasmid was designated EnII/Cp-Luc , in which expression of the firefly luciferase reporter gene is governed by the HBV core promoter . Reporter plasmid EnII/Cp-TR-Luc was constructed by inserting an HBV DNA fragment spanning the viral EnII/Cp region and 5′ TR ( nt 1390–1932 ) into the SacI/HindIII restriction sites in pGL3-Basic vector . Reporter plasmid EnII/Cp-Luc-TR bears TR-containing sequence insertion ( nt 1804–1930 ) at the XbaI/FseI site in plasmid EnII/Cp-Luc . Similarly , XbaI/FseI restricted TR-containing fragment ( nt 1804–1930 ) was implanted into the same restriction site in EnII/Cp-TR-Luc to generate EnII/Cp-TR-Luc-TR . HBV surface promoter reporter plasmids , namely S1-Luc and S2-Luc , were engineered through insertion of HBV DNA fragments containing S1 ( nt 2708–2809 ) and S2 ( nt 2906–3160 ) promoter region into the SacI and HindIII restriction sites in pGL3-Basic , respectively . CMV-IE promoter Renilla luciferase reporter plasmid pRL-CMV was purchased from Promega . pcDNA4-derived plasmids expressing the N-terminal 254 a . a . zinc-finger motif domain of rat ZAP ( rN-ZAP ) and full-length human ZAP isomers ( hZAP-L , hZAP-S ) were described previously and kindly provided by Dr . Malik Harmit ( Fred Hutchinson Cancer Research Center ) [41] . The N-terminal 254 a . a . coding region of hZAP was PCR amplified and cloned into pcDNA4 ( Life Technologies ) to generate plasmid hN-ZAP . Disruption of the individual or all the four putative zinc finger motifs in hZAP-S was carried out according to the previous report by using QuikChange II Site-Directed Mutagenesis Kit ( Agilent ) [44] . All of the above wildtype and mutant ZAP genes have an N-terminal HA-tag sequence in the expression vectors . The plasmids expressing the dominant-negative IRF3 ( DN-IRF3 ) and dominant negative IκB-alpha ( DN-IκBα ) were described previously [53] . IFN-β1 promoter luciferase reporter plasmid ( IFN-β1-Luc ) was a gift from Dr . Hong-Bing Shu ( Wuhan University ) . Cells ( ∼1 . 2×106 ) were seeded in a collagen coated 35-mm-diameter dish in antibiotics-free DMEM/F12 medium . After 6 hours , each well was transfected with a total of 4 µg plasmids with Lipofectamine 2000 ( Life Technologies ) by following the manufacturer's directions . Transfected cells were harvested at the indicated time points . The HepG2 cells ( ∼1×104 ) were transfected with promoter reporter plasmid plus vectors expressing gene of interest using Lipofectamine 2000 . For each transfection , empty control plasmid was added to ensure that each transfection receives the same amount of total DNA ( 200 ng ) . To normalize for transfection efficiency , 4 ng of pRL-CMV Renilla luciferase reporter plasmid was added to each transfection . Three days after transfection , cells were harvested and lysed . Luciferase activities in cell lysates were assayed using a dual luciferase assay system ( Promega ) and measured by TopCount NXT . Relative firefly luciferase activities were normalized based on Renilla luciferase activities . Intracellular HBV core DNA and total cellular RNA were extracted as described previously [53] , [80] . For Core DNA analysis , one third of the DNA sample from each plate was resolved by electrophoresis into a 1 . 5% agarose gel and blotted onto Hybond-XL membrane ( GE Healthcare ) . For RNA Northern blot analysis , ten microgram of total cellular RNA was resolved in 1 . 5% agarose gel containing 2 . 2 M formaldehyde and transferred onto Hybond-XL membrane . Membranes were probed with either α-32P-UTP ( 800 Ci/mmol , Perkin Elmer ) labeled minus or plus strand specific full-length HBV riboprobe and exposed to a phosphorimager screen . Hybridization signals were quantified with QuantityOne software ( Bio-Rad ) . Cells in 35 mm dish were washed once with PBS buffer and lysed in 300 µl of 1× Laemmli buffer . Thirty microliters of the cell lysate was resolved on a 10% SDS-PAGE and proteins were transferred onto Immobilon PVDF-FL membrane ( Millipore ) . The membranes were blocked with Western Breeze blocking buffer ( Life Technologies ) and probed with antibodies against HA-tag ( Covance , clone 16B12 ) , hZAP ( Proteintech Group , Inc ) , EXOSC4 ( Santa Cruz ) or β-actin ( Millipore ) . Bound antibodies were revealed by IRDye secondary antibodies . The immunoblot signals were visualized and quantified with the Li-COR Odyssey system . For protein analysis , the cytoplasmic and nuclear fractions of HepG2 cells were separated using the Qproteome Cell Compartment Kit ( QIAgen ) by following the manufacturer's directions . The purity of cytoplasmic and nuclear fractions was confirmed by measuring cytoplasmic and nuclear specific protein markers ( Annexin I and Lamin A/C , respectively ) with Western blot assay by following the manufacturer's procedures . For RNA analysis , cytoplasmic and nuclear RNA were isolated and purified by Cytoplasmic & Nuclear RNA Purification Kit ( Norgen ) . RNA samples were subjected to Northern blot assay for HBV RNA detection as described above . HepG2 cells were transfected with ZAP-S for 48 h and followed by fixation with 2% paraformaldehyde and permeablization of the cell membrane with 0 . 1% Triton X-100 . Cells were then immunostained with anti-HA antibodies ( Covance , clone 16B12 ) and the bound antibodies were visualized by Alexa Fluor 488 goat anti-mouse IgG ( Life Technologies ) . Nuclei were counterstained with DAPI . Cells were imaged with a Nikon fluorescent microscope and photographed with a charge-coupled device camera . HepG2 cells were cotransfected with pCMVHBV and control vector , or HA-tagged wildtype or mutant ZAP-S . In order to obtain easily detectable levels of HBV RNA and ZAP , the ratio between input HBV plasmid and ZAP expression vector was optimized to 3∶1 , and the transfection was maintained for 3 days . The harvested cells were lysed on ice with cell lysis buffer containing 1% NP-40 , 10 mM Tris . HCl ( pH 7 . 5 ) , 1 mM EDTA , 50 mM NaCl , 8% sucrose , and 1 U/µl of RNasin Plus RNase Inhibitor ( Promega ) . After centrifugation to remove the cell debris , the clarified cell lysates were incubated with EZview Red Anti-HA or Anti-FLAG Affinity Gel ( Sigma-Aldrich ) at 4°C for 2 h with gentle rotation . The beads were spun down and resuspended with rinse buffer ( 10 mM Tris . HCl ( pH 7 . 5 ) , 1 mM EDTA , 50 mM NaCl , 10 µM ZnCl2 , and 1 U/µl of RNasin Plus RNase Inhibitor ) for three times at 4°C . The pelleted beads were subjected to RNA extraction with TRIzol , and protein sample preparation with Laemmli buffer . Immunoprecipitated ZAP protein and HBV RNA were analyzed by Western blot and Northern blot assays , respectively . DNase I-treated total cellular RNA was used to generate cDNA by SuperScript III Reverse Transcriptase ( Life Technologies ) . Real-time PCR was performed with SYBR Green Master ( Roche ) and the LightCycler 480 System ( Roche ) by using ZAP-L and -S specific primers [62] . The gene expression data were normalized to GAPDH from the same samples . Control siRNA ( Cat . sc-37007 ) and hZAP siRNA ( Cat . sc-89362 ) were purchased from Santa Cruz Biotechnology , Inc . ZAP siRNA is a pool of 3 target-specific 19–25 nt siRNAs designed to knock down the expression of both ZAP isoforms . siRNA transfection was performed by Lipofectamine 2000 according to manufacturer's directions . HBV genomic DNA ( genotype D , subtype ayw ) : V01460 . 1; human ZAP-L: NM_020119 . 3; human ZAP-S: NM_024625 . 3; rat ZAP: AF521008 . 1; IPS-1: NM_020746 . 4 .
The dynamics of virus and host interaction greatly influence viral pathogenesis , and host cells have evolved multiple mechanisms to inhibit viral replication . Since it was first discovered as a cellular restriction factor for retroviruses , the host-encoded zinc finger antiviral protein ( ZAP ) has been shown to antagonize a variety of viral species , possibly through a common mechanism by which ZAP targets viral RNA for degradation . Here we report that hepatitis B virus ( HBV ) is also vulnerable to ZAP-mediated viral RNA reduction . ZAP is able to interact with HBV RNA through its zinc finger motifs , and the ZAP-responsive element which determines ZAP's antiviral specificity and activity is located within the 100-nucleotide-long terminal redundant region in the viral RNA genome . While the replication of HBV is constitutively restricted under the basal expression of intrahepatic ZAP , activation of host innate defenses , and potentially the acquired immune responses as well , could further elevate ZAP expression to suppress HBV replication . Therefore , our study not only expands the antiviral spectrum of ZAP , but also provides cumulative and novel information for a better understanding of ZAP biology and antiviral mechanisms . We also envision that the endogenous or engineered ZAP could be utilized in the future for development of therapeutic means to treat chronic hepatitis B , which currently affects more than 5% of the world's population .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "infectious", "hepatitis", "hepatitis", "b", "immunity", "gastroenterology", "and", "hepatology", "virology", "innate", "immunity", "host-pathogen", "interaction", "biology", "microbiology", "liver", "diseases" ]
2013
Inhibition of Hepatitis B Virus Replication by the Host Zinc Finger Antiviral Protein
The metabolic phenotype of cancer cells is reflected by the metabolites they consume and by the byproducts they release . Here , we use quantitative , extracellular metabolomic data of the NCI-60 panel and a novel computational method to generate 120 condition-specific cancer cell line metabolic models . These condition-specific cancer models used distinct metabolic strategies to generate energy and cofactors . The analysis of the models’ capability to deal with environmental perturbations revealed three oxotypes , differing in the range of allowable oxygen uptake rates . Interestingly , models based on metabolomic profiles of melanoma cells were distinguished from other models through their low oxygen uptake rates , which were associated with a glycolytic phenotype . A subset of the melanoma cell models required reductive carboxylation . The analysis of protein and RNA expression levels from the Human Protein Atlas showed that IDH2 , which was an essential gene in the melanoma models , but not IDH1 protein , was detected in normal skin cell types and melanoma . Moreover , the von Hippel-Lindau tumor suppressor ( VHL ) protein , whose loss is associated with non-hypoxic HIF-stabilization , reductive carboxylation , and promotion of glycolysis , was uniformly absent in melanoma . Thus , the experimental data supported the predicted role of IDH2 and the absence of VHL protein supported the glycolytic and low oxygen phenotype predicted for melanoma . Taken together , our approach of integrating extracellular metabolomic data with metabolic modeling and the combination of different network interrogation methods allowed insights into the metabolism of cells . Aerobic glycolysis indicates the incomplete oxidation of glucose to lactate under normoxic conditions [1] and has been a focus of cancer research in recent decades [2] . However , cancer cells are increasingly thought to employ heterogeneous metabolic strategies beyond aerobic glycolysis [3–6] . Many cancer cells generate substantial amounts of energy through mitochondrial oxidative phosphorylation [2 , 7 , 8] . Moreover , cancer cells use additional fuels , such as glutamine and fatty acids , to support proliferation [3 , 9] . These carbon sources can be used in different ways , e . g . , different parts of the tricarboxylic acid ( TCA ) cycle can be employed for glutaminolysis [5 , 8 , 10 , 11] . Reductive carboxylation involves only two TCA cycle reactions that run in reverse direction without producing energy , whereas glutaminolysis in the forward direction does yield energy [5 , 8 , 11] . In addition to various metabolic strategies , cancer cells display robustness towards environmental changes , such as , nutrient supply or oxygenation [12–14] . Even though these differences in metabolic phenotypes are known to exist , the variance in the metabolism of cancer cell lines has not been exhaustively analyzed using extracellular metabolomic data . Liquid chromatography-tandem mass spectrometry ( LC-MS ) was used to determine the metabolites that were consumed and released by the cancer cell lines included in the NCI-60 panel of the National Cancer Institute’s ( NCI’s ) Developmental Therapeutics Program ( DTP; http://dtp . nci . nih . gov ) [15] . By combining the obtained metabolomic profiles with doubling times and transcriptomic data , rapid proliferation was associated with cellular glycine requirements [15] . However , most of the intracellular pathways that gave rise to distinct metabolomic profiles remained undetermined . Metabolism can be investigated using constraint-based modeling [16 , 17] , which involves the application of physico-chemical principles and often assumes the system to be in a steady-state [16] . Limitations on metabolite uptake and secretion rates can be added to the model to increase the precision of the predictions by eliminating network states that exceed these constraints [18] . A reconstruction of the human metabolism is readily available [19 , 20] , and numerous analytical methods are used to investigate the metabolic differences that arise due to the imposed constraints [21 , 22] . Metabolomic data derived from body fluids and cell culture supernatant have previously been integrated with metabolic reconstructions [7 , 23 , 24] . One existing challenge in the integration of extracellular metabolomic data is incomplete data . Analytical techniques identify only a subset of the metabolome due to the chemical diversity among small molecules and because the analysis is often a priori limited to a defined set of targeted metabolites [25] . Hence , the information on which substrates are taken up by the cells is incomplete . Similarly , the management of data derived from cells grown in serum is difficult because the quantitative and qualitative composition of the serum is unknown . However , the quality of computational predictions depends on the extent to which a model’s solution space can be reduced by integrating available data . Ideally , only biologically relevant network states would remain to be investigated [18] . Novel approaches are necessary to overcome these difficulties and enable the rapid classification of metabolic phenotypes based on metabolomic profiles . Such approaches could have a broad impact on many biological fields including biomedicine . We developed a novel method termed minExCard to complete the uptake and secretion profile , by predicting a minimal set of metabolite exchanges in addition to the ones measured , to complete the metabolome . We applied the method to the comprehensive targeted extracellular metabolomic data set from Jain et al . , which was generated from the NCI-60 cell lines grown in medium enriched with serum [15] . Using minExCard we generated 120 condition-specific models from extracellular metabolomic data . Our models utilized different biochemical routes to supply the cells with energy and were distinctively affected by network perturbations . We distinguished different oxotypes based on the range of allowable oxygen uptake rates . We identified a distinctive tissue pattern for melanoma cell lines that was supported by protein and RNA expression levels from melanoma cell lines and primary melanoma . This work demonstrates how analysis of extracellular metabolomic data in the metabolic model context , and the combination of multiple analysis strategies , can lead to unprecedented insight into cell metabolism . Published metabolomic profiles comprising the uptake and secretion of metabolites from and into the culture medium were integrated with the metabolic model ( Fig 1A ) [15] . The metabolomic data consisted of two samples per cell line . Because there was considerable variation between samples ( Fig A in S1 Text ) , we generated one condition-specific cell line model for each sample rather than averaging the data for each cell line . The metabolome is dynamic and constitutes a snap-shot of the phenotype elicited by the cultivated cells over the duration of the experiment and under a specific set of environmental conditions . We refer to the models as condition-specific since they are tailored only according to the metabolomic profiles . Generic cell-line specific models would need to be generated from data sets of different experimental conditions and the existing literature for the same cell line , to ensure that it can carry out all the functions observed for these cells under any set of environmental conditions . To generate a condition-specific model , the global model was constrained using the metabolite uptake and secretion rates measured for the respective samples . Next , a minimal set of , on average 17 ± 3 , exchange reactions needed to sustain a minimal growth phenotype ( Vbiomass , min = 0 , 008 U ) together with the imposed uptake and secretion rates were identified based on the model structure by minimizing the number of exchange reactions ( using minExCard ) . An analysis of the expression of genes associated with the metabolites additionally required in the MCF-7 models ( which required the highest number of added exchange reactions ) , revealed that extracellular transport and metabolism of these added metabolites could indeed appear in MCF-7 cells ( see S1 Text , S1A Table , [26] ) . However , the gene expression data was only used to validate the added exchanges , but not for the generation of the condition-specific models since the transcriptomic data originated from a different experiment than the metabolomic data . All other metabolite exchanges and internal reactions that were no longer used by the model were removed to produce an individual condition-specific cell line model for each sample ( Fig 1A ) . The 120 models differed with respect to the numbers of reactions , metabolites , and genes ( Fig 1B and 1C , Fig B in S1 Text ) . Many of the models could substantially exceed the maximally possible growth rates expected for any human cell ( S1B Table ) . The capability of the models to grow at realistic rates was analyzed by applying constraints on the biomass objective function based on reported growth rates ( +/-20% ) for the individual cell lines , and flux balance analysis revealed whether the model remained feasible with these constraint . Only 14 models were infeasible when constrained using the experimental growth rates ( see S1 Text , S1C Table ) because the feasible range of flux rates through the biomass reactions exceeded or did not reach up to the experimental growth rates , even when assuming a 20% error range . ACHN-2 and UACC-257 were limited to experimental growth rates just by the metabolite uptake and secretion profile and the minimal growth constraint ( S1 Text , S1B and S1D Table ) . Considering a lower error of 5% or constraining both upper and lower bound to the growth rate , the ACHN-2 model became infeasible ( S1D Table ) . The predicted growth rates for the HCT-116 models using sampling Vmedian , biomass = 0 . 038 U , corresponding to a doubling time of 18 . 2 hrs , deviated at most 7% from the growth rate reported by Jain et al . and others ( S1D Table , [15 , 27] ) . Taken together , the diversity of the models and their ability to predict realistic growth rates suggested that they were a good starting point to investigate metabolic heterogeneity between the cell lines . Metabolic strategies yield different amounts of ATP , e . g . , full oxidation of glucose to CO2 can yield 32 ATP and aerobic glycolysis can yield two ATP [28 , 29] . Herein , we used the ATP yield as an estimator for distinct pathway utilization . For this analysis , we divided the sum of flux through all reactions in the model that produced ATP by the individual glucose uptake . There was a large range of ATP yields across the models ( Fig 2A , ATP yield: min = 2 . 92 , max = 55 . 27 , S1B Table ) that exceeded the theoretical measure for aerobic glycolysis . An exact fit with the theoretical ATP yields was not expected because the models could use all substrates as defined by the uptake profile and ATP-producing reactions present in the condition-specific model and not only glucose ( Fig A in S1 Text ) . As a sanity check , we tested for maximum ATP hydrolysis flux from only O2 and glucose as carbon source . ATP hydrolysis flux from glucose did not exceed the theoretical measures [28 , 29] in any of the 120 cancer models ( S1E Table ) . Upper bounds on exchange reactions were opened for the sanity check . Rank-ordered ATP yields nearly continuously increased and were occasionally interrupted between groups of models ( Fig 2A , Fig C in S1 Text ) . One interruption was associated with the switch of the major ATP-producing reaction . Models with an ATP yield < 4 . 21 ( ’glycolytic’ models , n = 38 , Fig 2A ) produced the highest fraction of ATP through phosphoglycerate kinase ( PGK ) . In contrast , models with an ATP yield > 7 . 26 produced ATP primarily via ATP synthase ( ’OxPhos’ models , n = 82 , Fig 2A ) . Thus , the ATP yield and ATP production strategy divided the models into glycolytic and OxPhos phenotypes . The distinction of the models was significantly associated with the ratios of glucose uptake to lactate secretion ( ttest , p< 0 . 01 ) , and glucose uptake to glutamine uptake ( ttest , p< 0 . 0002 ) . Taken together , the distinction of the glycolytic and the OxPhos models emerged from the ratios of fluxes of metabolites , which are associated with the observed Warburg phenotype and , which were imposed on the models as individual flux constraints . Consideration of differences in the utilization of the TCA cycle , i . e . , ATP production of succinate-CoA ligase , enabled the further identification of two OxPhos subtypes ( Fig D in S1 Text ) . This division was not obvious according to ATP yield ( Fig E in S1 Text ) . In addition to ATP , cells need cofactors to support proliferation . Distinct strategies used in the models produced different cofactors and enabled the division of glycolytic models into two subtypes ( Fig 2B and 2C , S1F–S1J Table ) . The two OxPhos subtypes were further subdivided into a total of six subtypes ( Fig 2B and 2C , S1J Table ) . The glycolytic subtypes differed only in the major FADH2-producing reaction ( Fig 2B , I and II ) . Two OxPhos subtypes were associated with high TCA cycle contribution to ATP production , which was associated with a high utilization of cytosolic malic enzyme as a leading NADPH source ( Fig 2B , IV and VII ) . The four remaining OxPhos subtypes predominantly used either isocitrate dehydrogenase ( IDH , Fig 2B , V and VIII ) or dihydroceramide desaturase ( Fig 2B , III and VI ) for NADPH production . Glyceraldehyde-3-phosphate dehydrogenase was the primary NADH producer in OxPhos models with relatively more glycolysis-based ATP production , whereas 2-oxoglutarate dehydrogenase was favored in models with a higher contribution of ATP synthase ( Fig 2C ) . Thus , the predicted strategies for cofactor production enabled further refinement for the classification of glycolytic and OxPhos models . Thus far , we stratified the models based on the imposed constraints and the distinct use of central metabolic pathways . In the following , we predict the behavior of each model towards environmental and genetic perturbations . Fluctuations of nutrients and oxygen supply during transformation shape the individual metabolic network and may influence the robustness of cancer cells towards environmental changes [30] . Variations of glucose uptake , glutamine uptake , oxygen uptake , and lactate secretion ( phenotypic phase plane analysis ( PhPP ) ) led to two major observations [31] . First , the size and form of the solution spaces varied across models ( Fig 3 ) . Using the form and size of the solution spaces as visual clues ( Fig G in S1 Text ) , we divided the models into six distinct clusters ( Figs 2E and 3 , S1K Table , S1 Text ) . Second , the solution space , which contains all possible network states and which was defined by variations in oxygen uptake , divided the models into three groups ( Fig 2D ) ( i ) Glycolytic models could only grow at low oxygen uptake rates ( Figs 2D and 3 cluster 4 ) . The group of OxPhos models comprised ( ii ) models growing only at high oxygen uptake rates ( Figs 2D and 3 cluster 1–3 ) and ( iii ) models that were indifferent with respect to oxygen uptake rates ( Figs 2D and 3 cluster 5–6 ) . The latter two groups provided a separation of the OxPhos models that was distinct from the previous analysis . Thus , the models could be further divided according to their robustness towards oxygen uptake . In silico gene knock-outs can predict novel drug targets [32] . Single gene deletion of 1215 unique human genes ( all isozymes of one gene were constrained to zero at once ) was performed for each of the 120 models . The number of essential genes varied across models ( min = 132 , max = 272 , S1B Table ) and was not associated with any phenotype . A total of 55 genes were essential to all models and could constitute metabolic targets for all previously defined phenotypes ( S1L Table ) . These numbers of essential genes predicted by our models were higher compared to those predicted for generic cell-or tissue specific models . This was caused by the vast reduction of exchange reactions and fixed uptake and secretion fluxes , which prevented that upon a gene knock-out , the models could switch to using different metabolic fuels or pathways connected to changes in gene expression . The flux ranges and the direction of flux of the exchange reactions were fixed , causing any reaction that was linked to the exchanges to become essential for the model . Whether a gene was essential under changing environmental conditions and whether cells in vivo could evade the effect by changing the metabolic pathways used to generate energy , cannot be answered by our models . However , models build from transcriptomic data could be used instead . Such models have previously revealed the switch to pathways requiring higher oxygen uptake when glycolytic enzymes were inhibited [33] . However , the condition-specific models , which are ‘frozen’ to the metabolic properties elicited at the time , highlight inhibition of which genes necessitate changes in metabolic flux and changes in gene expression . Cancer cells use the TCA cycle in different ways [5 , 8] . Reductive carboxylation involves the TCA cycle reactions isocitrate dehydrogenase and aconitase , and occurs in the mitochondria or the cytosol . The gene IDH1 encodes the cytosolic isocitrate dehydrogenase and the gene IDH2 encodes the mitochondrial isocitrate dehydrogenase . Interestingly , in silico IDH2 knock-out terminated growth in four models ( SK-MEL-28 , SK-MEL-28-2 , MALME-3-2 , and BT-549 ) and reduced growth in 12 additional models . A flux variability analysis ( FVA ) revealed that the four models had to employ reductive carboxylation ( S1M Table [34] , whereas this pathway remained optional for the other models even when constrained to experimental growth rates ( S1D Table ) . In agreement with an observed increase in reductive carboxylation under hypoxic conditions [5] , a reduction of the oxygen uptake rate ( lb = ub = −100 fmol/cell/hr ) rendered 14 additional models dependent on reductive carboxylation ( S1M Table ) . Fifteen models , including the four reductive carboxylation models , belonged to PhPP cluster 4 , which was characterized by a heavily constricted solution space at low oxygen uptake rates compared with , e . g . , the cluster 4C models ( Fig 3 ) . The remainder belonged to cluster 1B . Our models were therefore not only able to predict reductive carboxylation but also able to further reproduce the co-occurrence of low oxygenation and reductive carboxylation in cancer cell lines . Phosphoglycerate dehydrogenase ( PHGDH ) was another essential gene shared among the four models with obligate reductive carboxylation . Interestingly , SK-MEL-28 and MALME-3M had previously been associated with amplifications of PGDH due to 1p12 gain [4 , 35] . The correct prediction of the dependency of SK-MEL-28 and MALME-3M on PHGDH provides additional support for the presented approach and for the predicted dependency of SK-MEL-28 on reductive carboxylation . Because the oxotype played an essential role in determining the phenotype and because tissues are known to be differentially oxygenated [36] , we questioned whether tissue origin impacted the oxotype of the cancer . In total , 49 cell line model pairs had the same oxotype ( Fig 4 ) . Breast , colon , and non-small cell lung cancer models were spread across oxotypes . Leukemia , prostate , renal , and CNS cell line models predominantly depended on high oxygen uptake rates . In contrast , melanoma cell lines were clearly separated from the other cell lines by predominantly relying on low oxygen uptake rates ( Fig 4 ) . Thus , the oxotypes enabled us to distinguish melanoma cell lines from other cancer cell lines . Most melanoma models were predicted to be glycolytic and having a low oxotype ( Fig 4 , S1J and S1K Table ) . A reverse flux through the TCA cycle was essential for a small subset of melanoma models without additional constraints limiting the oxygen uptake . To validate that melanomas indeed use the mitochondrial isocitrate dehydrogenase , we analyzed protein abundance and RNA expression data from the Human Protein Atlas [37] . IDH1 protein abundance was low or not detectable in normal skin cell types ( hypergeometric p ( x = 5 ) = 0 . 047 , Table 1 , 1 ) , skin cancer , and melanoma . In comparison , IDH2 protein levels were medium in normal skin cell types ( hypergeometric p ( x = 5 ) = 0 . 006 , Table 1 , 2 ) and detected in more than 50% of the skin cancers and melanomas ( Table 1 ) . Thus , the data supported a prevalence of IDH2 for normal skin cell types , skin cancers , and melanoma at the protein level . Reductive carboxylation has been associated with the loss of the von Hippel-Lindau tumor suppressor ( VHL ) in renal cancer cell lines [38] . HIF1α protein is no longer degraded , which is associated with the expression of glucose transporters and glycolytic enzymes [39 , 40] . Since the process of HIF stabilization is connected to hypoxia , this process has also been referred to as pseudo-hypoxia [5] . To validate the predicted glycolytic phenotype and the low ‘oxotype’ , we analyzed HIF1α and VHL protein , and RNA levels . HIF1α protein abundance was low in normal skin tissue ( hypergeometric p ( x = 5 ) = 0 . 019 , Table 1 , 3 ) and low or medium in the majority of skin cancers and melanomas ( Table 1 ) . HIF1α RNA expression was overall high in human melanoma and epidermoid carcinoma cell lines ( Table 2 ) . The VHL protein detection was unreliable in all normal skin cell types ( Table 1 ) . Interestingly , VHL protein was not detected in skin cancers or in melanomas ( Table 1 ) . The absence of VHL was even more distinctive in skin cancers as compared to renal cancers where VHL levels were medium or high in 7 out of 12 patient samples ( Table 1 ) . Moreover , RNA expression was low in two melanoma cell lines , an epidermoid carcinoma , an immortalized normal keratinocyte cell lines ( hypergeometric p ( x = 4 ) = 0 . 044 , Table 2 , 1 ) , and A549 cells , which were predicted to be low oxotype ( Table 2 ) . Hence , the lack of VHL emerged as a prominent feature of normal skin and melanoma . We opted to build our models solely from metabolomic data , without consideration of the genotypic and other omics data , to evaluate whether such models could provide novel biological insights . This approach was particularly interesting for connecting the melanoma cell lines with the reverse flux through the IDH2 and psydohypoxia [5] . However , when only constrained based on the metabolomic data , our 786-O models predicted net reductive carboxylation was optional , which stood in contrast to net reverse flux observed for these cells . Limiting the oxygen uptake in the models to the minimum emphasized the reverse flux in the TCA cycle . Overall , this highlights that oxygen consumption in an experiment determines the observable metabolic phenotype , in addition to the growth medium composition ( or environmental condition ) . Addition of , e . g . , transcriptomic data could further define the phenotype [62] . There is no shortage in transcriptomic data for the NCI-60 cell lines . However , since the models build herein are condition-specific , the data used should originate from the same experiment to resemble the metabolic phenotype displayed in the experiment . The presented computational modeling approach is applicable to many cellular systems and represents a valuable starting point to investigate metabolic strategies of individual cell lines as well as to envision clinical applications . Further development of this approach could help realize personalized clinical applications utilizing metabolomic data . Immortalized cell lines , such as the NCI-60 cell lines , have a limited clinical relevance since they are monoclonal and accumulate mutations due to the high passage numbers [63] . One way to increase the clinical relevance of our work would be to extend the presented work to omics data generated from patient-derived primary tumor cells . Methods exist to cultivate primary tumor cells , or selected sub-populations of the same , e . g . , tumor-initiating stem cells; and to retain phenotype and genotypes using tissue-specific supplements and environmental conditions [63] . Extracellular metabolomic data or multiple omics data derived from such personalized cell cultures could then be used in conjunction with the presented approach to gain a better understanding of an individual’s cancer , and to predict appropriate treatment strategies . The global model constitutes a subset of Recon 2 [20] . This subset is the same as that used in a previous study [62] . Units ( U ) are given in fmol/cell/hr . The MetaboTools function setMediumConstraints was used to apply the following constraints to the global model [61] . Essentially , infinite constraints were set to lb = −2 , 000 U and ub = 2 , 000 U . All exchange reactions in the model were initially set to lb = −2 , 000 U and ub = 2 , 000 U . Subsequently , constraints were set for exchange reactions of ions ( lb = −100 U ) , vitamins ( lb = −1 U ) , essential amino acids ( lb = −10 U ) and compounds such as water or protons ( lb = −100 U ) . Oxygen uptake was constrained to lb = −1 , 000 U and ub = 0 U . This range was defined based on reported oxygen uptake rates of a cancer cell line ( 2 . 85 ⋅ 10-6ml O2/105cells/min = 646 . 013 U [64] ) . Additionally , the lower bounds of the superoxide anion and hydrogen peroxide exchanges ( i . e . , uptake flux ) were set to zero to prevent the generation of models that did not require oxygen uptake . Reaction fluxes are usually in units of mmol/gDW/hr . Here , however , the metabolite uptake and secretion profiles were mapped in the unit fmol/cell/hr [15] . We assumed a unitary cell weight of 10-12 g , which was in the range of the dry weight ( 3 . 645 ⋅ 10-12 g ) that we calculated for lymphocytes in an earlier study [62] . In that study , the dry weight was inferred from the dry mass ( range 35–60 ng [65] ) and cellular volume ( 4000 μm3 [66] ) of the human osteosarcoma cell line U2OS , which we related to the cell volume of lymphocytes ( 243 μm3 ) [67] . By calculating 4000/243 = 16 . 46 , 60 pg/16 . 46 = 3 . 645 pg ( 3 . 645 ⋅ 10-12 g ) [62] . According to 1mmol/gdw = 1012fmol/1012 cells , no biomass scaling was necessary . The lower bound ( lb ) of the biomass objective function was fixed to a minimal value of 0 . 008 U to match the lb defined for the slowest growing cell line in the data set ( HOP-92 , 88 hrs ) [27] , ensuring that the model building resulted in functional models with non-zero growth . S1Q Table lists the reactions and constraints of the global model . We used published metabolomic data [15] . There were two quantitative extracellular metabolomic profiles for each of the NCI-60 cell lines . These profiles defined the uptake and secretion rates of 115 metabolites [15] . From the entire set of detected metabolites , we used only the calibrated ( quantitative ) uptake and secretion fluxes . Fluxes were provided in the unit fmol/cell/hr ( U ) and were incorporated as such into the model . Throughout the manuscript , fluxes are reported in the unit fmol/cell/hr ( U ) . Metabolite identifiers in the data were mapped to the metabolite abbreviations in the global model . The metabolite aminoisobutyrate was not part of the global model and was excluded . We identified the existing metabolite exchange reactions based on the metabolite abbreviations . If there was no exchange reaction in the model but if the metabolite itself was part of the model , a new exchange reaction was added to the model . In addition to the exchange reactions , transport reactions need to be present in the model to account for transport of metabolites between the extracellular space and the cytosol of the model . Transport reactions need to be added for all metabolites for which we added exchange reactions . These transport reactions were identified from the literature . If no transporter for the metabolite could be identified , we added a diffusion reaction . The additions that we made to the model based on the metabolomic data comprised 44 transport and 37 exchange reactions ( S1R Table ) . The global model used to generate the cancer models comprised 3 , 935 reactions and 2 , 833 metabolites . The Integration of the metabolomic data was performed as detailed in a protocol that provides extensive support ( including workflows , code , and tutorials ) for the data integration , model generation , and model analysis , carried out in this study [61] . Consider the optimization problem min θ ( v ) s . t . S · v = 0 , l b ≤ v ≤ u b , ( 1 ) where v ∈ R n is a vector of reaction rates , θ ( v ) is a scalar valued objective function and S ∈ R m × n is the stoichiometric matrix consisting of m metabolites and n reaction rates as defined by the metabolic reconstruction . The lower and upper bounds , lb and u b ∈ R n respectively , constrain the sign and magnitude of the reaction rate , with the convention that a net forward rate is positive . In flux balance analysis ( FBA [68] ) , the objective is to minimize θ ( v ) : = cT ⋅ v , a linear sum of reaction rates , where c ∈ R is a parameter vector that specifies the linear contribution of each reaction rate to the objective function . When minimizing a single reaction rate , every entry of c is zero , except one . Typically , there is an infinite number of optimal reaction rate vectors that produce an optimal value of the objective function . To obtain a unique flux vector , we first solve Problem ( 1 ) with θ ( v ) : = cT ⋅ v , then fix the rate of the previously optimized reaction and again solve Problem ( 1 ) except with θ ( v ) : = 1 2 v T · v . This procedure returns a unique reaction rate vector that minimizes the square of the Euclidean norm of the reaction rates , subject to optimality with respect to the original objective function [21] . In flux variability analysis ( FVA ) , one uses linear optimization to compute the minimal and maximal rate of each reaction , subject to θ ( v ) : = cT ⋅ v being minimal as computed in Problem ( 1 ) [34] . The presence of an exchange and transport reactions does not ensure that a metabolite can be consumed or secreted by the model because anabolic and/or catabolic pathways may not be present or unknown [20] . We used the MetaboTools function prepIntegrationQuant to generate individual uptake and secretion profiles for each sample in the data set: To identify the subset of metabolites that the model could consume and secrete , we performed FBA while enforcing small uptake ( ub = −0 . 0001 U ) or secretion ( lb = 0 . 0001 U ) for all mapped metabolite exchanges . All metabolites that could not be consumed ( 14 ) or secreted ( 14 ) by the model were discarded ( S1S Table ) . Among them was homoserine 4-hydroxybenzoate , which could be neither consumed nor secreted by the model . Therefore , data for 112 metabolites could be mapped . Note that these 112 metabolites included those that could only be consumed , only be secreted , or by both consumed and secreted ( S1S Table ) . The identification of metabolites that are not part of a metabolic reconstruction is common , and pathways for these metabolites need to be added in future releases of the human metabolic model [20] , which served as a starting point ( see also above ) . If the uptake of a metabolite was possible in the global model but secretion was not , only metabolite secretion was discarded from the metabolic profiles , while uptake remained present , and vice versa . After the sets of ‘qualitatively’ feasible metabolite exchanges were identified , we mapped the sets of metabolite uptake and secretions of a sample to the global model using the MetaboTools function setQuantConstraints [61]: We mapped a minimum of 95 and a maximum of 105 exchanges to the models ( S1T Table ) . These exchanges were split into uptake and secretion . The number of metabolite uptakes mapped to the model ranged between 34 and 58 , and the number of secretions enforced in the model varied between 42 and 67 . We imposed each detected , quantitative flux x as a constraint to the bounds of the respective metabolite exchange reaction while considering a 20% allowance around x ( lb = 0 . 8x U and ub = 1 . 2x U ) . The constraint pairs for one sample were mapped to the global model one by one . After constraints were placed on one exchange reaction , FBA was performed to check if the model was still able to grow . Although the global model was able to perform all qualitative metabolite exchanges that were mapped , certain quantities or combinations of constraints could still render the model infeasible . In case of infeasibility , the original bounds of the model were restored , and we proceeded to the next set of constraints . Quantitative constraints rendered 27 preliminary cell line models infeasible ( Fig 1A ) . Of these 27 models 25x2 , 1x1 , and 1x4 exchange constraints were restored during the data integration ( S1B Table ) . Although 464 of the reactions in the global model can exchange metabolites across the boundary of a cell , the exchange of only 115 metabolites was actually quantified in the metabolomic profiles that we employed . The incompleteness of the metabolic profiles results from limits to the scope of individual metabolomic platforms , e . g . , oxygen uptake rates that were not reported . This issue was compounded due to the use of fresh medium that was undefined with respect to small molecules , e . g . , fresh medium containing serum . In the preliminary model , removing all but the metabolite exchanges ( corresponding to measured , exchanged metabolites ) always led to a model that did not admit a feasible steady-state flux . We hypothesized that the metabolic profiles were likely to be an incomplete representation of the total number of metabolites exchanged with the medium . Therefore , we developed a novel method , deemed minExCard , that takes a preliminary metabolic model as the input and predicts a steady-state flux vector with the minimum cardinality for the reactions corresponding to the missing exchanges . That is , it predicts a minimal number of missing exchange reactions that are required to be active to permit a feasible steady state flux ( S1O Table ) .
Altered metabolism is characteristic for many human diseases including cancer . Disease progression and treatment efficacy vary between patients . Hence , we need personalized approaches to define metabolic disease phenotypes . This definition will enable us to unravel the underlying disease mechanisms and to treat individuals more efficiently . Computational modeling increasingly supports the analysis of disease mechanisms and complex data sets . The interpretation of extracellular metabolomic data sets is particularly promising since this data type is proximal to the actual metabolic phenotype altered in human diseases . Moreover , it might enable us to directly interpret disease states from serum samples in the future . Herein , we took a first step towards this ambitious goal . We generated a large set of cancer metabolic models from extracellular metabolomic data and computationally stratified the models based on their metabolic characteristics into different phenotype groups . Melanoma emerged as an interesting example of how our approach can provide insights into the intracellular metabolism from extracellular measurements . Taken together , this work paves the way to generate condition-specific models from extracellular metabolomic data and demonstrates the many ways by which distinct phenotypes can be stratified and phenotype-specific intervention targets can be predicted .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "cell", "physiology", "medicine", "and", "health", "sciences", "oxygen", "cancers", "and", "neoplasms", "cell", "metabolism", "oncology", "physiological", "processes", "oxygen", "metabolism", "metabolomics", "metabolites", "pharmacology", "drug", "metabolism", "melanomas", "chemistry", "pharmacokinetics", "biochemistry", "cell", "biology", "physiology", "secretion", "biology", "and", "life", "sciences", "physical", "sciences", "metabolism", "chemical", "elements" ]
2017
A systems approach reveals distinct metabolic strategies among the NCI-60 cancer cell lines
Asters nucleated by Microtubule ( MT ) organizing centers ( MTOCs ) converge on chromosomes during spindle assembly in mouse oocytes undergoing meiosis I . Time-lapse imaging suggests that this centripetal motion is driven by a biased ‘search-and-capture’ mechanism . Here , we develop a model of a random walk in a drift field to test the nature of the bias and the spatio-temporal dynamics of the search process . The model is used to optimize the spatial field of drift in simulations , by comparison to experimental motility statistics . In a second step , this optimized gradient is used to determine the location of immobilized dynein motors and MT polymerization parameters , since these are hypothesized to generate the gradient of forces needed to move MTOCs . We compare these scenarios to self-organized mechanisms by which asters have been hypothesized to find the cell-center- MT pushing at the cell-boundary and clustering motor complexes . By minimizing the error between simulation outputs and experiments , we find a model of “pulling” by a gradient of dynein motors alone can drive the centripetal motility . Interestingly , models of passive MT based “pushing” at the cortex , clustering by cross-linking motors and MT-dynamic instability gradients alone , by themselves do not result in the observed motility . The model predicts the sensitivity of the results to motor density and stall force , but not MTs per aster . A hybrid model combining a chromatin-centered immobilized dynein gradient , diffusible minus-end directed clustering motors and pushing at the cell cortex , is required to comprehensively explain the available data . The model makes experimentally testable predictions of a spatial bias and self-organized mechanisms by which MT asters can find the center of a large cell . Spindle assembly in higher eukaryotic cells involves the self-organization of microtubules ( MT ) into a bipolar structure . During mitosis in animal cells , spindle poles are defined by a pair of centrosomes . However bipolar structures emerge even in the absence of centrosomes during meiosis in vertebrates as well as mitosis in plants . In such acentrosomal spindles , the poles self-organize by the dynamic interactions of MTs with molecular motors , regulatory factors and chromatin . While multiple components of this cellular-scale pattern forming system have been identified , the precise nature of the interactions between the components are still not completely understood . The meiotic maturation of mouse oocytes is a well studied example of such an acentrosomal spindle assembly system . The first meiotic division is characterized by germinal vesicle breakdown ( GVBD ) [1] , before and after which small aster-like fibrillar structures or microtubule organizing centers ( MTOCs ) are observed [2] . MTOCs which are nucleated both in the cytoplasmic and peri-nuclear spaces , both aggregate at the center to form a spindle by prometaphase I [3] . Such a convergence of radial MT arrays or asters was reported previously in Xenopus meiosis II oocytes [4] . Using cell-free Xenopus oocyte extracts , this convergence was shown to result from asymmetric centrosomal MT growth due to a gradient of RanGTP [5–7]- referred to as biased ‘search-and-capture’ . However during meiosis I in mouse oocytes , experimental perturbation of RanGTP levels does not significantly affect spindle assembly [8 , 9] . If RanGTP does not act as a guidance cue as reported previously [10] , the nature of the directional cue and force generation remains to be understood . The force required for MTOC convergence to the nuclear region is thought to originate from a combination of MTs , motors and anchorage points . Multiple mechanisms have been reported in the past to drive radial MT array transport in cells- ( a ) polymerization dependent pushing forces as seen during the centering of asters in vitro [11 , 12] , ( b ) cortical force-generator based pulling [13] , ( c ) cortical motors which both depolymerize and pull [14] , ( d ) cytoplasmic minus-ended motors which pull asters in a length-dependent manner [15] , ( e ) cytoplasmic streaming by cargo transport driving aster movement [16 , 17] and ( f ) acto-myosin contractility as seen in starfish oocytes [18] . Contact with the cell cortex can move asters when the relative MT lengths is comparable to the cell radius [19] . Both active and passive mechanisms drive the movement of centrosome nucleated asters . However most of the cortical pushing and pulling models are unlikely to affect long-range movement of MTOCs which have MT lengths ∼3 μm as compared to the cell-radius of ∼40 μm . Transport of asters by cytoplasmic streaming based on cargo transport by one large aster [17] , is also unlikely to drive mouse meiosis I oocyte MTOCs due to their size and number ( ∼80 to 100 ) , which will prevent a coherent and directed flow . Inhibition of acto-myosin contractility has also been shown to have no effect on the centripetal movement of mouse MTOCs [9] . While centrally-anchored MTOCs and cross-linking motors have also been proposed by Schuh et al . [9] to drive the MTOC motility , the movement continues even after nuclear envelope breakdown ( NEBD ) . Thus for a complete theoretical understanding of the mechanism by which MTOCs converge in spindle assembly a mathematical model of the process is necessary to test multiple hypotheses that have been proposed . Theoretical models have been used to probe the interactions of microtubules and motor complexes and are capable of reproducing in vitro self-organized patterns [20–22] . These simulations have been extended to understand the role of multiple components in spindle assembly such as antiparallel interactions [23] , pole focussing by minus-end directed motors [24] , gradients of stabilization [25] and intra-spindle nucleation and dynamic instability regulation [26] . In recent work , we have demonstrated the centripetal movement of centrosomal MT asters towards surface immobilized chromatin in Xenopus egg extracts can be modeled by a gradient of polymerization dynamics and uniform motor distribution [27] . This is comparable to a model of length-dependent pulling by motors to translocate MT asters during C . elegans embryogenesis [15] . However , neither of these models take into account the relatively shorter MTs seen in MTOC asters , and lack details specific to meiosis I . In search of common design principles in spindle assembly , theoretical modeling of the centripetal motility of MTOC arrays can be used to test the generality of previous results . Here , we quantify the spatial trends in MTOC motility and find the random and directional components of motility depend on how far the MTOCs are from the cell center . The detailed quantitative analysis allows us to develop and test theoretical models of random walk with drift . Only a spatial gradient of drift can reproduce the experimental data . Such an optimized gradient is further used to model MT dynamic instability and motor distributions , to test the combination of mechanisms that can reproduce the experimental statistics of centripetal MTOC motility . The mouse oocyte is modeled in a 2D circular geometry of radius rcell , with concentric circular chromatin of radius rchr . The outer cytoplasmic region has a radius rcyto and rcell = rchr + rcyto ( Fig 1B ) . MTOC asters are modeled as point particles , nucleated uniformly in the cytoplasmic space of the oocyte . The motion of the simulated particles is a mixture of random Brownian and directed centripetal motion , depending on the position of the MTOC in the oocyte ( Fig 1B ) , based on the previously observed ‘stop and go’ nature of the motility [9] . In this model , MTOCs are transported to the cell center and ‘captured’ by the chromatin once they reach the central chromatin mass . The process resembles models of biased ‘search-and-capture’ used to describe spindle assembly [7 , 36 , 37] . Here , we use the model to define the spatial properties of the bias of attraction by comparing the simulation outputs to spatial trends in MTOC motility seen in experiment . A mechanistically detailed model was developed using Cytosim [41] , a C++ Langevin dynamics simulation engine , by building on previously developed models of MT-mechanics [14 , 42] , polymerization kinetics [7 , 25] and motor interactions [20–24 , 26 , 27 , 43] . To test what minimal components will produce the observed centripetal motility of MTOC asters , a model of an MT stabilization gradient described previously [27] was developed by mapping the gradient shape optimized in the RWD model . This scenario was compared with scenarios where the gradient consisted of immobilized minus-ended molecular motors . These biased ‘search-and-capture’ scenarios were contrasted with self-organized scenarios which lacked any directional bias , i . e . diffusible motor-complexes and MTOC pushing from the cell boundary . The model is implemented in an oocyte cell geometry with MT polymerization dynamics and mechanics as well as discrete stochastic molecular motors that are either immobilized or diffusible . The experimental trajectories of MTOCs show a distinct centripetal motion as seen in the time-projected trajectories ( Fig 1A ) . The input parameters for diffusive and directed motion in the RWD model ( Fig 1B ) were obtained from fitting Eq 7 to experimental msd profiles ( S1A Fig ) and obtaining the mean Deff ( S1B Fig ) and veff ( S1C Fig ) . As a result , the nature of the centripetal motility depends solely on the parameters determining the field of drift . We optimize the parameters that determine the shapes of both attractive ( ϕa ) and repulsive ( ϕr ) fields ( Fig 1C ) by scanning 600 possible combinations , and minimizing the sum rank of errors ( S2A Fig ) obtained from the ranked errors ( ϵ ) between simulated and experimental values of χ and tc . Our minimization scheme identifies the optimal gradient to be a long range attractive gradient ( r1/2 = 10 μm and s = 1 ) and a short range repulsive gradient from the cell boundary ( r1/2 = 0 μm and s = 2 ) based on directionality and capture time . While the error ( ϵ ) minima do not coincide ( in terms of gradient parameters ) between χ ( S2B Fig ) and tc alone ( S2C Fig ) , our sum-rank scheme gives us a global optimum . The outputs of such a gradient result in XY trajectories which are directed inwards at the cell boundary , random in the mid-zone and directed closer to chromatin ( Fig 1D ) , qualitatively comparable to experiment ( Fig 1A ) . Quantitative comparisons between experimental and simulated χ profile reflects this trend in motility- particles at the cell boundary and near chromatin are more directed , than those in the mid-zone ( Fig 1E ) . The simulated capture time distribution also matches with experiment ( Fig 1F ) . In order to understand the mechanism underlying the experimental motility observed , trajectories were further analyzed for their time-dependence . The experimentally measured MTOCs have heterogeneous distance-time profiles , with some MTOCs moving rapidly in < 40 min , while others undergo a delayed ( > 40 min ) inward movement ( Fig 2A ) . The optimized RWD model profiles qualitatively match those from experiment . In previous work , distance-time plots with a sigmoid profile have been interpreted to mean pulling forces are at work , while a parabolic has been interpreted to mean pushing is at play [15] . Here , we use a fit function with three parameters , n: a measure of the shape of the profile ( n > 1: sigmoid and n ≤ 1: parabolic ) , Thalf: the time at which the distance travelled is half-maximal , and dmax: the maximal distance travelled , as follows: d ( t ) = d m a x · t n / ( T h a l f n + t n ) ( 11 ) The experimental and RWD simulation distance-time plots were fit to obtain dmax , Thalf and n . A value of n > 1 is taken to indicate pulling , while n ≤ 1 is taken to indicate pushing . Representative data from experiment ( Fig 2C ) chosen based on their nucleation position close to chromatin ( dn = 7 . 05 μm ) , mid-way in the cytoplasm ( dn = 15 . 49 μm ) and close to the cell membrane ( dn = 26 . 36 μm ) , show an apparent pattern in the n values- high in the mid-zone and low close to chromatin and near the cell boundary . Representative plots from the optimized RWD simulations ( Fig 2D ) with dn = 7 . 03 μm , dn = 14 . 01 μm and dn = 24 . 88 μm show a similar trend in the values of n . When the n from all experimental data ( S3 Fig ) is compared to simulated fits for different positions of nucleation , a qualitative match is observed ( Fig 2E ) . The n value from simulations is higher in the mid-cell region as compared to near chromatin or at the cell boundary . This can be understood in terms of the sharp transition in the attractive gradient of drift ( ϕa ) at r ≈ 15 μm , resembling a ‘pulling’ process . The phenomenological model does not allow an interpretation of the origin of pushing or pulling forces . We therefore proceeded to add detailed molecular-motor and MT polymerization dynamics to the model to make experimentally testable predictions about the system . The RWD model predicts two drift fields- attractive from the center and repulsive from the cell boundary- are required to reproduce experimental statistics . Here , we proceed to test molecular mechanisms which combine molecular motors , MT-dynamics and mechanics of MTs and membrane interactions , with the aim of developing a mechano-chemical understanding of the effective drift fields . We categorize these mechanisms into two types: We then systematically evaluate plausible mechanisms and evaluate them for their ability to result in MTOCs finding the center of the oocyte within an experimentally observed time-scale ( ∼20 min ) . In the previous section , qualitatively , self-organized mechanisms of MTOC centering could not drive centripetal motility . The spatially binned directionality ( χ ) of simulated MTOCs in the absence of any gradient further quantifies this ( Fig 4A ) . Neither tetrameric motor complexes , nor uniform surface immobilized motors and pushing at the cell boundary result in a trend in χ comparable to experiment . Cross-linking by motor complexes of different stall forces ( f0 = 2 and 7 pN ) and densities ( N m c = 10 3 and 104 motors/oocyte ) were tested and higher stall forces with high densities result in high values of χ throughout the cell ( > 0 . 5 ) . A directional bias in the form of a field of fcat and fres ( based on Eq 5 ) resulting in asymmetric MT lengths , also fail to reproduce the directionality trends ( Fig 4B ) . Confirming our qualitative observations from the simulation visualization , only a gradient of motors ( f0 = 7 pN , N m i = 10 3 ) can reproduce most of trend in directionality as a function of distance ( Fig 4C and 4D ) . In the absence of experimental estimates of the number of motors and their stall forces from meiotic mouse oocytes , we explore two extreme values of f0 ( 2 and 7 pN ) reported in literature for dynein and scan N m i over thee orders of magnitude . We find high density ( N m i = 10 4 motors/oocyte ) of weak motors ( f0 = 2 pN ) ( Fig 4C ) and a lower density ( N m i = 10 3 motors/oocyte ) of strong motors ( f0 = 7 pN ) ( Fig 4D ) , can both reproduce experimental profiles of directionality . The proportion of MTOCs captured at the chromatin boundary was evaluated by following the distance of MTOC centers as they entered the chromatin mass . Strikingly the proportion of MTOCs captured in the first 20 minutes of simulation from the motor gradient with immobilized motors of f0 = 7 pN and N m i = 10 3 most closely matched experiment ( Table 3 ) . However , the mean velocity values from simulations were insensitive to either f0 = 2 or 7 pN and motor densities over a range Nm = 102 to 104 motors/oocyte ( Table 4 ) . Additionally to test how the motility was affected by the total number of MTs per aster in the scenario of a motor gradient , we examined the χ and <v> of simulated MTOCs which were initialized at a distance of 15 μm from the chromatin edge . As a result we expect these asters to experience the maximal force asymmetry , as they are at the lower end of the motor gradient . We find for increasing motor densities ( N m i ) directionality χ continues to increase , but increasing NMT per aster appears to rapidly saturate the χ value for any given N m i value for both f0 = 2 and 7 pN ( Fig 5A and 5B ) . Increasing N m i leads to a marginal increase in the mean velocity ( <v> ) for a fixed NMT value . However increasing the value of MTs per aster , to our surprise , does not affect <v> ( Fig 5C and 5D ) . We interpret this to be the result of the uniform radial distribution of MTs in the aster and a tug-of-war arising from it . In order to further understand the role of motor-density changes and their effect on MTOC motility , we evaluate the random walk statistics of the motility and compare it to experiment . Simulations of multiple gradient forms , motor types and densities in this work suggest a motor gradient as a minimal model to understand the centering motion of MTOCs in mouse meiosis I oocytes . However , we were unable to reproduce the experimentally observed χ ∼ 0 . 5 , when MTOCs were 10-20 μm from the chromatin edge . Interestingly , the presence of the self-organized clustering motors ( f0 = 7 pN , N m c = 10 4 motors/oocyte ) alone resulted in simulated χ values that matched experiment , in the radial distance between 10 and 20 μm ( Fig 4A ) , due to MTOC aggregation . We hypothesized that a hybrid mechanism combining an immobilized motor-gradient with diffusible clustering motor-complexes might reproduce the complete experimental distance-dependent directionality profile . Visually the MTOCs appear to find the center more efficiently ( Fig 6A and 6B ) . Here 104 clustering motors per oocyte of stall force 2 pN were combined with 104 immobilized motors per oocyte and stall force 2 pN . A systematic screen of the effect of increasing tetrameric complex density while keeping the density of immobilized of motors constant was evaluated in terms of the measure of directionality . The radial distance profile of χ increases in the mid-range when clustering complex density is increased from 103 to 105 motors/oocyte ( Fig 6C ) . Either ‘weak’ diffusible dynein-like complexes ( f0 = 2 pN ) with a high density ( N m c 10 5 ) or ‘strong’ motors ( f0 = 7 pN ) with a lower density ( N m c = 10 4 motors/oocyte ) , both result in χ matching the experimental values in the mid-zone of the cell ( 10-20 μm ) ( Fig 6C and 6D ) . This result suggests that while clustering alone cannot center MTOCs in oocytes , it improves the fit to experiment . Thus we believe our model reproduces both the qualitative and quantitative nature of the MTOC centering motility and provides novel insights into the sensitivity of this model . It demonstrates how a combination of directional cues and self-organized clustering can center small MT asters in a large cell such as an oocyte . Meiotic spindle assembly in mammalian cells in the absence of centrosomes involves the nucleation of MTOCs in cytoplasm and their coalescence and sorting around chromosomes , resulting in bipolar spindle assembly . The nucleation of MTOCs in cytoplasm and the centripetal motility of small radial MT asters has been previously observed during the first meiotic division in mouse oocytes [3] . Similar convergence was also observed in Drosophila oocytes [60] and quantitative analysis and model calculations were used to infer that directed transport for the MTOCs was essential for the coalescence of MTOCs [61] . In Drosophila the unconventional kinesin Ncd ( minus-end directed ) was implicated to play a role in this inward motility [62] . In mouse oocyte MTOC coalescence , cytoplasmic dyneins or comparable minus-end directed motor have been implicated in force generation for the centripetal movement [9] . Here , we analyze experimental data from the early stages of the meiotic maturation of mouse oocytes . The experimental analysis is used to constrain a field of spatially inhomogeneous drift in a random walk . The optimized model of drift is used to model gradients of the motor dynein and MT dynamic instability . By comparing the simulation outputs with experiments , we arrive at a minimal model of a gradient of motors , essential to reproduce the experimentally observed statistics . The experimental statistics of the MTOC motility from mouse oocytes are mostly representative of post-NEBD dynamics , allowing us make the simplifying assumption that the nuclear envelope plays no explicit role in the process . The movement of these radial MT arrays appears visually to have both an effectively diffusive and a transport component ( Fig 1A ) . The frequency distribution of velocity from experiment is long tailed and fit to a lognormal function ( S4 Fig ) , suggesting anomalous super-diffusive transport . While the motility had been previously described as ‘stop-and-go’ [9] , we find little evidence of ‘stop’ or pause events in the motility . Our quantification of MTOC motility in cells , demonstrates the motility is qualitatively comparable to previous estimates of centrosomal aster movement observed in C . elegans fertilization [15] , MTOCs in Drosophila oocyte meiosis I [61] and centrosomal asters in Xenopus meiotic extracts [5 , 27] . This suggests a common theme underlying the transport of radial MT arrays in meiotic spindle assembly . The distance travelled or displacement from the start-point plotted over time of MT arrays have been used previously [15] to distinguish between “pulling” and “pushing” modes of motility of centrosomal MT arrays during pronuclear migration . In the case of mouse meiotic MTOCs , these plots also help to distinctly separate trajectories into two sub-populations- those which show an initial rapid rise followed by capture ( < 40 min ) , while others do not move much for a long time ( > 40 min ) and after this delay are captured at chromatin ( Fig 2A ) . We further improve on the work of Kimura et al . ( 2005 ) [15] by fitting the data with a saturation model with cooperativity ( Eq 11 ) , and use it quantitatively to distinguish between pushing ( n ∼ 1 ) and pulling ( n > 1 ) mechanisms ( Fig 2C ) . Every trajectory from experiment was fit to obtain a profile shape ( sigmoid or parabolic ) term n ( S3 Fig ) and comparing n from simulation and experiment shows a pushing mode of transport ( n ∼ 1 ) close to chromatin and the cell boundary , while those in the mid-range are pulled ( n > 1 ) ( Fig 2E ) . The distance travelled plots from the mechanistic motor-gradient model with MT asters sorted by nucleation distance demonstrate an increase after a short delay near chromatin ( dn = 0 to 10 μm ) due to pulling ( S5A Fig ) . Those in the intermediate range ( dn = 10 to 20 μm ) have a longer delay and then appear to be pulled ( S5B Fig ) . Close to the cell-boundary ( dn > 20 μm ) they increase rapidly and then saturate , due to MT-pushing at the membrane ( S5C Fig ) . Thus a model of a gradient of chromatin-centered motors and a rigid cortex can reproduce the qualitative differences observed in the distance-time profiles of MTOC transport . However in these experiments , the absence of clear ‘pulling’ in experiment ( n > 1 ) near chromatin might have been missed , since the MTOC identity is lost as it nears the chromatin . While cell cortex-based pushing mechanisms have been demonstrated to generate centripetal movement [12 , 50] , the nature and localization of minus-end directed pulling motors in the oocyte remains to be determined . Recent evidence of from mouse oocytes during MTOC fragmentation [63] and meiotic maturation [34] suggest dynein anchored at the nuclear envelope might influence both processes . A careful study of dynein localization dynamics in this and related systems , could by used to test our model prediction . A ‘tug-of-war’ in the transport of anti-parallel MTs moving on a surface coated with motors arises from the action of the same species of motor acting against each other , with small asymmetries in length , amplifying the velocity of transport [64] . Two-fold length asymmetries ( 10 to 20 μm ) have been previously observed in centrosomal asters [5 , 7] and simulations of such asymmetric asters on sheets of dynein motors resulted in aster transport towards chromosomes [27] . However , the mouse MTOC radius is in the range of 2 to 3 μm and no appreciable asymmetry of lengths has been reported [9] . In this work , neither homogeneous motor distributions ( S1 Video ) , nor tetrameric motor-complexes ( S2 Video ) , nor a dynamic instability gradient ( S3 Video ) result in convergence to chromatin in the ∼20 min time scale seen in experiment . Taken together , a gradient of motors is necessary in a minimal model with a mouse oocyte geometry for MTOCs to converge to the chromatin center ( S4 and S5 Videos ) . This suggests aster motility in meiosis I of mouse oocytes differs from that in meiosis II of Xenopus oocytes . In the latter , length asymmetry can result in directional transport , however in mouse oocytes the MTOC asters are ∼4 fold shorter in MT length , resulting in smaller forces being generated . The motor numbers would then be insufficient to successfully resolve the tug-of-war in mouse oocytes by a simple ∼2-fold changes in MT length , as seen in Xenopus oocytes . In contrast , the gradient of immobilized motors result in a comparable spatial distribution of velocity for minus-ended motors with f0 = 2 pN ( S6A Fig ) and f0 = 7 pN ( S6B Fig ) . Spatial gradients of RanGTP [6 , 65] are thought to direct centrosomal MT asters to chromatin during spindle assembly in meiotic extracts [5–7] . However the outcome of our simulations predicts that in meiotic MTOC motility , motor gradients are necessary . Such a gradient could arise from self-organized diffusion and attachment of minus-ended motors on MTs nucleated at the chromatin periphery . In addition , the motors could be immobilized on intracellular organelles , as shown in centrosomal aster centration in C . elegans [16] . It remains to be seen which of these specific mechanisms results in the the chromatin centered gradient of anchored motors . Some evidence from experiments in mouse oocytes serves to support our motor gradient model , where pre-NEBD maturing oocytes showed a high-concentration of dynein motors around the nucleus [66] . More recently , evidence of dynein localized at the nuclear periphery fragmenting MTOCs [63] , suggests a validation of our model of a chromatin centered gradient of dynein-like motors . Further testing is however required to examine its dynamics . The role of chromosomes in the centering activity of MTOCs in maturing mouse oocytes during meiotic I spindle assembly had been tested by experimentally removing the nucleus [9 , 39] . The MTOCs of such oocytes have a scattered appearance and fail to assemble bipolar spindles . While chromosomes are considered essential for meiotic spindle assembly [67] , we hypothesize that they also serve as the primary guidance cue of centripetal MTOC motility , in a manner comparable to other aster cell centering systems [5 , 27 , 36] . To test this , the spatial organization of MTOCs in enucleated oocytes was measured using published experimental data reported by Schuh and Ellenberg [9] . The image analysis of MTOCs positions from experiment ( S7A and S7B Fig ) resulted in a radial density distribution around the cell center ( S7C Fig ) . This distribution is comparable to a simulation of randomly localized MTOCs , suggesting the chromatin serves as an important guidance cue for the centripetal motility of MTOCs , and in it’s absence the directional motility is lost . The molecular mechanism which converts the positional information of the chromatin into a gradient of molecular motors , still remains to be understood . The msd profiles of MTOCs from simulations that were close to chromatin transition from super-diffusive to sub-diffusive motility ( S1 Text , S8 Fig ) , as estimated by α , the measure of anomalous diffusion ( S8F Fig ) . This transition results purely from changing the single dynein motor stall force from that reported for bovine brain cytoplasmic dynein ( f0 = 2 pN ) [48] to the yeast cytoplasmic dynein ( f0 = 7 pN ) [56] value . The MTOC convergence in the 2 pN stall force calculations is slow ( S4 Video ) as compared to when the motors had a higher stall force ( 7 pN ) ( S5 Video ) at the same motor density ( N m i = 10 3 motors/oocyte ) . Once the MTOCs reach the center of the motor gradient , they undergo effectively sub-diffusive movement , unable to generate enough force asymmetry to escape . With an additional centrosomal fluorescence label in mouse MTOC motility , the intra-nuclear motility and reorganization of MTOCs could be studied in future . This will also help better understand the subsequent bipolar spindle formation and its connection with chromosome biorientation in meiosis I of mouse oocytes [68 , 69] . The sensitivity analysis of the gradient model demonstrates that MT number per aster does not affect velocity and directionality of the asters . On the other hand the model is sensitive to motor density . The motor density in 2D area-density ranging between N m i = 10 3 and 104 motors/oocyte corresponds to a physical density of ≈ 0 . 2 to 2 motors/μm2 for an oocyte of radius 40 μm . The addition of motor complexes , which cross-link MTs and walk to the minus-ends of the respective MTs , also change the dynamics of MTOC transport . At high densities of motor complexes , the asters coalesce to a few ( ∼10 ) clusters and centripetal convergence results . Yet the directionality profiles are qualitatively different from the experimental measures ( Fig 6C ) . While the densities of both immobilized and diffusible motors tested are mean area densities , over-expression of dynein motor proteins could serve as an experimental test of our model predictions . A limitation of the models described here is that both the phenomenological and mechanistic models assume a 2D circular geometry , while the mouse oocyte is a 3D sphere . So asters finding the cell center in 3D is expected to take longer due to dimensionality in biological search problems [70] , and a further parameter optimization would be required . Our effort here serves to reduce the search for ‘scenarios’ , i . e . combinations of mechanisms such as motors , MT-dynamic instability , gradients and clustering motors , by optimizing simulations to experimental data . In future , a full 3D model would then only require parameter optimization to a 3D experimental dataset . At the other extreme , a 1D model could have further simplified the geometry based on the radial-symmetry of the system , as has been assumed in the ‘slide and cluster’ model of linear MT filaments in spindle assembly [71] . However this would ignore the orthogonal interactions between MTs of multiple asters , which are only possible in an explicit 2D geometry . Thus our choice of spatial dimensions is driven by an attempt to capture the important qualitative behavior of the system , while keeping the model simple enough for clarity and calculation speed . While a 3D simulations of cellular processes are more ‘complete’ , it has been suggested the choice of spatial dimensions should simplify the system to sufficiently capture the spatial dynamics [35 , 72] . A further limitation of both the phenomenological RWD and MT-motor model is the availability of only one time-series dataset . In future , additional experiments with mouse oocytes could help test the model predictions . While this model has been developed to test the generality of mechanisms on the mouse MTOC motility , it would be useful in future to explore the relevance of this model to other aster-centering systems such as in C . elegans [15] , Xenopus [27] , Drosophila [73] and sea urchin [74] . Additional mechanisms such as a contractile actin network has been shown to drive spindle assembly in meiosis I of starfish oocytes [18] , but are ignored in this model since in experiments , it does not affect the process [9] . Additionally the potential role of MT-dependent MT nucleation [75] remains to be explored as a self-organized mechanism . Testing alternative cellular geometries and additional mechanisms could in future result in a more complete exploration of MT aster centripetal transport and the physical constraints . This in turn might help us better understand the physical basis of the evolutionary diversity of aster-centering mechanisms . The models of of MTOC centripetal motility explored in this study , provide insights into several aspects of the early stages of self-organized spindle assembly . For instance , the RWD model demonstrates that for a cell of diameter ≈ 80 μm , a simple random-walk strategy of MTOC particles ‘search-and-capture’ at the chromosomes is insufficient within the time-scale of spindle assembly in meiosis ( 20-30 min ) [9] , and a long-range bias in motility is essential . The mechanistic model demonstrates that a bias of motors is minimally capable of reproducing the dynamics . MT mass increase which could arise due to increasing MT lengths ( stabilization ) [5 , 6] or number ( nucleation ) [75] , both appear to be insufficient to affect the dynamics of motility . We also find , dynein-like clustering motor complexes , which diffuse and cross-link MTs , at a high density result in an aggregation of MTOC asters to the cell interior . Such a self-organized mechanism however is inefficient in resulting in MTOC capture percentages comparable to experimental values ( Table 3 ) in comparable time-scales ( ≈ 20 min ) . Additionally MT density per aster does not affect MTOC centripetal motion but the density of immobilized motors ( N m i ) localized in a gradient does change the dynamics . Such parameters are likely to be adjusted by cells , depending on the specific geometry and time-constraints . The results of this study could be used to predict the nature of MTOC centripetal transport , when the size ratios of asters to cell sizes are also comparable to the mouse oocyte . A more complete picture of the evolutionary constraints on mechanisms driving radial MT arrays to find the center of a cell will however require further quantitative studies from acentrosomal spindle assembly from more organisms , as well as calculations that explore a greater parameter space . The model presented here predicts the functional form of a drift field in agreement with experimental data of MTOC motility . A mechanistic model of the gradient with immobilized minus-ended motors minimally reproduces experimental dynamics and allows us to test the effect of single molecule characteristics of motors on collective transport statistics . A hybrid model with a gradient of immobilized motors and diffusible clustering dynein-like complexes , combined with cortical pushing ( Fig 7 ) , satisfies all experimental measures available . Measuring the localization , density and mobility of dyneins in the mouse oocyte during meiosis I , would be a useful test of the model predictions . While the model is fit to spindle assembly during meiosis I in mouse oocytes , it also predicts the design constraints in terms of MT lengths and the localization , mobility and density of molecular motors when MT radial arrays are required to search space and undergo capture at the cell center .
Recent microscopy based time-lapse measurements of spindle assembly in the absence of pre-existing centrosomes , have improved our understanding of the principles of self-organization at a cellular scale . Mouse oocytes meiosis is one such example , where radial microtubule ( MT ) arrays , or asters , nucleated by MT organizing centers ( MTOCs ) centripetally converge on the central chromatin mass and reorganize to form a bipolar structure . This centripetal motility resembles a biased ‘search-and-capture’ process . Here we attempt to test whether such a bias is necessary and if so , to define the form and nature of the bias . We quantify the statistics of the experimentally measured motility and find MTOC transport involves both “pulling” from the center and “pushing” from the cortex . We hypothesize that the bias consists of a spatial gradient of forces driving this motility . To test this hypothesis , we develop a model of a random walk with drift in the mouse oocyte geometry . By optimizing the functional form of the drift field to experimental data , we then explore which minimal combination of molecular motors and dynamic instability parameters in such a gradient , could result in the generation of asymmetric forces . When minus-end directed dynein-like motors are localized in a gradient around chromatin , it reproduces the experimental spatio-temporal dynamics . By themselves , MT regulatory gradients , clustering motor complexes and cortical pushing fail to reproduce experimental statistics . A combination of the motor-gradient and clustering motors appears to explain all the available experimental statistics . Our findings suggest a possible functional role for previously observed enrichment of dynein around chromatin in mouse oocytes , and address how MTs asters find the center of a large cell , without the predominance of cortical interactions .
[ "Abstract", "Introduction", "Models", "Results", "Discussion" ]
[ "meiosis", "cell", "motility", "cell", "cycle", "and", "cell", "division", "cell", "processes", "condensed", "matter", "physics", "vertebrates", "animals", "xenopus", "germ", "cells", "animal", "models", "oocytes", "model", "organisms", "amphibians", "dyneins", "molecular", "motors", "nucleation", "epigenetics", "chromatin", "research", "and", "analysis", "methods", "chromosome", "biology", "animal", "cells", "proteins", "gene", "expression", "xenopus", "oocytes", "physics", "biochemistry", "cytoskeletal", "proteins", "cell", "biology", "ova", "genetics", "biology", "and", "life", "sciences", "cellular", "types", "physical", "sciences", "microtubule", "motors", "frogs", "organisms" ]
2016
A Motor-Gradient and Clustering Model of the Centripetal Motility of MTOCs in Meiosis I of Mouse Oocytes
Many animal and plant viruses rely on vectors for their transmission from host to host . Grapevine fanleaf virus ( GFLV ) , a picorna-like virus from plants , is transmitted specifically by the ectoparasitic nematode Xiphinema index . The icosahedral capsid of GFLV , which consists of 60 identical coat protein subunits ( CP ) , carries the determinants of this specificity . Here , we provide novel insight into GFLV transmission by nematodes through a comparative structural and functional analysis of two GFLV variants . We isolated a mutant GFLV strain ( GFLV-TD ) poorly transmissible by nematodes , and showed that the transmission defect is due to a glycine to aspartate mutation at position 297 ( Gly297Asp ) in the CP . We next determined the crystal structures of the wild-type GFLV strain F13 at 3 . 0 Å and of GFLV-TD at 2 . 7 Å resolution . The Gly297Asp mutation mapped to an exposed loop at the outer surface of the capsid and did not affect the conformation of the assembled capsid , nor of individual CP molecules . The loop is part of a positively charged pocket that includes a previously identified determinant of transmission . We propose that this pocket is a ligand-binding site with essential function in GFLV transmission by X . index . Our data suggest that perturbation of the electrostatic landscape of this pocket affects the interaction of the virion with specific receptors of the nematode's feeding apparatus , and thereby severely diminishes its transmission efficiency . These data provide a first structural insight into the interactions between a plant virus and a nematode vector . Efficient transmission from host to host by vectors is an important biological feature shared by many animal and plant viruses . Arthropods transmit many viruses to mammals and plants . Examples include highly pathogenic viruses such as Rift Valley fever virus , Dengue virus or Chikungunya virus , primarily transmitted to animals and humans by Aedes spp . mosquitoes [1] , [2] , Tick-borne encephalitis virus transmitted by ticks [3] or Sharka/plum pox virus disease affecting stone fruits and vectored by aphids . In animals , transmission by vectors is limited to some genera such as Alphavirus Flavivirus , Rhabdovirus or Reoviridae and requires a replication cycle in the vector [4] . In contrast , nearly all plant viruses depend on vectors for their transmission . Non-enveloped viruses - the vast the majority of all plant viruses - are generally specifically acquired by their vectors , but do not replicate in them [5] , [6] , [7] , [8] . Over the years , virus transmission has gradually been recognized as a specific process but the molecular mechanisms governing the recognition between a virus and its vector are far from being unraveled . Comparative studies of transmissible and non-transmissible plant virus isolates have led to the identification of determinants in capsid proteins ( CP ) [9] , [10] , [11] , [12] . In addition to the CP , some viruses require additional viral proteins referred to as helper components for their transmission by vectors ( HC ) [7] , [8] , [13] . HCs are viral proteins capable of engaging interactions with the viral CP and putative receptor molecules from the vector . Thus , they act as bridging molecules . Various motifs in CPs or HCs required for transmission are described for a broad range of plant viruses , in particular members of the genera Potyvirus , Caulimovirus and Cucumovirus vectored by aphids . For example , the rod shaped potyviruses have DAG and PTK motifs in their CP and HC-pro , respectively [14] , [15] , [16] . In contrast , in the icosahedral Cucumber mosaic virus ( CMV ) , the CP is the sole viral determinant of transmission [17] . There , the CP that folds into ß-barrel domains exposes a conserved and negatively charged βH-βI loop exposed at the surface of the virion to establish electrostatic interactions with components inside the aphid's mouthparts [18] , [19] . In Cauliflower mosaic virus ( CaMV ) , transmission necessitates two HC proteins named P2 and P3 in addition to the CP . Together these proteins form a transmissible viral complex whose assembly depends on interactions between coiled-coil domains [20] , [21] , [22] and components of the host plants [23] . This complex is thought to be specifically retained in the acrostyle , a specialized anatomical structure in the aphid stylet where virus receptor proteins accumulate [24] , [25] . Less is known about the transmission by ectoparasitic nematodes of soil-borne viruses belonging to the genera Nepovirus and Tobravirus . In the rod-shaped tobraviruses , the partly unstructured C-terminal tail of the CP is necessary but not sufficient to promote transmission and other viral proteins may act as HC [26] , [27] , [28] . In nepoviruses , the CP that assembles into icosahedral particles is the sole viral determinant involved in transmission specificity , as shown for Grapevine fanleaf virus ( GFLV ) and Arabis mosaic virus ( ArMV ) which are transmitted by two different species of Xiphinema nematodes , X . index and X . diversicaudatum , respectively [29] , [30] . Recently , a 3D homology model of GFLV based on the crystal structure of Tobacco ringspot virus ( TRSV ) [31] , revealed the existence of a stretch of 11 amino acids within the BC loop of the B-domain that differs between GFLV and ArMV . The transmission of GFLV by X . index was abolished when this sequence was replaced by the corresponding region from ArMV . Hence , this loop has all the properties of a determinant for GFLV transmission [32] . The general feature that emerges from all these analyses is that transmission of non-circulative plant viruses involves well-defined and precise interactions between viral and vector molecules . In this respect , parallels can be established with virus-receptor interactions used by animal viruses to enter host cells [33] . However , our current knowledge of the vector-assisted transmission of animal or plant viruses lags far behind that of animal virus-receptor interaction whose details are known in some cases up to the atomic resolution . In the coming years the challenge will be to characterize the key molecules of the vectors engaged in transmission and to gain high-resolution structural insights into their interactions with the cognate viruses . To understand the molecular details controlling virus-vector interactions , we have use the model pathosystem GFLV - X . index . Here , we have identified a GFLV variant ( GFLV-TD ) poorly transmitted by X . index that differs from its parent strain ( GFLV-F13 ) by a single Gly297Asp mutation . Using X-Ray crystallography in combination with cryo-electron microscopy 3D reconstruction , we solved the crystal structures of GFLV-TD and GFLV-F13 at 2 . 7 Å and 3 . 0 Å resolution , respectively . These 3D structures highlighted the dramatic effect of a single amino acid substitution in GFLV transmission and helped identify a pocket at the virus surface with predicted function in the specific recognition of GFLV by X . index . Altogether , the presented results give a first structural insight into the molecular mechanism needed for the specific binding of a plant virus to its nematode vector . GFLV strain F13 ( GFLV-F13 ) was first isolated from an infected grapevine in southern France in 1964 [34] . In agreement with its classification in the Nepovirus genus , it contains a bipartite , linear , single stranded positive sense RNA genome . RNA1 plays an essential role in replication and RNA2 is necessary for movement and encapsidation ( Figure 1A ) . Ever since its isolation , GFLV-F13 was propagated by mechanical inoculation of the systemic herbaceous host Chenopodium quinoa . After four decades of successive passages onto C . quinoa , the nematode transmission of varied GFLV-F13 inocula was assessed . This led to the identification of a variant poorly transmitted by X . index named GFLV-TD ( Figure 1B ) . Beside the defect in transmissibility , GFLV-TD was indistinguishable from its wild-type parental strain GFLV-F13 in terms of symptom development on C . quinoa , reactivity to GFLV antibodies in DAS-ELISA and virus purification yields ( data no shown ) . Similarly , in transmission assays ( Figure S1 ) , no difference in the ability of X . index to ingest GFLV-F13 and GFLV-TD was detected by RT-PCR after a monthly acquisition access period ( AAP ) ( Figure 1C , top panel ) . However , at the end of the inoculation access period ( IAP ) , GFLV-TD was not detectable by RT-PCR in X . index ( Figure 1C , bottom panel ) , suggesting that it is poorly or not retained by nematodes . These results were consistent with the transmission deficiency of GFLV-TD likely due to the paucity or incapacity of the virus to be retained by the vector at specific sites within its feeding apparatus . Since the CP is the sole determinant required for GFLV transmission [29] , [30] , the GFLV-TD CP coding sequence was characterized by IC-RT-PCR and sequencing to identify potential amino acid mutations . A single Gly to Asp mutation at position 297 was found . To assess whether this mutation explained the deficiency in nematode transmission of GFLV-TD , it was introduced into the GFLV-F13 RNA2-encoded CP gene by site-directed mutagenesis of the corresponding cDNA infectious clone [35] . Similar to the natural GFLV-TD variant , the site-directed mutant , named GFLV-G297D , was poorly transmitted by X . index ( Figure 1B ) . In addition , GFLV-G297D was not retained by the vector after the IAP , therefore mimicking GFLV-TD ( Figure 1C ) . These results confirm the critical role of Gly297 in GFLV transmission efficiency . To determine their atomic structures , GFLV-TD and GFLV-F13 virions were crystallized as described [36] . Two crystal forms were obtained and analyzed ( Table 1 ) . The asymmetric unit of the GFLV-TD crystal ( PDBid 2Y26 ) contains 20 CP subunits and that of GFLV-F13 contains 60 subunits , i . e . the entire virion . The structure of GFLV-TD was solved by molecular replacement using a cryo-electron microscopy model at 16 . 5 Å resolution ( Figure S2 ) followed by solvent flattening , non crystallographic symmetry ( NCS ) averaging and refinement at 2 . 7 Å ( Table 1 ) . The complete GFLV-TD particle was generated by symmetry operations and used as a model to solve the structure of GFLV-F13 ( PDBid 2Y7T , 2Y7U , 2Y7V ) by molecular replacement at 3 . 0 Å ( Table 1 ) . In both cases , the icosahedral GFLV capsid is formed by 60 copies of the CP arranged according to a pseudo T = 3 symmetry ( Figure 2A ) . The CP folds into three jelly-roll β sandwiches . To follow the TRSV nomenclature , the three jelly-roll domains were named C , B , and A from the N- to C- termini , respectively . Two linking peptides connect the C-B and B-A domains ( Figure 2B ) . The B and C domains clustered at the 3-fold axis . Five A-domains organized around the 5-fold axis form a protrusion at the capsid's surface ( Figure 2A ) . The particle outer radius seen down the 5-fold , 3-fold and 2-fold axes is 155 Å , 141 Å and 130 Å , respectively ( Figure 2C ) . The A-domain deviates most from the β sandwich fold of the other domains with an extensive insertion between the βC and the βD strands that comprises one additional strand ( Figure 3 ) . This is in contrast with the capsid structures of closely related comoviruses where two strands are added at this position [37] . Along each 5-fold axis , i . e . the summit of the pentamers , a channel with an inner diameter of 7 . 1 Å contains an additional electron density that may be attributed to an ion ( Figure 2D ) . However , the distance to the neighboring Lys atoms is incompatible with direct hydrogen or ionic bonding ( Figure 2D ) , and suggests , in agreement with the presence of surrounding density peaks , that the ion is linked via intermediate water molecules . The structural variability of CP subunits within a capsid was very low . The average root-mean-square distances ( r . m . s . d . ) of pair-wise CP superposition were 0 . 07±0 . 01 Å and 0 . 09±0 . 02 Å for GFLV-TD ( 20 CPs ) and for GFLV-F13 ( 60 CPs ) , respectively ( Table S1 ) . The superposition of the GFLV-F13 asymmetric unit ( 20 CPs ) onto one third of the GFLV-TD caspid as rigid blocks , led to an r . m . s . d . of 0 . 4 Å for 10080 Cα positions . Higher deviations were found locally with a maximum distance of 1 . 9 Å at crystal packing contacts . At the level of individual CPs , the two viruses were very similar with an average r . m . s . d . of 0 . 13±0 . 01 Å over 504 Cα atoms ( Table S1 , Figure S3A ) . Overall we could not find any significant conformational change , neither between the two variants , nor inside their respective capsid . GFLV and TRSV are both transmitted by Xiphinema nematodes [38] , [39] . As mentioned above , a 3D model of GFLV based on the crystal structure of TRSV helped identify a region at the virion's surface with function in nematode transmission [32] . As expected from CP sequence homology , the CP of GFLV and TRSV display similar 3D architectures with a good superimposition of the CP folds ( Figure S3B ) . Both virions have about the same outer dimensions but those of TRSV are slightly smaller than those of GFLV . The greatest capsid radius of TRSV measured down the 5-fold , 3-fold and 2-fold symmetry axes is 155 , 137 and 123 Å [31] . Overall contacts between the CP subunits of GFLV are the same as those described for TRSV [31] . Subunit interfaces on the 2-fold and 3-fold axes involve the αA' helix in the C domain and the βHI and βBC loops in the B and C domains , respectively ( Figure S4 ) . The three jelly-roll domains of the GFLV and TRSV CPs are nearly identical , except for the presence of extra α helices and two supplementary β sheets in the GFLV structure ( Figure 3 ) . The independent superimposition of the C , B and A domains showed the A is the most divergent and C domains the most conserved ( Table S1 ) . The most striking difference between TRSV and GFLV is the GH loop located at the outer surface of the B domain . In GFLV this loop is longer and much more prominent than in TRSV ( Figure S3B ) . Also , the N-terminal tail facing the interior of the capsid in TRSV is absent in GFLV ( Figure S3B ) . This tail accounts almost exclusively for the size differences between the two CPs ( 504 residues in GFLV vs 513 in TRSV ) . We previously hypothesized that residues important for transmission are exposed at the virion outer surface [32] . According to the GFLV crystal structures , 381 out of 504 CP residues are accessible to the solvent and 208 of them are located at the surface of the virion ( underlined in Figure 3 ) . Remarkably , among those , residue 297 lies in the most exposed part of the GH loop in the B-domain and is highly accessible to the solvent ( Figure 2B , Figure S5 ) . Sequence information and experimental electron density unambiguously helped identify an Asp side chain at this position in GFLV-TD ( Figure 4 ) . The conformation of the GH loops in the structures from GFLV-F13 and GFLV-TD is nearly identical with a maximum distance of 0 . 18 Å between equivalent atoms ( Figure 4 ) and therefore , cannot account for the loss of GFLV-TD transmission . Consequently , in the absence of major differences between both structures , the addition of a negatively charged side chain per CP resulting from Gly297Asp substitution is presumably responsible for the loss of transmissibility by the nematode . As mentioned above , a stretch of 11 residues within the CP named region 2 ( R2 ) is essential for GFLV transmission by X . index [32] . Knowing that CP amino acid 297 also affects transmission efficiency and that Gly297 and R2 are relatively close together ( Figure S5 ) , we investigated whether both could act synergistically . To address this issue , GFLV amino acid residues in both locations were exchanged by their ArMV counterparts . The single substitution Gly297Ala generated a recombinant named GFLV-G297A and the dual substitution of R2 and Gly297 generated a recombinant named GFLV-R2G297A . Transmission assays showed that GFLV-G297A was transmitted by X . index but not by X . diversicaudatum ( Figure 5 ) . In contrast , GFLV-R2G297A was no longer transmitted by either nematode species ( Figure 5 ) , although virions were ingested by nematodes during AAP ( Figure S6 ) . These results indicate that Gly297 can be substituted by Ala but not by Asp without effect on transmission by X . index . Moreover , the simultaneous substitution of Gly297 and R2 by ArMV sequences is not sufficient to confer transmission by X . diversicaudatum , suggesting that additional residues may be involved . The GFLV structure was inspected in the proximity of the residue Gly297 and of the region R2 to identify additional residues that may act as transmission determinants . Gly297 and R2 are located at the edge of a positively charged pocket within the B-domain , whereas most of the GFLV outer surface is negatively charged ( Figure 6A ) . The walls of this pocket are formed essentially by the GH , BC and C′C″ loops encompassing Gly297 , R2 and the previously defined region R3 [32] , respectively ( Figure 6B ) . The base of the pocket ( Figure 6B , purple residues ) is formed by at least 11 residues deeply embedded in the capsid shell but still accessible to the solvent ( Figure 3 , stars ) . In the crystal structures of GFLV-F13 and GFLV-TD , the residues of the GH , BC and C′C″ loops are well exposed at the outer surface of the capsid ( Figure 3 , Figure S5 ) . This includes the residues Phe188+189 , Thr192+195 and Leu197 from R2 which are different between GFLV and ArMV and may participate in the specific binding of GFLV to X . index ( Figure 3 and [32] ) . Altogether , our data suggest that a positively charged pocket located within the GFLV CP B-domain between the 3-fold and 5-fold axes may constitute a ligand recognition site . GFLV-TD is a natural variant of GFLV-F13 that emerged spontaneously in the greenhouse after multiple mechanical passages in C . quinoa plants over time . Loss of virus transmission is not uncommon under such experimental conditions [12] , [40] , [41] , [42] , [43] . However , to our knowledge this is the first isolation and characterization of a spontaneously occurring transmission-deficient nepovirus . In the case of GFLV-TD , CP sequencing revealed that a single Gly297Asp mutation had occurred . A reverse genetics approach confirmed the involvement of CP residue 297 in the transmission deficiency of GFLV-TD by X . index . In addition , the defect in transmission was correlated with a lack of virus retention by X . index , although virus acquisition by nematodes was not affected . Therefore , Gly297 is a bona fide determinant of GFLV transmission efficiency . The high-resolution structure of GFLV reveals an overall organization well in agreement with its classification in the order Picornavirales within the picorna-like super family [44] , [45] . The GFLV capsid consists of 60 subunits , each containing three distantly related jellyroll domains that may have arisen by triplication of a single copy present in some ancestor virus and subsequent divergent evolution [31] , [46] . The high degree of similarity of the 3D structures of GFLV and TRSV ( Figure S3 , Table S1 ) is in agreement with their classification in the same genus [47] . Yet , the superposition of their capsid proteins is not perfect . This is mainly due to small differences in the orientation of subunits within particles and the length of surface loops , e . g . GH loop in the B-domain . These differences certainly explain why classical molecular replacement using homology models was unsuccessful . Indeed , our initial 3D model of GFLV [32] resembled more TSRV from which it was derived than the actual crystal structure ( Figure S3C ) . In contrast , the 16 . 5 Å cryoEM map of GFLV ( Figure S2 ) rapidly led to an unambiguous solution . Overall , the resulting structures of GFLV-F13 and GFLV-TD have identical architectures although they were determined in different crystalline packings [36] . These findings indicate that particles are quite rigid and , more importantly , that the differential ability to be transmitted is not due to a conformational modification but rather to an alteration of the physical-chemical properties of their outer surface . Single point mutations detrimental to virus transmission often affect highly conserved residues . For instance , single mutations in the conserved HI loop of CMV either reduce or abolish aphid transmission [18] . Also , single mutations in the conserved PTK motif of ZYMV HC-Pro [14] or in the DAG motif of TYMV CP [48] hinder aphid transmission of potyviruses . In GFLV , Gly297 is a highly conserved amino acid of the GH loop and our structure shows that it is very accessible to the solvent . Out of the 238 GFLV CP sequences available to date in GenBank , only three allelic variants exist at this position: Ser297 ( accession number 38604190 ) , Asn297 ( accession number 86450421 ) and Asp297 ( reported for GFLV isolate CACSB5 from California with accession number 299118269 [49] and this work ) . The transmissibility of the Ser297 and Asn297 allelic variants and CACSB5 isolate is unknown . Here we show that the Gly297Asp strongly affects transmission . We also found that the Gly297Ala single mutant ( GFLV-G297A ) is still transmitted by X . index , although Ala is the most frequent residue at position 297 in the CP of ArMV strains . Altogether , this indicates that the nature of the side chain of residue occupying the position 297 is decisive for vector recognition . Since the same structure is observed in GFLV-TD and GFLV-F13 , a conformational effect of the Gly297Asp mutation cannot account for the deficiency in transmission of GFLV-TD . However , the Asp297 side chain could create a steric hindrance and thereby interfere with proper recognition of a ligand within the nematode feeding apparatus . A more likely scenario is that Asp297 perturbs the electrostatic potential at the surface of the virions and their solvation shell via the addition of 60 negative charges in GFLV-TD . A striking consequence of this alteration is a 2 . 5-fold increase of the solubility of GFLV-TD with respect to that of wild-type GFLV-F13 . Another one is the different crystal packing [36] . In the same way , alteration of the electrostatic potential may also impair the binding and retention of GFLV inside the nematode feeding apparatus , thereby reducing its transmissibility . Future work will clarify which hypothesis , electrostatic potential or steric hindrance , contributes most to the loss of transmission of GFLV-TD . Our results show that Gly297 and region R2 are transmission determinants but they cannot alone explain the strict transmission specificity between GFLV and X . index . Thus , these residues may be part of an ensemble of surface residues with ligand binding properties . In view of our structural data , it appears that they are located at the edge of a pocket near the 3 fold axis whose walls are formed essentially by the GH , BC and C′C″ loops within the B-domain . This pocket is remarkable in several respects . First , it is positively charged whereas most of the GFLV outer surface is negatively charged ( Figure 5A ) . Second , all three loops contain residues that are protruding from the capsid outer surface ( Figure 3 , Figure S5 ) and are therefore likely to be recognized by compounds of the nematode feeding apparatus . Finally , these three loops were previously identified for their possible involvement in nematode transmission and the function of region R2 encompassing the BC loop was experimentally proven [32] . For all these reasons , we suggest that this pocket may constitute a ligand recognition site with critical function in GFLV transmission by X . index . We also note that its topology resembles the receptor-binding site of other picorna-like viruses , in particular the heparin binding site of Foot-and-mouth disease virus ( FMDV ) where the pocket occupies a similar position within the icosahedral asymmetric unit ( Figure S7 ) and contains important polar and positively charged residues with ligand binding properties [50] , [51] . Whether the occurrence of negatively charged residues in the pocket is detrimental for GFLV transmission by its vector needs to be confirmed . Indeed , so far only two mutants , namely Phe188Glu ( i . e . the first residue of R2 , [32] ) and Gly297Asp ( described as GFLV-TD in this work ) have been identified in which an alteration of the net electrostatic charge inside the putative ligand-binding pocket was correlated to a defect in virus transmission . This work provides a new framework for further analyses aiming at precisely defining the structure and charge properties of the binding pocket and of its importance for GFLV transmission by nematodes . The knowledge of the underlying molecular mechanisms is a prerequisite for the identification of a ligand within the nematode feeding apparatus and the subsequent development of novel strategies to control virus propagation in vineyards . In conclusion , effective virus transmission from host to host relies on a specific interaction with a vector . Here , we have identified structural features involved in such interaction on the surface of a 30 nm icosahedral nepovirus . We showed that a single mutation ( Gly297Asp ) in the GH loop within the CP B domain is sufficient to diminish GFLV transmission by its ectoparasitic nematode vector X . index . In the absence of any detectable difference in the resolved 3D structures of the wild-type virus and a transmission deficient mutant , we come to the conclusion that the introduction of a negative charge at a precise position in each of the 60 protein subunits of the capsid is sufficient to diminish virus retention inside the nematode's feeding apparatus and thereby hinder virus transmission . We have also delimited a positively charged pocket formed at the surface of the protein capsid which may constitute a binding site for the vector . These findings open new perspectives for the mapping of the ligand recognition site on the virus and the identification of a viral receptor or ligand in the nematode . Providing deeper insights into virus-vector interactions at the atomic level will help understand the origin of the specificity of virus-vector interactions and facilitate the implementation of new strategies to break the viral cycle . GFLV and ArMV strains were isolated from naturally infected grapevines and propagated in the systemic host C . quinoa . Full-length cDNA clones of GFLV-F13 RNA1 and RNA2 are available [35] . They were used to produce RNA molecules by in vitro transcription as described previously [52] . Transcripts of either wild-type GFLV RNA1 and RNA2 or GFLV RNA1 and mutated RNA2 were mechanically inoculated to C . quinoa [35] . Virus infection was assessed in uninoculated apical leaves of C . quinoa plants 2 to 3 weeks post-inoculation by double-antibody sandwich ( DAS ) -enzyme-linked immunosorbent assay ( ELISA ) with specific γ-globulins to GFLV and ArMV . Samples were considered positive if their optical density ( OD405nm ) readings were at least three times those of healthy controls after 120 min of substrate hydrolysis . Viral particles were purified mainly as described in [53] with one additional 60 to 10% ( m/v ) sucrose gradient that was performed at 210 , 000× g in SW41 rotor ( Beckman ) for 2 . 5 h . Purified virions were resuspended in sterile water and filtered through a 0 . 22 µm pore-size Ultrafree-MC membrane ( Millex ) prior to storage at 4°C . Crystallization by vapor diffusion at 20°C in sub-microliter sitting drops and structural analyses were performed as described [36] . Plasmid pVecAcc65I2ABC , carrying a full-length cDNA copy of GFLV RNA2 was used as template for the production of chimeric CP genes harboring a mutated amino acid in position 297 by PCR site directed mutagenesis overlap extension mutagenesis [32] . Plasmid pVecAcc65I2ABCG2 is a derivative of pVecAcc65I2ABC carrying the CP region R2 in position nts 2 , 609–2 , 640 ( nucleotide positions are given according to the GFLV-F13 RNA2 sequence , GenBank accession no . NC_003623 ) [32] . Residue 297 ( corresponding to codon nts 2 , 936–2 , 938 ) was mutated into an aspartic acid , using pVecAcc65I2ABC as template , the mutagenic primer pair mutDF/mutDR and the external primer pair 18/36 ( Table S2 ) . Mutagenic PCR-amplified products were digested with Acc65I ( nts 2 , 678–2683 ) and BglII ( nts 3 , 055–3 , 060 ) and cloned into the corresponding sites in pVecAcc65I2ABC to yield pVecAcc65I2ABCG297D . Residue 297 was mutated into Alanine with the mutagenic primers mutAF/mutAR and the external primers 18/36 ( Table S2 ) ; PCR-amplified products were digested with Acc65I and BglII , and cloned into the corresponding sites in pVecAcc65I2ABC and pVecAcc65I2ABCG2 to yield pVecAcc65I2ABCG297A and [54] pVecAcc65I2ABCG2-G297A , respectively . Each PCR reaction was carried out as described [32] . For simplicity , transcripts and mutant viruses derived from these constructs were referred to as GFLV-G297D ( plasmid pVecAcc65I2ABCG297D ) , GFLV-G297A ( plasmid pVecAcc65I2ABCG297A ) , and GFLV-R2G297A ( plasmid pVecAcc65I2ABCG2-G297A ) . The integrity of all GFLV RNA2 clones was verified by DNA sequencing . Nematode transmission assays were performed in two steps of 4 weeks each , the acquisition access period and the inoculation access period [30] . C . quinoa and Nicotiana benthamiana were used as source and bait plants for transmission assays with X . diversicaudatum and X index , respectively . Transmission tests were performed using 200 nematodes per plant . The presence of GFLV and ArMV was verified in total RNA extracts from nematodes by reverse-transcription ( RT ) -polymerase-chain reaction ( PCR ) as described [30] . The progeny of GFLV RNA2 CP sequence was characterized in infected plants by immuno-capture ( IC ) -RT-PCR and sequencing as described in [29] , except that two cDNA fragments were amplified with primer pairs 397/227 and 115/18 ( see Table S2 ) . Sequences were analyzed with ContigExpress ( Vector NTI Software , InforMax ) . Purified GFLV particles were applied to a quantifoil R 2/2 carbon grid ( Quantifoil Micro Tools GmbH , Germany ) , blotted by filter paper , and flash-frozen in liquid ethane to make a vitreous-ice embedded sample . Electron micrographs were recorded under low-dose conditions at liquid-N2 temperature with a JEOL 2010 operating at 200 kV microscope . Micrographs collected at X 50 , 000 magnification with a defocus range of 1 . 3–2 . 5 µm were digitized on a Nikon Coolscan 9000 ED with a step size of 10 µm . The images were coarsened by a factor of 2 , resulting in a pixel size corresponding to 4 Å at the specimen level . The semi-automatic X3D program ( J . F . Conway ) was used for picking particles . The defocus value was estimated for each micrograph using CTFFIND3 [55] , and phases flipped using CTFMIX [56] . Particle origins and orientations were determined and refined using the model-based orientation determination method [57] . The GFLV reconstruction was determined using as starting model the 3D reconstruction of TRSV filtered at 40 Å resolution . The density map was calculated by Fourier-Bessel formalism as described [57] , and implemented in the EM3DR program . Resolution was estimated using the Fourier shell correlation ( FSC ) criterion with a cutting level of 0 . 5 [58] . The final density map computed at 16 . 5 Å resolution includes 2 , 424 particles extracted from 8 micrographs . X-ray diffraction data from GFLV-F13 and GFLV-TD were collected on crystal-cooled samples ( Table 1 ) at FIP-BM30 beamline ( ESRF , Grenoble , France ) and at X06DA beamline ( SLS , Villingen , Switzerland ) . They were reduced using the XDS package [59] . Diffraction data were phased by molecular replacement using AMoRe [60] followed by non-crystallographic symmetry ( NCS ) averaging and solvent flattening using RAVE [61] , [62] . Attempts to phase data using TRSV-based homology models generated by Modeller [63] were not successful . In contrast , the 3D EM reconstruction led to a clear molecular replacement solution with cubic data in the 30-15 Å resolution range . The orientations of viral particles within the cubic crystal were identified by inspection of the self-rotation function calculated at the highest resolution available ( 4 . 5 Å for GFLV-F13 and 2 . 85 Å for GFLV-TD ) . Self-rotations corresponding to four differently oriented icosahedral particles were found . Calculation of the translation-function using the correctly oriented 3D EM model showed that four icosahedral particles were present in the unit cell , each sharing one of its 3-fold axis with the crystal . The molecular replacement solutions defined the molecular boundaries ( masks ) of the particles within the cubic crystals . Based on the icosahedral symmetry of the 3D EM model , the rigid-body operators relating equivalent regions within the molecular boundaries were defined ( 20 NCS x 3 crystallographic transformations ) . An iterative procedure of phase extension from 16 . 5 Å to the maximum available resolution was then carried out by using density modification techniques , including NCS map averaging , solvent flattening and intermediate steps where the molecular masks and the NCS operators were refined . The incorporation of high-resolution data finally converged to an experimental map at 2 . 85 Å which allowed the rapid rebuilding of GFLV subunit from homology models . The atomic model of GFLV-TD was refined with PHENIX [64] with cubic data reprocessed at 2 . 7 Å resolution . NCS constrains were applied to the ensemble of monomers in the asymmetric unit except three regions which changed conformation due to packing contacts ( Tyr 9 , loops 15–19 and 259–265 ) . Water molecules were added after convergence of capsid refinement . Strong peaks in the difference map were examined in Coot [65] to identify 28 solvent molecules around one monomer A . They were then transferred by symmetry to subunits B-T and a total of 556 solvent sites were assigned in the final model . Strong density peaks were also observed on the 5-fold axes of the capsid indicating the presence of a large ion , possibly a phosphate . A ring of solvent molecules bridging the ion to the CP monomers was clearly seen in 2 out of 4 pentamers of the cubic asymmetric unit . However , this ion could not be explicitly identify ( no exploitable anomalous signal ) and was not included in the model . The structure of the GFLV-F13 particle was solved by MR using the GFLV-TD model and was refined at 3 Å resolution . No solvent molecule was included , since it was not possible at this resolution to describe a common hydration pattern for the 60 viral subunits in the asymmetric unit . The stereochemical quality ( Table 1 ) of final models was assessed with Coot and Procheck [65] and all residues were in the allowed regions of the Ramachandran plot . The totality of the CP amino acids ( 504 residues per subunit ) was observed in both GFLV-F13 and -TD GFLV structures . Atomic coordinates have been deposited in the Protein Databank ( GFLV-TD: pdb ID 2Y26; GFLV-F13: 2Y7T , 2Y7U , 2Y7V ) . GFLV structures were compared with lsqman [61] . R . m . s . d . on Cα positions were calculated for each pairwise superimposition of CPs observed in the cubic ( GFLV-TD ) and in the monoclinic ( GFLV-F13 ) asymmetric units . Average r . m . s . d . were derived from the former analysis and are reported in Table S1 , as well as the r . m . s . d of GFLV CP vs TRSV CP and GFLV CP model based on TRSV . [61] . Solvent accessible surface was calculated with a probe radius of 1 . 4 Å , with the program MSMS [66] . The analysis of the surface potential was performed with APBS [57] , [67] . Figures were prepared using PyMol ( http://www . pymol . org/ ) and Chimera [67] .
Numerous pathogenic viruses from animals and plants rely on vectors such as insects , worms or other organisms for their transmission from host to host . The reasons why certain vectors transmit some viruses but not others remain poorly understood . In plants , Grapevine fanleaf virus ( GFLV ) , a major pathogen of grapes worldwide and its specific vector , the dagger nematode Xiphinema index , provides a well-established model illustrating this specificity . Here , we determined the high-resolution structures of two GFLV isolates that differ in their transmissibility . We show that this difference is due to a single mutation in a region exposed at the outer surface of the viral particles . This mutation does not alter the conformation of the particles but modifies the distribution of charges within a positively-charged pocket at the outer surface of virions which likely affects particle retention by X . index and , thereby also transmission efficiency . Therefore , we propose that this pocket is involved in the specific recognition of GFLV by its nematode vector . This work paves the way towards the characterization of the specific compound ( s ) within the nematodes that trigger vector specificity and provides novel perspectives to interfere with virus transmission .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "plant", "science", "plant", "microbiology", "viral", "transmission", "and", "infection", "virology", "plant", "biology", "biology", "microbiology", "viral", "structure" ]
2011
Structural Insights into Viral Determinants of Nematode Mediated Grapevine fanleaf virus Transmission
Yaws is targeted for eradication by 2020 in the WHA66 . 12 resolution of the World Health Assembly . The objective of this study was to describe the occurrence of yaws in the Americas and to contribute to the compilation of evidence based on published data to undertake the certification of yaws eradication . A systematic review of the epidemiological situation of yaws in the Americas was performed by searching in MEDLINE , Embase , LILACS , SCOPUS , Web of Science , DARE and Cochrane Database of Systematic Reviews . Experts on the topic were consulted , and institutional WHO/PAHO library databases were reviewed . Seventy-five full-text articles published between 1839 and 2012 met the inclusion criteria . Haiti and Jamaica were the two countries with the highest number of papers ( 14 . 7% and 12 . 0% , respectively ) . Three-quarters of the studies were conducted before 1970 . Thirty-three countries reported yaws case count or prevalence data . The largest foci in the history were described in Brazil and Haiti . The most recent cases reported were recorded in eight countries: Suriname , Guyana , Colombia , Haiti , Martinique , Dominica , Trinidad and Tobago , and Brazil . Gaps in information and heterogeneity were detected in the methodologies used and outcome reporting , making cross-national and chronological comparisons difficult . The lack of recent yaws publications may reflect , in the best-case scenario , the interruption of yaws transmission . It should be possible to reach the eradication goal in the region of the Americas , but it is necessary to collect more information . We suggest updating the epidemiological status of yaws , especially in two countries that need to assess ongoing transmission . Twenty-four countries need to demonstrate the interruption of transmission and declare its status of yaws endemicity , and sixteen countries should declare if they are yaws-free . It is necessary to formally verify the achievement of this goal in Ecuador . Yaws is a poverty-related chronic disease characterized by a primary skin lesion ( “mother yaws” ) followed by a secondary skin lesion , latent infection , and a chronic stage which may include a destructive process of bones and joints . [1 , 2] The disease is a contagious non-venereal treponematosis caused by the bacterium Treponema pallidum subspecies pertenue , transmitted by skin contact . The incubation period is 9–90 days , with an average of 21 days . Humans are the only source of infection . There is no natural immunity to yaws , and there is no vaccine to prevent it . [1 , 2] Yaws affects mainly children below 15 years of age ( with a peak between 6 and 10 years ) and sex differences were not described . [3] Early detection and treatment can avoid gross disfigurement , which occurs in about 10% of the cases . [1] Nevertheless , yaws remains a cause of disability and associated stigma in much of the developing world , primarily affecting those who reside in tropical regions , in rural and overcrowded communities , living in substandard hygiene conditions , with lack of knowledge of the risk factors for infection , and limited access to healthcare . [4] Diagnosis should include patient examination and laboratory confirmation with a combination of treponemal and non-treponemal serological tests as the serological tests are indispensable for diagnosing latent disease . It is however also necessary to take into consideration the epidemiological context because the serological tests cannot differentiate between yaws and other treponematoses . [5] In 1950 the World Health Organization ( WHO ) estimated that 50 million people were infected with yaws . [6] A review of historical documents from the 1950s shows that over 85 countries and territories were endemic for this disease . The WHO and the United Nations Children’s Fund ( UNICEF ) provided technical assistance to 46 of these countries between 1952 and 1964 , with the consequent drastic decline of yaws prevalence in the endemic areas . [7] Since then , disease control activities were reduced in most countries , and a surveillance phase began , but yaws has not been eradicated . [6 , 8] Reporting of yaws to the WHO has not been mandatory since 1990 and therefore the availability of up-to-date data on yaws infection is limited . [7] According to WHO , in the Americas , 26 countries were previously considered endemic , and their current status is unknown , seven countries do not have previous history of yaws , and one country–Ecuador–has claimed the interruption of the transmission but it is still necessary to formally verify this achievement . [9 , 10] Treatment with a single dose of oral azithromycin has proven effective [11] and has renewed optimism that eradication can be achieved through a new treatment policy , the so-called “Morges Strategy . ”[2] This should be implemented along with efforts to facilitate access to clean water , improve sanitation , and promote health education within the community . Yaws is targeted for eradication , defined as the complete interruption of transmission ( absence of new cases of yaws ) globally , by 2020 in the WHA66 . 12 resolution of the World Health Assembly ( 2013 ) [12] and by the WHO roadmap on Neglected Tropical Diseases ( 2012 ) . [13] The Directing Council of the Pan American Health Organization ( PAHO ) adopted the eradication goal in the CD55 . R9 resolution and the plan of action for the elimination of neglected infectious diseases and post-elimination actions 2016–2022 . [14 , 15] WHO details the procedures for verification and certification of interruption of yaws transmission . [3] To guide the process towards successful eradication , a better knowledge of the historical and current epidemiological status of yaws in the Americas is needed . This review shall allow formulating recommendations and methodological suggestions to move forward on the certification process in the Region . The objective of this study was to describe the occurrence of yaws in the Americas by age group and by country and to contribute to the compilation of evidence based on published data to undertake the certification of the yaws eradication . A systematic review of the epidemiological situation of yaws in the Americas was performed . An electronic search of the scientific literature published until June 1 , 2017 , was conducted in the following databases: MEDLINE ( PubMed ) , Embase , LILACS ( including SciELO ) , SCOPUS , Web of Science , Database of Abstracts of Reviews of Effects ( DARE ) and Cochrane Database of Systematic Reviews . Experts on the topic were consulted , and institutional PAHO/WHO library databases were reviewed . The search terms used in DARE , Pubmed and EMBASE were “yaws” and “endemic treponematoses” , introduced as MeSH terms or text terms ( all fields ) or as major terms in EMBASE , together with a combination of the names of all countries , capitals , and main cities of the Region of the Americas introduced as text terms . In LILACS the keywords were also entered in Spanish , Portuguese , and French . Search was limited to studies in humans . Details of the search strategy are provided in a supplementary file online . The review was elaborated following the PRISMA ( Preferred Reporting Items for Systematic Reviews and Meta-Analyses ) Statement criteria for reporting systematic reviews . [16] The review protocol was registered in the PROSPERO database ( Reg . N° CRD42017067449 ) before conducting the study . The studies included in this review had to fulfill the following criteria: ( a ) Participants: Persons who have been evaluated clinically or serologically for a diagnosis of yaws . ( b ) Intervention: Clinical evaluation or serological test for yaws . ( c ) Outcomes: Number of suspected or confirmed cases ( according to the WHO case definition ) [2] and/or prevalence of yaws . ( d ) Study Design: Clinical trials , systematic reviews and meta-analyses , cross-sectional studies , observational studies , and reports of cases . The exclusion criteria were: ( 1 ) Studies conducted outside of the Region of the Americas . ( 2 ) Studies published in languages other than the official languages of the PAHO Region ( English , Spanish , Portuguese , or French ) . ( 3 ) Studies presenting data that had already been included in the review due to their previous publication in another article ( duplication ) . Prevalence data were only recorded for studies conducted in the community or studies that reported statistical data from epidemiological surveillance . Two reviewers ( ACZ and VBN ) carried out the study selection independently , with any disagreements resolved by discussion and consensus . Full-text articles of potentially relevant studies selected through title and abstract screening were analyzed . For studies that met the inclusion criteria , data were extracted and entered into a Microsoft Excel database . The following information was collected: number of cases ( per age group if available ) , location , year of sample , and setting . For studies not reporting the year in which the survey was carried out , the year of publication was recorded instead . For studies describing the number of cases or prevalence results by geographical area within several areas of a country or municipality , these data was treated separately rather than as a single data set . Thus , one study may have yielded more than one outcome record . For studies that did not report results by age group , data were recorded for the total of the population . Results were analyzed separately for children ( 0–16 years old ) and for the general population ( includes information from studies that did not report the age of the cases or were conducted in people over 16 years of age ) . Mapping was undertaking using Tableau 10 . 4 . The initial search identified a total of 679 references . After removing the duplicates , 472 unique references ( titles and abstracts ) were screened , and 223 papers were selected for full-text reading . Of these , 148 were excluded mainly because they did not report cases . Agreement between the two reviewers was unanimous for the excluded citations . The PRISMA flow diagram of the search strategy is presented in a supplementary file online . Seventy-five full-text articles published between 1839 and 2012 met the inclusion criteria ( Table 1 ) . Three-quarters of the studies were conducted before 1970 . Epidemiological data were found for 43 countries ( Table 2 and Fig 1 ) . The scientific literature mainly stemmed from Haiti ( n = 11 , 14 . 7% ) and Jamaica ( n = 9 , 12 . 0% ) . Thirteen studies ( 17 . 3% ) reported cases from various countries . More than half of the studies were case series or case reports ( n = 46 , 61 . 3% ) followed by cross-sectional design ( n = 26 , 34 . 7% ) , and three studies ( 4 . 0% ) had a mixed design ( both case-series and cross-sectional design ) . More than half of the studies did not report the age of the cases ( n = 42 , 56 . 0% ) or were conducted in adult population only ( n = 7 , 9 . 3% ) . Twenty-six studies reported cases in children up to 16 years old ( 34 . 7% ) . Categorization into four categories according to age as recommended by the WHO ( 0–4; 5–9; 10–14; ≥15 years old ) was performed in five articles ( 6 . 8% ) . The remaining 21 studies that reported cases in children ( 28 . 0% ) either used other age categories or did not disaggregate the results into age groups . There was a notable heterogeneity in the diagnostic method used: 48 . 0% of the studies ( n = 36 ) performed both clinical and serological diagnosis in combination with or without dark-field or histology examination; 10 . 7% of the studies ( n = 8 ) used solely clinical diagnosis; 8 . 0% of the studies ( n = 6 ) used clinical diagnosis with dark-field or histology examination; one study in children used serological diagnosis exclusively ( 1 . 3% ) ; and five studies reported cases identified through more than one diagnostic algorithm ( 6 . 7% ) . The diagnostic methods were not documented in 19 studies ( 25 . 3% ) . From the 41 studies that mentioned having used a serological test , most used non-treponemal tests ( n = 23 , 56 . 1% ) or combined non-treponemal/treponemal tests ( n = 12 , 29 . 3% ) , and six articles ( 14 . 6% ) did not specify the kind of serological test used . According to the filiation of countries to the PAHO , there are 35 Member States , four Associate Members , and three Participant States with 12 territories in the Region of the Americas . [87] For this study we will call them countries and territories . Information was identified for 43 countries and territories of the Americas ( Table 2 and Fig 1 ) . Yaws case counts were reported in 31 countries: one from North America , five from Central America , seven from Latin Caribbean , five from Andean Area and Brazil , one from Southern Cone , and twelve from the Non-Latin Caribbean . Yaws prevalence data were reported in 20 countries which included Bolivia and Saint Kitts and Nevis . The absence of yaws was reported from 10 countries or territories: Aruba , Bahamas , Belize , Canada , Chile , Curacao , Honduras , Montserrat , Paraguay , and Uruguay . No data were available for seven countries or territories: Bermuda , Turks and Caicos , Bonaire , Saba , Saint Eustatius , Sint Maarten , and the Cayman Islands . Although information for Mexico was not found in this review , according to the information from the PAHO no cases of yaws have ever been reported in Mexico . [82 , 83] The reported number of cases of yaws and the highest prevalence of yaws in general population by country or territory and sample period are summarized in Table 2 and Fig 1 , respectively . Taking into account that three-quarters of the studies were conducted before 1970 , the information was summarized into two groups according to the period ( before 1970 and since 1970 to date ) . General Population includes information from studies that did not report the age of the cases or were conducted in adult population only . Before 1970 ( 32 countries or territories described at least one case in this period ) : In the United States of America , three cases of yaws were reported between 1921 and 1923 . In Costa Rica , a total of 40 cases were described in the province of Puntarenas in 1929 , and six cases were detected at the eastern border of the country between 1951 and 1956 . In El Salvador , one case was reported in 1936 . Guatemala reported a maximum of six cases in San Pablo Jocopilas in 1931 . Nicaragua reported four cases in 1936 . In Panama , the highest case number was 104 cases ( prevalence 17 . 2% ) in Sambu in Chepigana , Darien , in 1949 . In Cuba , an estimated maximum of 4 , 000 cases was recorded in 1953 ( last data available ) , principally in the Eastern Province . The Dominican Republic reported a maximum of 3 , 827 cases in 1955–1956 . Seventeen cases of yaws were observed in the villages of the Maroni Basin tropical rainforest in French Guiana in 1951 , and the last national report from 1954 included eight cases . Guadeloupe had a historic maximum of 501 cases in 1932 , and the last report from 1950–1953 informed of 100 cases ( 0 . 04% of the total population ) . Haiti reported the highest nation-wide prevalence of yaws ( 80 . 0% ) in 1948 and a maximum of 1 , 281 , 666 cases in the period 1950–1954 . Martinique reported six cases between 1949 and 1952 . Puerto Rico reported a maximum of 94 cases in 1936; the last report from 1956 reported no new cases . A yaws prevalence of 2 . 4% in the general population was recorded in the La Paz department in Bolivia in 1946 . Colombia reported a maximum of 68 , 725 cases between 1950 and 1953 on the Pacific Coast and in Chocó . Ecuador reported a maximum of 13 , 651 cases in the Coastal Region between 1950 and 1955 . In Peru , a maximum of 2 , 797 cases was reported from the eastern part of the country in the period 1952–1954 . Venezuela reported a maximum of 10 , 235 cases from 1951 to 1955 , primarily from the States of Miranda , Sucre , Yaracuy , Cojedes , and Carabobo . Brazil reported a maximum of 297 , 681 cases from 12 states ( 197 municipalities ) in 1957 . Most of these cases were concentrated in the Northeastern Region . The highest prevalence rate reached 28 . 4% in Para ( 1956–1959 ) . In Argentina , three cases were reported between 1939 and 1963 . Anguilla reported eight cases in 1902 . Antigua and Barbuda reported a historic maximum of 70 cases in 1954 . Dominica reported a historic maximum of 1 , 469 cases in 1954 . Grenada reported a maximum of 1 , 500 cases ( 7 . 0% of the total population ) from 1950 to 1953 . Guyana reported a prevalence of yaws of 0 . 03% in 1952 and 72 cases in 1954 . Jamaica reported a maximum of 8 , 500 cases in 1955 and the highest prevalence ( 62 . 3% ) was described in St . Thomas , Bath , in 1932 . Saint Kitts and Nevis reported a national yaws prevalence of 5% in a total population of 55 , 000 in 1956 . Saint Lucia reported a historic maximum of 1 , 124 cases in 1954 . Saint Vincent and the Grenadines reported a maximum of 1 , 117 cases ( 22 . 5% of the population ) in 1956 . In Suriname , a historic maximum of 1 , 436 cases was recorded in 1950 . Trinidad and Tobago reported a total of 8 , 069 cases from 1946 to 1953 ( with a prevalence of 0 . 1% in 1952 ) . For the Virgin Islands ( UK ) , sporadic cases of yaws were described in 1956 . Since 1970 ( 19 countries or territories described at least one case in this period ) : Guatemala reported one case in 1975 , and the last update from 1979 reported no cases . Panama reported one case in 1977 , and the last update from 1980 reported no cases . The Dominican Republic reported nine cases in 1971 , and the last update from 1979 reported no cases . In Haiti , the case count decreased from 123 in 1971 to 31 in 1979 ( last data available ) . In Martinique , a peak of 40 cases was recorded in 1975 , and the last report from 1995–1999 cited 13 cases detected in blood donors . Colombia reported 573 cases on the Pacific Coast in 1973 and a prevalence of 0 . 2% in Buenaventura , Cauca Valley , in 1981 . In 1992 , 108 cases were reported , and the last update from 1995 reported no cases . Ecuador reported a maximum of 868 cases in 1975 . Three epidemiological surveys conducted in the same 87 communities from the Santiago Basin Esmeraldas revealed the highest percentage of people affected by yaws in Rocafuerte ( 26 . 7% ) in 1988 and all the communities reported zero cases in 1998 . The last two cases in Peru were diagnosed in 1979 . In Brazil , the number of cases described ranged from two in the state of Rondõnia ( 1972 ) to 2 , 996 in Amazonas ( 1970 ) . The last report from 1977 described 17 cases . Antigua and Barbuda reported nine cases in 1972 , and the last case was reported in 1977 . One case was reported in Barbados in 1982 . Dominica reported 351 cases in 1971 and 28 cases in 1979 ( last report identified ) . Grenada reported 15 cases in 1971 and the last report from 1979 identified no cases . Guyana reported 36 cases in the period 1979–1984 . The last report from 2002 from Mazaruni/Left Bank Essequibo River did not report any new cases . Jamaica reported 62 cases in 1972 , and the last report with no new cases dates from 1979 . Saint Lucia reported 26 cases in 1971 and the last case was reported in 1979 . Saint Vincent and the Grenadines reported 96 cases in 1972 and the last case was reported in 1979 . In Suriname , 45 and 21 cases were reported in 1982 and 1983 , respectively ( last data available ) . Trinidad and Tobago reported a maximum of 1 , 048 cases in 1974 and the last report identified included 123 cases in 1979 . Given the heterogeneity of the age group reporting in children , results were analysed without disaggregating into subgroups of age . Yaws infection in children was described in 12 of the 43 countries or territories in which data were recorded ( Table 3 ) . In the entire study period , the highest case count reported in the community setting was of 42 , 419 children on the Pacific Coast and in Chocó , Colombia ( 1950–1953 ) . The highest prevalence ( 90% ) was found in Brandon Hill , Saint James , Jamaica , in 1932 . In the school setting , the highest case number recorded was 2 , 354 cases from 64 schools in Saint Catherine , Jamaica , in 1932 . The highest prevalence rate reached 70 . 1% ( 824 children ) reported from 29 schools in Cauca , Colombia , in 1937 . The highest number of cases identified in a health facility setting was reported from Port-au-Prince , Haiti , in 1929 ( 1 , 053 children ) . Ecuador has claimed the achievement of the goal . It would be recommendable to reassess the interruption of transmission in children aged 1–5 years in areas were yaws was historically endemic . The epidemiological and historical information supporting the achievement of the interruption of transmission of yaws in the country should be compiled in a dossier and submitted to the WHO for the verification process . Ecuador may be the first country in the Americas to apply the PAHO/WHO procedures for verification and certification of interruption of transmission of yaws . Six countries reported less than ten imported cases before 1970 ( Argentina , 1963; Nicaragua , 1957; Virgin Island ( UK ) 1956; the United States of America , 1947; El Salvador , 1936; and Anguilla , 1902 ) . Also , ten countries reported zero cases before 1970 ( Canada , Belize , Honduras , Chile , Paraguay , Uruguay , Aruba , Bahamas , Curacao , and Monserrat ) . We did not find reports of yaws cases after 1970 in all these countries . Documentation to support that autochthhonous cases of yaws have ever occurred should be compiled and submitted to PAHO/WHO in all these countries along with the evidence that its health and surveillance systems are sufficient to detect any imported yaws case . Cuba , Guadeloupe , Puerto Rico , Costa Rica and French Guiana reported cases , and Bolivia and Saint Kitts and Nevis reported prevalence before 1970 . Peru , Antigua and Barbuda , Barbados , Saint Lucia , and Saint Vincent and the Grenadines have reports of one or two cases of yaws after 1970 , most of them before 1980 . Guyana , Suriname , Dominica , Trinidad and Tobago , Brazil and Martinique reported cases after 1970 , most of them before 1990 . Guatemala , Panama , Dominican Republic , Grenada , Jamaica , and Venezuela have reports of zero cases in studies carried out after 1978 . These countries should review in depth the information at local level , mainly in the municipalities with a history of yaws . These countries should provide comprehensive evidence to support the elimination in a dossier , and declare the status of yaws endemicity indicating whether there is evidence of the interruption of transmission or whether additional assessment needs to be carried out . Although Colombia had the latest publication of yaws in 1992 , the country reported suspected cases between 2014 and 2017 to PAHO/WHO . Haiti also reported cases in 2015 to PAHO/WHO . In these countries , it would be necessary to carry out an assessment including the collection of information to support the absence of the disease , review past and existing records , and conduct clinical and serological surveys in children in previously endemic areas . Countries with confirmed cases should implement the Morges Strategy . For seven countries there was no data available on the occurrence of yaws: Bermuda , Turks and Caicos , Bonaire , Saba , Saint Eustatius , Sint Maarten , and the Cayman Islands . A more in-depth search of information , studies or data published locally should be carried out in each one to decide on next steps . Although Mexico reported no cases of yaws since 2013 to PAHO/WHO , the country should compile all the information to support its current epidemiological status . The proposed classification of countries is intended to encourage countries in the Americas to start reviewing and documenting the current epidemiological situation of yaws . In conclusion , it should be possible to reach the eradication goal in the region of the Americas , but it is necessary to update the epidemiological status and evidence must be compiled to confirm whether the interruption of yaws transmission has occurred in most of the countries .
Yaws is a contagious non-venereal treponematosis caused by the bacterium Treponema pallidum subspecies pertenue , transmitted by skin contact . It is a poverty-related chronic disease characterized by primary and secondary skin lesions , with latent infection and a chronic stage , which could include a destructive process of bones and joints . Early detection and treatment can avoid gross disfigurement and the associated stigma . Currently , the treatment with a single dose of oral azithromycin has proven effective . This systematic review shows that in the Americas there is a need to update the epidemiological situation of yaws and if needed , to implement and optimize the best public health recommended interventions to interrupt transmission and then verify elimination of transmission . Current WHO guidelines define the methodology for monitoring and evaluating yaws control programs . Yearly surveys of pre-school children , though logistically complex , are needed in the post-zero case surveillance .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "clinical", "research", "design", "tropical", "diseases", "geographical", "locations", "north", "america", "treponematoses", "bacterial", "diseases", "research", "design", "age", "groups", "case", "series", "jamaica", "neglected", "tropical", "diseases", "caribbean", "research", "and", "analysis", "methods", "infectious", "diseases", "serology", "south", "america", "serodiagnosis", "haiti", "yaws", "research", "assessment", "people", "and", "places", "colombia", "diagnostic", "medicine", "systematic", "reviews", "population", "groupings" ]
2019
Epidemiological situation of yaws in the Americas: A systematic review in the context of a regional elimination goal
Interferons ( IFN ) exert antiviral , immunomodulatory and cytostatic activities . IFN-α/β ( type I IFN ) and IFN-λ ( type III IFN ) bind distinct receptors , but regulate similar sets of genes and exhibit strikingly similar biological activities . We analyzed to what extent the IFN-α/β and IFN-λ systems overlap in vivo in terms of expression and response . We observed a certain degree of tissue specificity in the production of IFN-λ . In the brain , IFN-α/β was readily produced after infection with various RNA viruses , whereas expression of IFN-λ was low in this organ . In the liver , virus infection induced the expression of both IFN-α/β and IFN-λ genes . Plasmid electrotransfer-mediated in vivo expression of individual IFN genes allowed the tissue and cell specificities of the responses to systemic IFN-α/β and IFN-λ to be compared . The response to IFN-λ correlated with expression of the α subunit of the IFN-λ receptor ( IL-28Rα ) . The IFN-λ response was prominent in the stomach , intestine and lungs , but very low in the central nervous system and spleen . At the cellular level , the response to IFN-λ in kidney and brain was restricted to epithelial cells . In contrast , the response to IFN-α/β was observed in various cell types in these organs , and was most prominent in endothelial cells . Thus , the IFN-λ system probably evolved to specifically protect epithelia . IFN-λ might contribute to the prevention of viral invasion through skin and mucosal surfaces . Type I interferon ( IFN ) , also called IFN-α/β , was originally discovered owing to its potent antiviral activity [1] . Type I IFN was later shown to display pleiotropic activities . It modulates innate and acquired immune responses , cell growth and apoptosis [2] . Type I IFN forms a vast multigenic family [3] . Human and mouse genomes carry 13 or 14 genes coding for closely related IFN-α subtypes [4] , [5] . In addition , they contain genes coding for IFN-β , IFN-κ [6] , IFN-ε/τ [7] and IFN-ω ( human ) or limitin/IFN-ζ ( mouse ) [8] . MuIFN-α subtypes share about 90% amino acid sequence identity with each other and approximately 30% sequence identity with other type I IFN subtypes . Some of these IFNs are glycosylated while others are not [4] , [5] , [9] , [10] . In spite of this remarkable variability , all type I IFN subtypes appear to bind the same heterodimeric receptor [11] , raising the question of the reason for type I IFN gene multiplicity . Some data suggest that various IFN subtypes might exhibit different affinities for each of the receptor subunits and hence , generate signals that could vary in nature , duration , or intensity . For instance , Jaitin and his collaborators reported that IFN-α/β subtypes differ in their affinity for IFNAR1 and that this receptor subunit is the limiting factor for ternary complex formation [12] . Binding to the IFNAR1 subunit would favor signaling pathways leading to antiproliferative activity whereas binding to the IFNAR2 subunit would favor signaling pathways leading to antiviral responses [13] . Such subtle binding differences could explain the few qualitative differences observed in the activity of different IFN subtypes . Alternatively , the multigenic nature of the IFN family could allow individual IFN subtypes to be expressed in a tissue or in a cell-specific fashion . Intriguingly , the multigenic type I IFN system cohabits with the seemingly redundant type III IFN system discovered more recently . Type III IFN ( also called IFN-λ or IL-28/29 ) is structurally and genetically close to the members of the IL-10 family of cytokines but displays type I IFN-like activity [14] , [15] . In humans , 3 genes code for the 3 members of this new family: IFN-λ1 , IFN-λ2 and IFN-λ3 . Among these molecules , only HuIFN-λ1 is glycosylated [14] , [15] . In the mouse , the IFN-λ1 gene is a pseudogene . IFN-λ2 and IFN-λ3 genes encode glycosylated proteins [16] . IFN-λ expression has been shown to depend on the same triggers ( viral infection , TLR ligands ) [17] , [18] and signal transduction pathways [19]–[21] as those inducing type I IFN expression . Type I and type III IFNs bind unrelated heterodimeric receptors . The type I IFN receptor is made of the ubiquitously expressed IFNAR1 and IFNAR2c subunits [22] . The type III IFN receptor is made of the IL-10Rβ subunit which is widely expressed and shared by other IL-10 related cytokines , and of the IL-28Rα subunit which is specific to IFN-λ and responsible for signal transduction [14]–[16] , [23] . Although type I and type III IFN receptors are unrelated , they trigger strikingly similar responses , mostly through the activation of STAT-1 and STAT-2 , and , to a lesser extent , of STAT-3 [14] , [16] , [24]–[26] . Association of phosphorylated STAT-1 and -2 with IRF-9/p48 yields the ISGF3 complex which induces the transcription of hundreds of genes , the so-called “interferon stimulated genes” ( ISGs ) . These ISGs encode proteins such as Mx1 , OAS or IFIT , which mediate the antiviral effects of IFN [27] . IFN-α/β and IFN-λ were also reported to activate the MAP kinase pathway through JNK and p38 phosphorylation . ISGs activated by type I and type III IFNs were found to be similar [25] , [26] . Accordingly , type III IFN was shown to display antiviral [23] , [24] , [28] , [29] , antiproliferative [16] , [30] , and immunomodulatory properties [31] , [32] , similar to those of type I IFN . It has been shown that , in vitro , cell responses to IFN-λ closely depend on the expression of the IL-28Rα receptor subunit [18] , [26] . Overexpression of IL-28Rα in non-responding cells restored the response of these cells to IFN-λ [26] . IL-28Rα expression has been detected in primary keratinocytes and colonic cells , but not in splenocytes , fibroblasts and endothelial cells , indicating that the IFN-λ receptor can be expressed in a cell-specific fashion [16] , [24] . These data suggest that , in vivo , distinct cells or tissues might be targeted by IFN-α/β and IFN-λ . However , few data are available about production of IFN-λ and about the tissue and cell specificity of the response to this IFN in vivo . To examine possible tissue specificity of IFN-λ expression , we compared the expression of type I and type III IFNs in the brain and in the liver , using various viral infection models . To compare the responsiveness of different tissues and cells to type I and type III IFNs , we used a strategy based on in vivo expression of cloned IFN genes . We observed some tissue specificity in the production of type III IFN and a clear tissue specificity in the response to type III IFN . At the cellular level , the response to IFN-λ showed a marked specificity for epithelial cells , thus clearly differing from the response to IFN-α . Currently available in vitro data do not reveal differential expression of type I and type III IFN genes . To test whether some tissue specificity exists in the production of type III versus type I IFN in vivo , we compared IFN-α , IFN-β and IFN-λ expression in the brain and in the liver of mice infected with various RNA viruses: Theiler's virus ( TMEV , the neurovirulent strain GDVII or the persistent strain DA1 ) , LACVdelNSs ( La Crosse virus mutant lacking the IFN-antagonist protein NSs ) , Mouse Hepatitis virus ( MHV , strain A59 ) or Lactate dehydrogenase-elevating virus ( LDV ) . For detection of mouse IFN-λ , we designed new primers that amplify both IFN-λ2 and IFN-λ3 transcripts , but not putative transcripts from the IFN-λ1 pseudogene . For detection of mouse IFN-α , we designed primers that are specific for IFN-α5 ( Table 1 ) . This IFN subtype has been shown to be among the most prominently induced IFN-α subtypes in the brain , after both LACV and TMEV infections [33] . Using the RT-PCR-cloning-sequencing strategy used in the former study [33] , we observed that IFN-α5 was also among the most prominently expressed IFN-α subtypes ( 20 . 4% ) in the liver of MHV-infected mice ( Figure 1 ) . Thus , IFN-α5 expression appears to be a good marker to follow global IFN-α expression in both infected livers and brains . We first analyzed IFN production in mice infected intracerebrally ( i . c . ) with MHV-A59 or intraperitoneally ( i . p . ) with LDV ( Table 2 ) . Following i . c . injection , MHV-A59 can spread within the central nervous system ( CNS ) , by the hematogenous and neuronal routes . The virus can also enter the bloodstream via the disrupted blood-brain-barrier at the inoculation site and reach the liver where it replicates . MHV-A59 strain is known to target a large range of cells including hepatocytes , macrophages ( including Kupffer cells and microglial cells ) , endothelial cells , glial cells and neurons [34] . LDV injected i . p . rapidly infects a population of LDV-permissive macrophages in the mouse [35] . One day post-infection , which corresponds to the peak of viremia , LDV antigen-positive cells have been detected in most organs , including the liver and the leptomeninges of the brain . Subsequently , the virus establishes a persistent infection that is limited by the number of available target cells [36] , [37] . Thus , groups of C57BL/6 mice were infected either i . c . with MHV-A59 or i . p . with LDV , since these infection models allow to compare the IFN responses in the brain and the liver of the same animals . Mice infected with MHV-A59 were sacrificed at 72h post infection , when clinical signs of encephalitis were prominent . LDV-infected mice were sacrificed at 24 hours post infection , which corresponds to the peak of viremia and of IFN expression [36] , [38] . In mice infected with LDV ( Figure 2A ) , we noticed a striking difference in the relative expression of IFN-λ in the brain and in the liver . IFN-λ mRNA was readily detected in the liver but was hardly detectable in the brain ( 1 out of 9 mice had detectable amounts of IFN-λ mRNA in the brain ) . In contrast , IFN-α and IFN-β mRNAs were clearly detected in both the liver and the brain of these mice . The expression of IFN-λ , relative to that of type I IFN was significantly lower in the brain than in the liver ( Table 3 ) . In mice infected with MHV-A59 ( Figure 2B ) , the same trend was observed . The differences were less extensive , yet statistically significant ( Table 3 ) . We then examined , in diverse experimental infection conditions ( see Table 2 ) , whether the same trend of lower relative expression of IFN-λ in the brain than in the liver existed . IFN production was examined in the brain of mice infected with neurotropic viruses ( TMEV-DA1 , TMEV-GDVII , LACVdelNSs ) . At the time point analyzed ( Table 2 ) , both TMEV strains inoculated intracerebrally primarily infect neurons , as do LACVdelNSs inoculated intraperitoneally [39]–[41] . In the brain of mice infected with these viruses , IFN-λ expression was either non-detectable ( TMEV-DA1 ) or very low , compared to that of IFN-α or IFN-β ( TMEV-GDVII and LACVdelNSs ) ( Figure 2C , 2D , 2E , 2F ) . In contrast , in the liver of mice infected i . p . with MHV-A59 , although variation existed between experimental groups , IFN-λ expression was close to or higher than that of IFN-α ( Figure 2G , 2H ) . Taken together , our data suggest that IFN-λ expression ( relative to that of IFN-α/β ) is restricted in the brain as compared to the liver . We next analyzed whether the response to specific IFNs also exhibited some degree of tissue specificity in vivo . To this end , we chose to compare ISGs expression in peripheral organs and in the CNS , after in vivo expression of cloned IFN genes . IFN was expressed in vivo from expression vectors that were electroinjected in the tibialis anterior muscle [42] . An advantage of this technique over the administration of recombinant IFN is that gene products are expected to carry native post-translational modifications like glycosylation . We tested the efficacy of the procedure by following plasmid-driven expression of luciferase , using in vivo imaging . As shown in Figure 3 , luciferase expression was readily detectable in the tibialis muscle after 2 days , and lasted up to 3 or 4 months after a single plasmid electroinjection . Then , to test whether IFN could be expressed in vivo , in this experimental setting , mice were electroinjected in the tibialis anterior muscle , with plasmid DNA coding for MuIFN-α6T ( accession AY220465 ) or for a mutant of this IFN carrying a glycosylation site ( D68N mutation ) . PCR analysis and sequencing of PCR products confirmed that the IFN subtype expressed in the muscle corresponded to the subtype expressed by the injected plasmid ( data not shown ) . Two days and seven days after electroinjection , both glycosylated and non-glycosylated forms of circulating IFN-α6T , expressed from tibialis muscles , induced the expression of various ISGs ( OASl2 , Mx1 , IRF7 and Ifit1 ) in the injected muscle but also in liver , spleen and kidney . ISGs were also upregulated , but to a lesser level , in the brain and in the spinal cord ( Figures 4 and 5 , Tables 4 and 5 , and data not shown ) . When the empty vector was electroinjected , upregulation of ISG expression was detectable in the injected muscle but hardly , if at all , in other tissues . Experiments conducted in IFNAR1-KO mice failed to reveal transcriptional upregulation of ISGs by IFN-α6T ( Figure 5 , Tables 4 and 5 ) , showing that the induction of ISGs , observed in mice carrying the type I IFN receptor gene , was indeed type-I IFN-dependent . Thus , electrotransfer of plasmid DNA in vivo allows the expression of circulating IFN which activates ISG expression in the tissues examined . In this experimental setting , no significant difference was detected between the activities of glycosylated and non-glycosylated forms of IFN-α6T . We used this in vivo expression strategy to compare the tissue specificities of the responses to type I and type III IFNs . Seven days after electrotransfer , we measured , by real-time RT-PCR , ISG expression in the organs of mice that received plasmids coding for either IFN-α6T or IFN-λ3 ( Figures 4 and 5 and Tables 4 and 5 ) . Interestingly , although IFN-α6T induced bona fide ISG expression in all organs tested , response to IFN-λ3 exhibited some tissue specificity . In response to IFN-λ3 , expression of OASl2 ( Figure 4 ) , Mx1 ( Figure 5 ) , and IFIT1 ( not shown ) was close to background in the brain , spinal cord , spleen , liver , and muscle but was detected in the kidney . In different experimental settings ( Table 4 ) , induction of OASl2 expression by IFN-λ3 was ≤3 . 1±0 . 7 in the brain but ranged from 6±0 . 9 to 27±5 . 2 in the kidney . Accordingly , induction of Mx1 expression in mice carrying functional Mx1 alleles was ≤2 . 3±0 . 4 in the brain but ranged from 8 . 4±2 . 4 to 29±0 . 6 in the kidney . Experiments performed in IFNAR1-KO mice ( Figure 5 and Table 5 ) indicated that the induction of ISG expression observed with IFN-λ3 did not depend on the activation of the type I IFN system . In cell lines , the response to type III IFN was shown to be related to the expression level of the α subunit of the IL-28 receptor . Differential expression of IL-28Rα could thus explain the tissue selectivity of IFN-λ responses in vivo . We used real-time RT-PCR to compare the expression levels of IL-28Rα and of the ubiquitously expressed IFNAR1 subunit of the type I IFN receptor , in the brain , liver and kidney . Expression of IFNAR1 and IL-28Rα were influenced neither by IFN-α nor by IFN-λ expression ( Figure 6 ) . In the kidney , which showed good responsiveness to type III IFN , IL-28Rα expression was clearly higher than in brain and liver ( Figure 6 ) . In order to identify the cells responding to type I and type III IFNs in vivo , we performed immunohistofluorescence using Mx1 as a marker of the IFN response . On one hand , we studied the IFN response in the kidney which was found to respond readily to both IFN-α and IFN-λ ( see Figure 4 ) . On the other hand , we examined the IFN response in the brain . In contrast to the kidney , this organ readily responded to type I IFN but hardly responded to type III IFN . In the kidney , IFN-α-induced Mx1 expression was widespread ( Figures 7C , 7E , 7G , and 8A ) . Mx1 labeling was prominent in endothelial cells ( Figures 7C , 7E , 7G ) but Mx1-positive cells also included epithelial cells of the tubules and of the urinary epithelium ( not shown ) . The neighboring adipose tissue was also strongly responsive to IFN-α6T ( Figure 8A ) . In contrast , Mx1 expression in response to IFN-λ was strikingly restricted to epithelial cells ( Figures 7D , 7F ) . Labeling of the urinary epithelium was prominent ( Figure 7H ) ( much stronger than in response to IFN-α expression ) . Glomeruli were negative ( Figure 7D ) . In the cortex and medulla , only epithelial cells were positive . Adipose tissue showed background-like labeling ( Figure 8B ) . In the brain , very few cells responded to IFN-λ , as expected from the very low expression of ISGs in this organ . These cells appeared to correspond to rare epithelial cells of the meninges and to cells of the choroid plexus . In the choroid plexus , the comparison between Mx1 expression in response to IFN-α and to IFN-λ was exemplar ( Figure 8C–F ) . IFN-α induced mostly Mx1 expression in the endothelial cells of the vessels comprised between the two monolayers of cuboidal epithelial cells ( Figure 8C and 8E ) . Some epithelial cells were also Mx1-positive . In response to IFN-λ , Mx1 expression was prominent in epithelial cells but absent from endothelial cells ( Figure 8D and 8F ) . In view of the striking restriction of the IFN-λ response to epithelial cells in the brain and in the kidney , we tested whether the responsiveness of different tissues to IFN-λ would parallel their epithelial nature . Thus , we used real-time RT-PCR to compare , in different tissues , i ) ISG induction in response to systemically expressed IFN-λ versus IFN-α ( Figure 9A ) , and ii ) IL-28Rα versus IFNAR1 expression ( Figure 9B ) . Response of the tissues to IFN-λ ( over IFN-α ) nicely paralleled IL-28Rα ( over IFNAR1 ) expression . Interestingly , tissues like stomach , intestine , skin , and lung , which have an important epithelium component showed the highest IFN-λ over IFN-α responsiveness . The small apparent differences seen between relative expressions of IL-28Rα ( over that of IFNAR1 ) in tissues of gastro-intestinal tract and in lungs or skin were not significant . Also , these differences did not appear when considering IL-28Rα expression alone ( data not shown ) . In contrast , nervous tissues and spleen responded very poorly to IFN-λ and expressed small amounts of IL-28Rα . Surprisingly , the liver responded poorly to IFN-λ and expressed low amounts of IL-28Rα , in spite of the epithelial nature of the hepatocytes . In contrast , the response of the heart was surprisingly high . Many data converge to show that type I IFN can be expressed by virtually all nucleated cells , including some neurons . In contrast , little is known about the specificity of IFN-λ expression . Upregulation of IFN-λ transcription has been shown to depend on the same stimuli , sensors , and signal transduction pathways as those involved in type I IFN production [17]–[21] , [28] . IFN-λ expression has been mainly described in vitro , in MD-DCs , pDCs , macrophages , and in numerous lymphoid , myeloid and epithelial cancer cell lines [18] , [28] . In these studies , IFN-α/β and IFN-λ have been shown to be expressed simultaneously . In MD-DCs and in pDCs , upon influenza A or Sendai virus infection , IFN-α/β and IFN-λ were expressed at the same order of magnitude and with similar kinetics [43] . Our data show that expression of IFN-λ in the central nervous system is minimal , even under conditions of strong IFN-α and IFN-β expression , as those observed after infection by LACVdelNSs or TMEV-GDVII . In contrast , in the liver , IFN-λ was readily expressed after both LDV and MHV-A59 infections . The difference between relative type III and type I IFN expression levels detected in the liver and in the brain was highly significant in the case of C57BL/6 mice infected i . p . with LDV or infected i . c . with MHV-A59 . A similar trend of low relative expression of IFN-λ in the brain was observed with the other infection models ( different viruses and different mouse strains ) . However , our study does not exclude a possible influence of the mouse genetic background in the relative expression of type I and type III IFN genes . Nevertheless , our results show that some differential tissue specificity exists in the production of type I and type III IFNs . This suggests that the molecular pathways leading to type I and type III IFN gene expression vary either qualitatively ( some specific factors required for IFN-λ gene induction ) or quantitatively ( different thresholds of sensors , signal transduction or transcription factors required for the activation of type I and type III IFNs ) . The tissue specificity of IFN-λ production observed in this work probably results from cell type specificity . In vitro , IFN-λ was shown to be notably produced by MD-DCs and pDCs [43] . If these cells are also important IFN-λ producers in vivo , the paucity of DCs , in particular of pDCs , in the CNS might be the reason for the low expression of type III IFN in this organ . In cell lines , IFN-λ responses have been shown to correlate with expression of IL-28Rα . On the basis of IL-28Rα expression and of IFN-λ responsiveness of cell lines and primary cells , it was suggested that IFN-λ could be primarily expressed by cells of epithelial origin . Accordingly , in vivo , IFN-λ proved to be effective against some viruses known to infect epithelial cells such as Herpes simplex virus-2 [17] . Indirect evidence also comes from the fact that Yaba-like disease virus , a virus with tropism for the dermis was found to produce a type III IFN antagonist protein [11] . However , until now , no direct in vivo data identified the cells responding to IFN-λ . Here , we show , by immunohistochemistry , that the response to IFN-λ involves primarily epithelial cells , at least in the kidney and in the CNS . In the kidney , Mx1 expression in response to IFN-λ was notably prominent in cells of the pluristratifiated urinary epithelium . In contrast , endothelial cells which responded nicely to IFN-α failed to respond to IFN-λ . In the choroid plexus of the brain , response to IFN-α was most prominent in endothelial cells and detectable in cuboidal epithelial cells . In contrast , response to IFN-λ was only detectable in cuboidal epithelial cells . At the tissue level , responsiveness to IFN-λ , as measured by ISG induction , correlated with IL-28Rα over IFNAR1 expression . Again , epithelium-rich tissues such as stomach , intestine , skin or lung were responsive to IFN-λ . It is not clear , however , why the liver was not more responsive and why the heart appeared to be as responsive as the lung . IFN-λ was reported to share , with type I IFN , immunomodulatory activities . For instance , IFN-λ was found to modulate the Th1/Th2 balance of the immune responses [32] . However , in agreement with previous studies , our data show that neither endothelial cells nor spleen cells , two important components of homing and activation of immune cells , responded detectably to IFN-λ , though the response of a small cell population could easily have been undetected . It will be of interest to identify the target cells that mediate the immunomodulatory function of IFN-λ . Type I IFN turned out to have much impact on CNS pathologies . On one hand , type I IFN was shown to be instrumental in the resistance of humans and mice to neurotropic viral infections [44] , [45] . On the other hand , type I IFN proved to be beneficial against autoimmune disorders like multiple sclerosis [46] , [47] and the murine experimental autoimmune encephalitis [48] . IFN-β was shown to decrease the relapse rate and disease activity in relapsing-remitting MS [49] . However , exposure to type I IFN can also cause adverse effects . IFN treatment often triggers flu-like symptoms . When prolonged , for instance in the case of hepatitis C treatment , type I IFN treatment can lead to neurological or neuropsychiatric adverse effects like depression [50] , [51] . IFN-λ could represent an interesting alternative to type I IFN . Indeed , IFN-λ appears to activate the same set of genes as type I IFN and most biological functions of type I IFN appear to be shared by type III IFN . We observed that the CNS is both a poor IFN-λ producer and a poor responder to this cytokine . In the CNS , the blood-brain barrier is mostly made of the tight junctions that bridge the endothelial cells and thus prevent the diffusion of metabolites from the blood to the CNS parenchyma . The lack of responsiveness of endothelial cells to circulating IFN-λ could thus explain the global absence of response to IFN-λ in the CNS . In the choroid plexus , however , endothelial cells are fenestrated . In this structure , the blood-brain barrier is formed by the tight junctions occurring between the cuboidal epithelial cells ( Figure 8G ) . Response of these cells to IFN-λ suggests that they express the IFN-λ receptor on their basolateral membrane which is accessible to factors diffusing from the bloodstream . The low responsiveness of the CNS to IFN-λ does not appear to result solely from the combination of the blood-brain barrier and lack of endothelial cell responsiveness . Our RT-PCR data show that expression of the IL-28Rα receptor chain is very low in the entire brain . This suggests that , even in inflammatory conditions ( such as in MS or during viral infection ) known to affect the integrity of the blood-brain barrier , the CNS would be expected to respond poorly to IFN-λ . This fits with the observation that IFNAR1-KO mice ( which have an intact IFN-λ system ) exhibit extreme susceptibility to many neurotropic viral infections [45] . It will be of interest to test whether , owing to the low responsiveness of the CNS , IFN-λ would exhibit less toxicity than IFN-α/β . This might be of interest if the effective targets of the IFN treatment are in the periphery and , of course , responsive to IFN-λ . Although type I and type III IFNs signal through different receptors , these two IFN families share common features . Production of both IFN types can be triggered by the same stimuli and responses of cells to type I and type III IFNs involves the upregulation of the same set of genes . Why these two seemingly redundant systems co-evolved is not fully clear . Previous data based on cell lines and primary cells responsiveness to IFN-λ suggested that a key difference between the type I and type III IFN systems could be the cell specificity of IFN-λ receptor expression [18] , [26] . Our work confirms that , in vivo , a major difference between the type I and type III IFN systems is the cell type-restricted nature of responses to IFN-λ . Type III IFN appears to have evolved primarily as a protection of epithelial cells . However , type I IFN also acts on these cells , leaving open the question of redundancy . On one hand , IFN-λ could be viewed as a leftover of an ancestral antiviral protection system that arose to protect simple organisms . In the evolution , type III IFN-like genes , which occur in the genome of the fish , appear to have preceded type I IFN genes that emerged with the development of birds and tetrapods [52] . Type I IFN would have evolved faster to become the primary antiviral protection system , active in many cell types . In this hypothesis , IFN-λ would only play the role of a back-up system . On the other hand , the co-existence of two systems with overlapping specificities might have been selected because both systems contribute to the protection against live-threatening and/or widespread pathogenic viruses or microorganisms . Our data suggest that the primary function of IFN-λ would be the protection of epithelial structures . Many viruses use epithelial cells as primary replication sites . These include viruses like poxviruses , herpesviruses and influenza virus that could have had enough impact on species populations to drive some evolution of the genomes . The effect of IFN-λ against vaginal infection by HSV-2 [17] , the inverse correlation between rhinovirus-induced IFN-λ expression and viral load in infected volunteers [53] , and the antagonistic activity of Yaba-like virus against IFN-λ [11] , support an active role for this IFN . IFN-λ is thus also expected to contribute to the defense of respiratory epithelia , against influenza virus . Accordingly , recent findings suggest that IFN-λ contributes to the protection of airways against influenza A virus , through induction of Mx gene expression ( Markus Mordstein and Peter Staeheli , unpublished observations ) . IFN-λ might also be instrumental in the early defense of the intestinal mucosa against very common pathogens such as rotaviruses or possibly against bacteria . Further studies are needed to confirm that , in these tissues , the primary targets of IFN-λ activity are also the epithelial cells , and to evaluate how much protection is added by the IFN-λ system to the very potent IFN-α/β system . The notion that some differential regulation exists in the production of type I and type III IFNs might also broaden the range of the response or accelerate the reactivity of the body to some specific pathogens . 3–4 week-old female FVB/N , 129/Sv , C57BL/6 mice ( infection experiments ) and 7–8 week-old female or male FVB/N mice ( electroinjection experiments ) were obtained from Charles River Laboratories or from the animal facility of the Univ . of Louvain , Belgium . Congenic mice carrying a functional Mx1 gene were from the breeding colony of the Univ . of Freiburg , Germany . These mice were BALB . A2G-Mx1 and B6 . A2G-Mx1 ( designated Mx1/WT ) [54] as well as B6 . A2G-Mx1 mice lacking a functional type I IFN receptor ( designated Mx1/IFNAR1-KO ) [55] . Handling of mice and experimental procedures were conducted in accordance with national and institutional guidelines for animal care and use ( Agreement ref . UCL/MD/2006/034 ) . Viruses used in this study were: Theiler's murine encephalomyelitis virus ( TMEV ) persistent strain DA ( DA1 molecular clone ) , and neurovirulent strain GDVII [40] , La Crosse virus deleted from the NSs gene ( LACVdelNSs ) [56] , mouse hepatitis virus , strain A59 ( MHV-A59 ) [57] and lactate dehydrogenase-elevating virus of the Riley strain ( LDV ) [58] . Intracerebral infections ( i . c . ) were done by injection of 40 microliters of serum-free medium containing 103 PFU of TMEV ( GDVII ) , 105 PFU of TMEV ( DA ) , or 2×104 TCID50 of MHV-A59 . Control mice were injected with 40 microliters of serum-free culture medium . Intraperitoneal ( i . p . ) infections were performed by injection of 250 microliters of serum-free medium containing 104 PFU of LACVdelNSs , 2×107 ID50 of LDV , or 1 or 2×104 TCID50 of MHV-A59 . Mice were anesthetized and perfused with PBS before organs harvest . RNA was isolated from organs using the technique described by Chomczynski and Sacchi [59] and reverse-transcribed as previously described [60] . Real-time RT-PCR was performed , as described previously [60] , using SybrGreen and the iCycler or the MyIQ™ apparatus ( Biorad ) . Standards consisted of 10-fold dilutions of known concentrations of murine genomic DNA , of plasmids carrying the PCR fragment of interest ( pCR4-Topo , Invitrogen ) or plasmid pcDNA3-IFN-α5 [10] or pEF-IFN-λ3 [16] ( kindly provided by S . Kotenko ) . Primers sequences and PCR conditions used are presented in Table 1 . The IFN-subtype specificity of primers for IFN-α5 was confirmed . No PCR product was detected when plasmids encoding the other IFN-α subtypes were used as templates . Moreover , when genomic DNA was used as template , the IFN-α5 gene segment was specifically amplified , as confirmed by sequencing of the PCR products . The firefly luciferase gene was cloned from pGL3 ( Promega ) in pcDNA3 ( Invitrogen ) using HindIII-XbaI restriction sites , to yield pCS41 . Plasmid pcDNA3-muIFNα6T [10] was subjected to site directed mutagenesis [61] with oligonucleotide TM439 ( 5′ GGA GGG TTG CAT TCC AAG CAG CAG A 3′ ) to generate the Asp to Asn78 mutant ( D78N ) that carries a N-glycosylation site . The mutated IFN-α6T region was recloned in pcDNA3 and sequenced to make sure that no unexpected mutation occurred during the mutagenesis procedure . MuIFN-λ3 , was cloned from pEF-2-mIFN-λ3 [16] into pcDNA3 ( Invitrogen ) using Asp718-EcoRI restriction sites . The human IFNGR2 signal sequence and the N-terminal FLAG coding sequences present in pEF-2-mIFN-λ3 were replaced by a sequence encoding the wild-type murine IFN-λ3 signal sequence . To this end , the 3′ complementary primers TM723 ( 5′ AAA GGT ACC GCC ACC ATG CTC CTC CTG CTG TTG CCT CTG CTG CTG GCC GCA 3′ ) and TM724 ( 5′ AAA GGA TCC GCT TGG GTT CTT GCT AGC ACT GCG GCC AGC AGC AGA GGC AA 3′ ) were used for PCR and the resulting fragment was cloned in the recombinant plasmid using the Asp718 and BamHI restriction sites . The muIFN-λ3 region was sequenced to make sure that no unexpected mutation occurred during PCR and subcloning steps . The plasmid obtained , pcDNA3-IFN-λ3 , encodes a wild-type muIFN-λ3 with a wild-type signal sequence . A similar procedure was followed to obtain pcDNA3-IFN-λ2 from pEF-2-mIFN-λ2 [16] . Mice were anesthetized with 200 µl of a mix of Medetomidin hydrochlorid 100 µg/ml ( Domitor ) and Ketamine 500 µg/ml ( Anesketin ) given i . m . Before DNA injection , mice were shaved locally , using depilatory cream . 10 µg of endotoxin free plasmid DNA ( Qiagen endofree ) in 25 µl of PBS were injected in the left and right tibialis anterior muscles of the mice . Electric pulses ( 80 V per 4 mm , 8 pulses , 20 msec/pulse , pause: 480 msec ) were then administered using a Cliniporator system ( Cliniporator , IGEA , Carpi , Italy ) equipped with 4 mm electrode plates [62] . For all experiments , conductive gel was used to ensure electrical contact with the skin ( EKO-GEL , ultrasound transmission gel , Egna , Italy ) . Mice were then woken up by i . m . injection of 250 µl of Atipamezol 500 µg/ml ( Antisedan ) . Mice were anesthetized as for DNA electroinjection and given 3 mg of Luciferin ( Xenogen ) in 100 µl of PBS , intraperitoneally . 10 min after luciferin injection , luciferase activity was monitored in vivo using a CCD camera ( IVIS 50 , Xenogen ) [63] . Mice were then woken up , as described above . Mice were anesthetized before being euthanized for organs harvest . They were perfused with PBS . Freshly collected brains and kidneys were immersed in buffered formaldehyde 4% for 24h at room temperature and then embedded in paraffin . Tissue sections of 8 µm in thickness were cut , placed on SuperFrost Plus slides , dried at 37°C overnight , and processed by standard methods for immunohistochemistry . Briefly , sections were deparaffinized , permeabilized for 5 min in phosphate-buffered saline ( PBS ) containing 0 . 1% Triton X-100 , and washed in PBS . Sections were then treated for 90 min at 97°C in sodium citrate buffer 0 . 01 M - pH 5 . 8 , to unmask antigens . Blocking was performed by incubating sections for 1 hour with normal goat Serum ( Sigma ) diluted 1/50 in PBS . Then , immunolabeling was done in blocking solution containing the antibodies . Mx1 protein was detected with rabbit polyclonal antibody AP5 [64] that recognizes the C-terminal 16 amino acids of Mx1 . It was used at a dilution of 1/150 . For immunofluorescent labeling , the secondary antibody ( at 1/800 ) was a goat anti-rabbit antibody coupled to Alexa 488 ( Molecular Probes ) .
Virus-infected cells can secrete interferons ( IFNs ) , cytokines that induce an infection-resistant state in neighboring cells . IFNs are critical to slow down early multiplication of pathogens in the body . Two IFN families exhibiting strikingly similar properties were described: type I IFNs ( or IFN-α/β ) and type III IFNs ( or IFN-λ ) . Our work addressed the question of the redundancy of these two IFN systems in vivo . First , we found that the relative expression of IFN-λ over that of IFN-α/β exhibited some extent of tissue specificity and was low in the brain . Next , we used a strategy based on in vivo expression of cloned IFN genes to compare the responses of different tissues to IFN-α and IFN-λ . As was suggested by previous in vitro work , response to IFN-λ appeared to be restricted to epithelial cells , unlike response to IFN-α which occurred in most cell types . Tissues with a high epithelial content such as intestine , skin or lungs were the most responsive to IFN-λ and expressed the higher amounts of IFN-λ receptor . Our data suggest that the IFN-λ system evolved as a specific protection of epithelia and that it might contribute to prevent viral invasion through skin and mucosal surfaces .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "virology/host", "antiviral", "responses", "virology/animal", "models", "of", "infection", "immunology/innate", "immunity" ]
2008
IFN-Lambda (IFN-λ) Is Expressed in a Tissue-Dependent Fashion and Primarily Acts on Epithelial Cells In Vivo
The multifunctional signaling protein p75 neurotrophin receptor ( p75NTR ) is a central regulator and major contributor to the highly invasive nature of malignant gliomas . Here , we show that neurotrophin-dependent regulated intramembrane proteolysis ( RIP ) of p75NTR is required for p75NTR-mediated glioma invasion , and identify a previously unnamed process for targeted glioma therapy . Expression of cleavage-resistant chimeras of p75NTR or treatment of animals bearing p75NTR-positive intracranial tumors with clinically applicable γ-secretase inhibitors resulted in dramatically decreased glioma invasion and prolonged survival . Importantly , proteolytic processing of p75NTR was observed in p75NTR-positive patient tumor specimens and brain tumor initiating cells . This work highlights the importance of p75NTR as a therapeutic target , suggesting that γ-secretase inhibitors may have direct clinical application for the treatment of malignant glioma . Human malignant glioma ( MG ) is one of the most common primary central nervous system tumors in adults . These tumors are diffuse , highly invasive , with dismal prognosis , and long-term survivors are rare [1 , 2] . MG extend tendrils of tumor several centimeters away from the main tumor mass . These , as well as the recently identified brain tumor-derived stem-like cells [3–6] , herein called brain tumor-initiating cells ( BTICs ) , act as “disease reservoirs , ” rendering these tumors refractory to available treatments such as surgery or radiotherapy [7 , 8] . The highly invasive nature of these tumors is the result of genotypic and phenotypic changes that result in the activation of a number of coordinate cellular programs , including those necessary for migration ( e . g . , motility ) and invasion ( e . g . , extracellular matrix [ECM] degradation ) [9] and changes in pathway signaling that impart resistance to conventional treatments by reducing proliferation and increasing resistance to apoptosis [8 , 10 , 11] . A detailed understanding of the mechanisms underlying this invasive behavior is essential for the development of effective therapies . Several genes , including those that encode uPA/uPAR , ephrinB3/EphB2 , matrix metalloproteinases ( MMPs ) , a disintegrin and metalloproteases ( ADAMs ) , cathepsins , and integrins , have previously been implicated in glioma invasion [12] . More recently , gene expression profiling identified several subclasses of gliomas that separate tumors into good and poor prognosis groups of which diffuse infiltrative gliomas are divided into four such subclasses [13] . One of these four subclasses , designated hierarchical cluster 2B ( HC2B ) , was found to include several genes with specific roles in cell migration and invasion , and membership in this group was found to strongly correlate with poor patient survival . Our understanding of the proteins that initiate , and the pathways that regulate , glioma invasion is continually expanding , such as the recent discovery that CD95 via the activation of the PI3K/Akt/glycogen synthetase kinase ( GSK3β ) pathway regulates glioma invasion [14] . However , despite recent advances and efforts to target these specific molecules or pathways , no clinically relevant agents have been identified as yet . Using a discovery-based approach and a series of functional , biochemical , and clinical studies , we have identified the p75 neurotrophin receptor ( p75NTR ) as a critical regulator of glioma invasion [15] . We found that p75NTR , through a neurotrophin-dependent mechanism , dramatically enhanced migration and invasion of genetically distinct glioma and that robust expression of p75NTR was detected in the highly invasive tumor cell population from p75NTR-positive glioblastoma patient specimens . In this current study , we investigated the mechanism by which p75NTR imparts this highly invasive behavior to malignant glioma , and assessed the use of a clinically applicable agent in abrogating this invasive behavior . p75NTR elicits a large array of diverse biological responses that are regulated by a complex layer of mechanisms . These intricate layers of control have been proposed to explain the variety of cellular effects triggered by p75NTR activation . Key p75NTR signaling pathways already identified include Ras homolog gene family , member A ( RhoA ) , Jun N-terminal kinase ( JNK ) , mitogen-activated protein kinase ( MAPK ) , and nuclear factor κ B ( NFkB ) [16] . These pathways are believed to be activated by upstream proteins that directly associate with various regions of the p75NTR intracellular domain ( ICD ) . These proteins include guanine nucleotide dissociation inhibitor ( RhoGDI ) , ribosome-inactivating protein-2 ( RIP-2 ) , and p75NTR-associated cell death executor ( NADE ) [17–20] , which associate with a region referred to as the “death domain”; Schwann cell factor-1 ( SC-1 ) ; neurotrophin receptor-interacting MAGE homolog ( NRAGE ) ; tumor necrosis factor ( TNF ) receptor-associated factor ( TRAF ) , and neurotrophin receptor interacting factor ( NRIF ) [21–23] , which associate with the juxtamembrane region of p75NTR; and a PDZ-containing protein Fas-associated phosphatease-1 ( FAP-1 ) , which associates with the C-terminal Ser-Pro-Val ( SPV ) [24] . What proteins or biological process are activated by p75NTR , however , is highly cell context specific . In addition to associating with other signaling molecules , p75NTR , similar to amyloid precursor protein ( APP ) and Notch , has been shown to undergo regulated α-secretase and γ-secretase cleavage , referred to as regulated intramembrane proteolysis ( RIP ) . Cleavage of several type-1 transmembrane receptors has been implicated and shown to be necessary in eliciting some downstream biological responses [25–28] . α-Secretase cleavage of full-length p75NTR by a sheddase liberates the extracellular domain ( ECD ) , leaving an unstable membrane-bound C-terminal fragment ( CTF ) that is cleaved by the γ-secretase complex to release an ICD with potential signaling capability [26 , 29] . Here , we show for the first time to our knowledge that regulated intramembrane proteolysis of p75NTR is a requirement for the highly invasive behavior of p75NTR-positive malignant glioma , and designate RIP as a clinical target for the treatment of invasive malignant glioma . In a previous study , our laboratory identified p75NTR as a potent mediator of invasion in human glioma using a novel invasive glioma mouse model generated by serial in vivo selection [15] . In that study , we found that p75NTR was expressed in 22% mid-grade astrocytomas ( two of nine ) and 85% of glioblastoma multiforme ( GBM ) specimens ( 17 of 20 ) , and that the p75NTR-positive glioma cells in the patient tumor cell population were more migratory than the p75NTR-negative glioma cells . Here , we investigate the mechanism underlying this p75NTR-induced invasion . In neurons , p75NTR is a substrate for sequential α- and γ-secretase–mediated intramembrane proteolysis generating 24 kDa CTF and 19 kDa ICD fragments , respectively , and the generation of these fragments are required for some of its biological functions [26 , 28 , 30–34] . We therefore sought to determine whether intramembrane proteolysis of p75NTR occurred in malignant glioma patient specimens . To do this , we assessed whether the generation of the 24-kDa CTF and the 19-kDa ICD occurred in a panel of surgically resected human glioma specimens and normal human brain . Tumor and normal tissue taken at the time of surgery were immediately snap frozen in liquid nitrogen and stored at −80 °C . Frozen tumor tissue was digested in lysis buffer and analyzed by western blots using a p75NTR cytoplasmic-specific antibody that not only detected the full-length p75NTR protein , but also detected p75NTR-positive fragments migrating at 24 and 19 kDa , respectively , in the p75NTR-positive specimens ( eight of nine GBMs and two of five Grade III glioma ) ( Figure 1A ) . Hence , p75NTR processing occurs in human glioma tumors , and this suggested the possibility that p75NTR processing is required for glioma invasion . To address the possible role ( s ) of p75NTR proteolytic processing in glioma cells , we assessed whether the appearance of the p75NTR-positive fragments at 24 and 19 kDa was the result of proteolytic processing of the full-length p75NTR in invading glioma cells . We have previously established the highly invasive glioma cell lines U87R and U251R for which p75NTR accounts for their invasive behavior [15] . The U87R and U251R invasive glioma cells were grown in the absence or presence of the proteasome inhibitor epoxomicin , a compound used to inhibit rapid degradation of proteins often associated with RIP-mediated proteins [26 , 35] . Western blot analysis showed that in addition to the 75-kDa full-length p75NTR protein , 24-kDa and 19-kDa fragments ( Figure 1B , lane 1 and 5 ) were present and stabilized in the presence of 1 μM epoxomicin ( Figure 1B , lane 2 and 6 ) . These results are in agreement with the model that the full-length p75NTR protein is cleaved , releasing the ECD , CTF , and intracellular fragments . Next , we verified that the appearance of the 24-kDa and 19-kDa fragments was the result of sequential cleavage of p75NTR by an α-secretase and then a γ-secretase . First , we determined whether treatment of p75NTR glioma cells ( U87p75NTR ) using the TNF-α protease inhibitor ( TAPI ) -2 , known to inhibit metalloproteases and ADAMs such as tumor necrosis factor-α converting enzyme ( TACE ) [36–38] and previously shown to inhibit the proteolytic processing of p75NTR in neurons [26 , 32 , 33 , 39] , could inhibit p75NTR processing in glioma cells . TAPI-2 inhibited the proteolytic processing of p75NTR as indicated by the lack of CTF and ICD , and abrogated p75NTR-mediated invasion ( Figure S1 ) . Since TAPI-2 has broad specificity , and glioblastomas are known to produce high levels of many proteases , including members of the MMP , ADAM , and ADAMTS families , leaving the exact identity of the α-secretase unclear , we focused our efforts on the second cleavage event . To determine whether the generation of the 19-kDa fragment was the result of cleavage of p75NTR by a γ-secretase , U87R and U251R cells were treated with 2 μM Compound X ( Calbiochem ) , a specific inhibitor of γ-secretase , for 4 h in the absence or presence of epoxomicin . Western blot analysis of p75NTR revealed that in the presence of the γ-secretase inhibitor , an accumulation of the 24-kDa fragment occurred without subsequent cleavage to the 19-kDa ICD , consistent with the release of the ICD of p75NTR by γ-secretase ( Figure 1B , lanes 3 , 4 , 7 , and 8 ) . The role of processing of p75NTR was not limited to a single glioma cell line and was a general mechanism observed in glioma cells established from genetically distinct individuals ( U87p75 , U251p75 , U343p75 , and U118p75 ) . We found that in all p75NTR-positive glioma cell lines , full-length p75NTR was cleaved to generate two fragments of 19 and 24 kDa: ICD and CTF , respectively ( Figure 1C ) . These results demonstrate that regulated intramembrane proteolysis of p75NTR is a global event occurring in highly invasive p75NTR-positive human glioma cells . In neurons , ectodomain shedding of p75NTR by α-secretase and then γ-secretase cleavage to generate an ICD fragment can result in the activation of downstream events [26–28 , 30–34] . To test whether the processing of p75NTR resulting in the release of the ICD fragment has a functional role in glioma invasion , we analyzed in vitro migration and invasion of U87R , U251R , U87p75NTR , and U251p75NTR glioma cell lines using circular monolayer migration assays ( Figure 2A and 2B ) and 3D-collagen invasion assays ( Figure 2C and 2D ) in the absence and presence of the γ-secretase inhibitor , Compound X . p75NTR-mediated glioma migration and invasion were significantly inhibited in the presence of Compound X . In contrast , when the proteasome inhibitor epoxomicin was used to stabilize p75NTR-ICD , a significant increase in migration and invasion was seen ( unpublished data ) , consistent with increased invasion observed when a cDNA construct mimicking the ICD fragment was ectopically expressed in U87 glioma cells ( Figure 3Aand 3B ) . To determine whether γ-secretase inhibition was confined to glioma invasion or had effects on other biological processes , we assessed the effect of γ-secretase inhibition on survival and proliferation of p75NTR-positive glioma cells . No significant change was observed on either survival or proliferation in vitro ( Figure S2 ) . It is well known that γ-secretase has many substrates [40 , 41] . To directly test the role of p75NTR processing in glioma invasion , we constructed cleavage-resistant chimeric proteins of p75NTR by replacing either the transmembrane ( p75FasTM ) or the extracellular stalk domain of p75NTR ( p75FasS ) with equivalent domains from the Fas receptor [39] ( Figure 3C ) . Both p75NTR and Fas receptors are members of the TNF receptor superfamily , and although they each contain similar domains , Fas , unlike p75NTR , does not undergo RIP . Since ectopic expression of p75NTR in the human glioma cells lines U87 and U251 was sufficient to mediate glioma invasion [15] , these cell lines were used as a model system to assess the p75NTR chimeric mutants . U87 and U251 were therefore stably transfected with the cleavage-resistant p75NTR constructs ( p75FasS and p75FasTM ) . To ensure proper function of all p75NTR protein constructs , we assessed their location , topography , and ability to bind neurotrophin in both U87 and U251 glioma cell lines . Receptor orientation and localization at the plasma membrane was confirmed by flow cytometric analysis using a monoclonal antibody specific to the ECD domain of p75NTR ( Figure S3A ) . As expected , all p75NTR constructs were expressed at the plasma membrane with the correct topography . Next , we assessed whether the chimeric constructs could still bind neurotrophin . Previously , we demonstrated that in the absence of p75NTR , glioma cells secrete high levels of brain-derived neurotrophic factor ( BDNF ) protein into the culture medium in vitro . When these same cells express p75NTR , the majority of the BDNF is found to be cell associated , presumably bound to p75NTR [15] . To confirm that the p75NTR cleavage-resistant chimeric forms retained the ability to bind neurotrophin , ELISA assays were performed to detect BDNF expression in the conditioned medium and total cell lysates of U87 and U251 cells expressing p75FL , p75FasTM , p75FasS , and p75CRD130 ( Figure S3B ) . p75CRD130 is a neurotrophin-binding mutant created by inserting four amino acids after amino acid residue 130 [15 , 42–47] . Expression of the chimeric p75NTR proteins ( p75FasTM and p75FasS ) , just like the p75 wild type , resulted in a shift in BDNF localization from the conditioned medium to the cell lysate . This was in contrast to the cells expressing the neurotrophin-binding mutant ( p75CRD130 ) or the empty vector ( pcDNA ) where the bulk of BDNF was detected in the culture medium . These data demonstrate that p75 NTR cleavage-resistant chimeric constructs p75FasTM and p75FasS retained their ability to bind neurotrophin ( Figure S3C ) . Once we confirmed the correct expression and binding of the various p75NTR constructs , western blots using a p75NTR cytoplasmic domain-specific antibody were performed to evaluate proteolytic processing of the various p75NTR receptors ( Figure 3D ) . In cells expressing p75FasS , only the full-length protein was detected , consistent with inhibition of the α-secretase cleavage , whereas the full-length 75 kDa and the 24-kDa fragment were detected in cells expressing the p75FasTM construct corresponding to the ectodomain shedding of p75NTR by α-secretase but with inhibition of the γ-secretase cleavage . Moreover , in the presence of epoxomicin , no additional p75NTR fragments were observed ( Figure S4 ) . These results demonstrate the cleavage-resistant chimeric p75NTR alleles were expressed with correct biochemical characteristics in U87 and U251 glioma cells . In addition , and consistent with the hypothesis that proteolytic processing of p75NTR is required for glioma invasion , only the full-length 75 kDa band was detected in lysates from U87 cells expressing p75CRD130 , a p75NTR construct that was unable to induce glioma invasion [15] . Since we have shown that neurotrophin binding is required for p75NTR-mediated glioma invasion [15] , and the neurotrophin-binding mutant p75CRD130 does not undergo RIP , it would appear that RIP of p75NTR is required for glioma invasion . To determine whether this is in fact true , U87 and U251 cells expressing the p75NTR cleavage-resistant constructs were assessed for their invasive ability using 3D-collegen invasion assays . We found that expression of cleavage-resistant forms of p75NTR ( p75FasS , p75FasTM , and p75CRD130 ) , which prevented receptor proteolysis , blocked p75NTR-mediated glioma invasion ( Figure 4A and 4B ) , providing evidence to support a role for γ-secretase–dependent release of p75NTR ICD in mediating glioma invasion . To determine whether p75NTR processing was required for glioma invasion in vivo , U87 glioma cell lines ectopically expressing p75FasS and p75FasTM were implanted into the brains of immunocompromised ( SCID ) mice . U87 glioma cells expressing full-length p75NTR ( U87p75 ) or control vector ( U87pcDNA ) were used for comparison . Twenty-eight days after implantation , the mice were sacrificed , and frozen brain sections were stained with antibodies against human nuclei , to visualize all glioma cells ( Figure 4C , upper panel ) or with anti-human p75NTR ( Figure 4C , bottom panel ) . Implantation of U87 glioma cells stably transfected with the control pcDNA vector led to the formation of well-circumscribed tumors , while U87 glioma cells ectopically expressing p75NTR formed tumors with highly infiltrative edges . In sharp contrast to the p75NTR-expressing U87 tumors , tumors expressing either p75FasTM or p75FasS formed well-circumscribed tumors similar to the p75NTR-negative tumors ( U87pcDNA ) . Comparable results were seen in three independent experiments . In conjunction with the in vitro data , these data suggest that proteolytic processing of p75NTR is required for glioma invasion in vivo ( Figure 4C ) . It is well known that the microenvironment of tumors can change the biochemical characterization and function of cells . We have demonstrated in vitro that glioma cells expressing p75NTR undergo proteolytic processing to generate first the 24-kDa CTF and then the 19-kDa ICD . To provide evidence that RIP of p75NTR occurs in vivo , 7–9-μm cryosections from mice implanted for 3–4 wk with in vivo–selected U87R and U251R , or ectopically expressing p75NTR , p75FasS , p75FasTM , and pcDNA , were assessed for p75NTR processing by western blot . The 24- and 19-kDa fragments were found in the highly invasive glioma cells , U87R , U251R , and U87p75NTR . In contrast , neither the 24-kDa nor the 19-kDa fragment was seen in cells expressing p75FasS , and as expected , only the 24-kDa fragment was detected in cells expressing the p75FasTM , consistent with their in vitro characterization ( Figure 4D ) . These data further support a role for RIP of p75NTR in glioma invasion . Our data demonstrated that 85% of GBM specimens ( 17/20 ) express p75NTR , that the p75NTR-positive glioma cells in the original patient tumor cell population were more migratory [15] , and that 24- and 19-kDa p75NTR-positive fragments are present in p75NTR-positive primary Grade III and GBM patient specimens ( Figure 1 ) . We therefore wanted to determine whether the appearance of these fragments in the malignant glioma patient specimens was the result of intramembrane proteolysis of p75NTR . To do this , we established primary cultures from human glioma patient tumors . The recent discovery that human stem cell-like tumor cells , termed BTICs , retain characteristics that closely recapitulate the original patient tumor [3–6 , 48 , 49] prompted us to establish the primary patient tumor cultures under neural stem cell–promoting conditions . BTICs share characteristics with neural stem cells ( NSCs ) such as continuous self-renewal , extensive brain parenchymal migration and infiltration , and potential for full or partial differentiation , properties not found in established glioma cell lines [50 , 51] . Operative samples of human GBM were obtained at the time of surgery , and brain tumor sphere cultures were established in NS-A basal medium plus epidermal growth factor ( EGF ) and basic fibroblast growth factor ( bFGF ) ( EF medium ) . Immunocytochemical analysis of BTICs established from five glioma patients expressed the early neural cell progenitor proteins Nestin , Musashi , hSox2 , and CD133 ( J . J . P . Kelly , S . Weiss , P . A . Forsyth , and D . L . Senger; unpublished data ) . In addition , four out of five glioma tumor progenitor cells in vitro expressed high levels of p75NTR as detected by immunocytochemistry ( Figure 5A ) and western blot ( Figure 5B ) . To determine whether p75NTR expressed on the BTICs undergoes RIP , BTICs were grown in the absence and presence of γ-secretase and/or 2 μM epoxomicin . Similar to the glioma cell lines , full-length p75NTR , CTF , and ICD were detected , and the 19-kDa ICD fragment was dependent on γ-secretase cleavage ( Figure 5B ) . We next determined whether the BTICs retained their expression of p75NTR in vivo: BTIC cells were implanted into the brains of SCID mice and allowed to establish for 4–8 wk . Animals were sacrificed , and frozen sections were stained with either an anti-human nuclear antibody ( to identify the human BTICs ) or anti-p75NTR ( Figure 5C ) . All tumors established from BTICs cells showed highly infiltrative tumors , and consistent with the in vitro data , four out of five tumors showed high expression of p75NTR in vivo . p75NTR as a substrate for γ-secretase [26 , 33 , 39] adds to a growing list of proteins shown to be substrates for γ-secretase cleavage , including APP [52–54] , Notch [55 , 56] , and Notch ligands Delta1 and Jagged2 [57] , ErbB4 [58] , CD44 [59 , 60] , and E-cadherin [61 , 62] . Our in vitro data and the recent application of γ-secretase inhibitors ( egs . LY-450139 and LY-411575 ) in advanced clinical trials for Alzheimer disease [63–65] prompted us to investigate the use of γ-secretase inhibitors to treat highly invasive gliomas . Using an intracranial glioma model , we assessed the therapeutic potential of γ-secretase inhibitors . Parallel experiments were performed using the genetically distinct U87p75NTR and U251p75NTR glioma cell lines and the p75NTR-positive BTICs established from a patient GBM . Cells were implanted intracerebrally into SCID mice; and 3 d after implantation for U87p75NTR and U251p75NTR or 5 d after for BTICs , mice were administered subcutaneously ( s . c . ) either 10 mg/kg γ-secretase inhibitor or vehicle control ( corn oil ) once/day for 2–3 wk ( three to five mice/group ) . Tumors were allowed to grow for a total of 4–6 wk , at which time , all animals were sacrificed , their brains removed , frozen in O . C . T . compound , and sectioned . Immunohistochemical staining of the frozen brain sections for anti-human nuclei ( unpublished data ) or p75NTR ( Figure 6A–6C ) showed that animals implanted with U87p75NTR- , U251p75NTR- , or p75NTR-positive BTICs formed tumors with highly infiltrative edges ( Figure 6A–6C; upper panels ) . In sharp contrast , animals implanted with U87p75NTR- , U251p75NTR- , or p75NTR-positive BTICs and given the γ-secretase inhibitor DAPT developed localized tumors with highly demarcated edges ( Figure 6A–6C; lower panels ) . These results strongly suggested γ-secretase inhibition that results in blocking the generation of the p75NTR ICD substantially inhibited the invasive ability of glioma cells in vivo . To establish whether the effects of the γ-secretase inhibition were confined to glioma invasion or had consequences on other biological functions , we assessed the effect of γ-secretase inhibition on glioma cell proliferation in vivo and found no significant change ( Figure S5 ) . The γ-secretase inhibitor had negliable effects on the self-renewal capability of the BTIC line used in Figure 5 ( unpublished data ) . To confirm that administration of DAPT inhibited p75NTR ICD generation in vivo , 7–9 μm cryosections were lysed as described previously , and western blots for p75NTR were performed ( Figure 6D ) . These experiments show the presence of full-length p75NTR , CTF , and ICD in control animals that received s . c . administration of vehicle ( corn oil ) alone . In contrast , western blots of cryosections from animals that received daily injections of the γ-secretase inhibitor DAPT detected only the full-length and CTF fragments of p75NTR . Subcutaneous administration of γ-secretase inhibitor DAPT inhibited the generation of the p75ICD and resulted in a visible accumulation of the CTF . In addition and most importantly , animals bearing U87p75NTR orthotopic xenographs and given daily s . c . injections of the γ-secretase inhibitor DAPT survived significantly longer ( p < 0 . 0001 ) than control animals ( Figure 6E ) , further highlighting the potential use of γ-secretase inhibitors in the clinical treatment of malignant glioma . The p75NTR signaling cascade is a complex signaling axis that depends on numerous factors , including cellular context and specific protein interactions that influence biological outcomes to regulated intramembranous proteolysis of p75NTR . For example , a recent report showed that in primary cultures of cerebellar neurons , p75NTR ectodomain shedding and subsequent γ-cleavage is necessary for the growth inhibitory signal of myelin associated glycoprotein ( MAG ) [33] . Conversely , in retinal ganglion cells , neurotrophin-induced activation of p75NTR was shown to promote neurite growth in a RIP-dependent manner [66] . Ligand-dependent induction of p75NTR cleavage has also been reported in other cell systems , including sympathetic neurons and glial cells [28 , 30 , 34] . Similarly , we have shown that glioma migration is neurotrophin dependent [15] and that this neurotrophin-induced invasion is dependent on RIP of p75NTR . To assess the role of RIP in p75NTR-mediated glioma invasion , we used a pharmacological and molecular approach both in vitro and in vivo to demonstrate that ( 1 ) p75NTR proteolytic processing occurs in glioma cell lines , surgically resected tumor specimens , and BTICs isolated from patient specimens; ( 2 ) cleavage-resistant alleles of p75NTR are insufficient to mediate glioma invasion; and ( 3 ) pharmacological inhibition with a clinically applicable γ-secretase inhibitor results in a dramatic decrease of glioma invasion both in vitro and in vivo and significantly prolonged survival of animals bearing p75NTR-positive intracranial tumors . Together , these data highlight the potential of using pharmacological inhibition to interfere with RIP as a therapeutic intervention for highly infiltrative p75NTR-positive gliomas . One of the initial steps in regulating RIP is the shedding of the ECD by an α-secretase . This shedding event is required for subsequent cleavage of the CTF to generate an ICD . In order to show that both of these proteolytic events were important in the processing of p75NTR , we made a series of chimeric molecules with the Fas receptor , a related family member that does not generate CTF and ICD fragments [39 , 67] . The means by which the ECD is shed from the full-length p75NTR protein and what its biological role is are not fully understood [68–70] . Glioma cells are known to express many proteases , including serine , cysteine , and metalloproteinases that are involved in invasion and tumor progression . The ADAM metalloproteinase disintegrins , including ADAM17 and ADAM10 , have been described as prominent sheddases for p75NTR as well as other transmembrane type-1 receptors such as APP [71–73] , with recent in vivo evidence establishing a correlation with glioma invasion and an increase in ADAM17 under hypoxic stress [74 , 75] . The use of inhibitors targeting these proteinases may thus result in preventing RIP of p75NTR . Here , we have shown that the broad-range metalloproteinase inhibitor TAPI-2 was able to prevent both proteolytic processing of p75NTR in glioma and p75NTR-mediated invasion . Although a possible therapeutic strategy for highly invasive p75NTR-positive tumors , previous clinical attempts to inhibit the protease-rich environment of tumors using broad-spectrum MMP inhibitors have so far proven to be ineffective as anti-cancer agents , with phase II and III trials failing to show efficacy or survival benefit [76 , 77] . The reason for this lack of efficacy may result in part from the fact that glioblastomas produce high levels of proteases , many of which have been suggested to help facilitate tumor cell survival and invasiveness [74 , 78–83] . Attempts , therefore , to inhibit the ectodomain shedding of p75NTR in a clinical setting may prove difficult . The second proteolytic event with possible direct therapeutic importance is mediated by the γ-secretase complex , which is composed of several proteins including presenilin , nicastrin , APH-1 , and presenilin enhancer 2 ( PEN-2 ) [84] . This protein complex is known to be essential in the normal processing of amyloid β-peptides from β-APP . Abnormal accumulation of amyloid β-peptides with the formation of plaques is believed to be the pathogenesis of Alzheimer disease . Given the connection between Alzheimer disease and γ-secretase , there has been great interest in developing compounds that can inhibit this protein complex with some of these compounds already in phase II/III clinical trials [85] . The exact molecular mechanism ( s ) by which the ICD fragment of p75NTR exerts the invasive behavior of glioma cells is unknown . As is the case with the Notch signaling pathway [41 , 86 , 87] , there have been recent studies to suggest that the ICD fragment can translocate to the nucleus , but whether it acts as part of a transcriptional complex is unclear [28 , 30] . In addition , myelin-associated glycoprotein binding to cerebellar neurons induces α- and γ-secretase proteolytic cleavage of p75NTR , and the resulting ICD fragment is necessary for both the activation of the small molecular weight GTPase , RhoA , and inhibition of neurite outgrowth [33] . Whether these processes or others are regulated by the p75NTR ICD fragment in glioma cells remains to be determined . In our present study , we show that neurotrophin-induced p75NTR proteolytic processing is required for p75NTR-mediated glioma invasion in vitro and in vivo . Furthermore , daily administration of the γ-secretase inhibitor DAPT to animals bearing p75NTR-postive intracranial tumors significantly prolonged survival . These results are intriguing and support the possible clinical application of γ-secretase inhibitors for the treatment of these deadly tumors . We cannot , however , exclude the possibility that we are inhibiting the processing of other proteins that may be involved in glioma invasion since γ-secretase is known to mediate the proteolytic processing of several transmembrane proteins [52 , 53 , 55 , 57–61] . The biochemical evidence presented here , however , supports the hypothesis that the anti-invasive effect of γ-secretase inhibition is at least in part the result of inhibition of p75NTR RIP . Moreover , the fact that we did not observe any significant effects on proliferation or survival of the human glioma cells in vivo suggests that the dominant mechanism of activity is the inhibition of p75NTR-mediated glioma invasion . Excitingly , we also found that a large percentage ( four out of five ) BTICs from primary glioma patient tissue express high levels of p75NTR . This rare population of cells with stem-like properties and the ability to repopulate the tumor [3–6] have been shown to be resistant to our current therapies ( radiation and temozolomide ) and thus may represent a “disease reservoir” for these devastating tumors [88 , 89] . Unlike the U87 parental cells , these cells are highly invasive in vivo , and treatment with a γ-secretase inhibitor dramatically blocked their invasive nature ( Figure 6 ) . Several recent studies have demonstrated strong similarities between BTICs and neural stem and progenitor cells [4 , 90 , 91] . However , whether human glioblastoma stem cells arise from mutated neural stem cells or a more mature cell type that acquires self-renewal capacity remains to be determined . Interestingly , a small population of cells ( 0 . 3% ) within the stem cell niche of the adult rat subventricular zone has neurosphere-forming capacity , express p75NTR [92] , and appear to be maintained from birth through adulthood [93–95] . In addition , the more migratory p75NTR glioma cell population in clinical glioblastoma patient specimens also represents a small percentage of the main tumor mass [15] . It is intriguing to note that glioma cells that express high levels of p75NTR seem to possess many characteristics of BTICs , including self-renewal , extensive brain parenchymal migration , and potential for differentiation ( J . J . P . Kelly and S . Weiss , unpublished data ) . Whether p75NTR is an early brain tumor stem cell marker , at least for some GBMs , remains to be determined . In a previous study , we postulated that p75NTR itself may be a valid target for the treatment of glioma , and now we propose that abrogation of the cellular processing of p75NTR represents an additional therapeutic target . Although these inhibitors may have application in malignant glioma , they may have an even broader application for cancer , as p75NTR has also been implicated in other cancers , including melanoma , specifically the more aggressive melanomas that metastasize to the brain [96–98] . Thereby , therapies that target the processing of p75NTR may also be beneficial for other metastatic cancers . The human glioma cell lines U87 , U118 , and U343 were obtained from the American Type Culture Collection . The human glioma cell line U251N was a kind gift from V . W . Yong ( University of Calgary , Calgary , Alberta , Canada ) . All cells were maintained in complete media ( Dulbecco's modified eagle's medium [DMEM] F12 supplemented with 10% heat-inactivated fetal bovine serum [FBS] , 0 . 1 mM nonessential amino acids , 2 mM l-glutamine , and 1 mM sodium pyruvate [Gibco BRL , http://www . invitrogen . com] ) at 37 °C in a humidified 5% CO2 incubator . Cells were passaged by harvesting with trypsin ( Gibco BRL ) at 80%–90% confluence . Stable transfectants of U87 , U251 , U118 , and U343 cells were maintained in identical media with the exception of the addition of 400 μg/ml of G418 ( Invitrogen , http://www . invitrogen . com ) . The human p75NTR expression vector was constructed as described previously [98] . The expression plasmids containing the p75NTR mutants were constructed by subcloning of PCR fragments containing the desired p75NTR sequences . Chimeric proteins were created by replacing either the transmembrane ( p75FasTM ) or the extracellular stalk domain of p75NTR ( p75FasS ) with equivalent domains from the Fas receptor [Figure 3C] as described by Domeniconi et al . 2005 [33] . The neurotrophin-binding mutant that was mutated by a four-amino acid ( ARRA ) insertion after amino acid residue130 was termed p75CRD130 [15 , 42 , 43 , 47] . The p75NTR intracellular domain construct was created using amino acids 236–399 of the wild-type receptor plus a methionine at the amino terminus ( p75-ICD ) . The original p75NTR templates were from B . Hempstead ( p75WT; Weill Medical College of Cornell University , New York , New York ) and M . Chao ( pT3/T7-p75; New York University School of Medicine , New York , New York ) . All constructs were inserted into pcDNA 3 . 1 expression vectors ( Invitrogen ) . The sequences of all the mutant expression plasmids were confirmed prior to stable transfection . Transfection of glioma cell lines was performed as described previously [15] . Briefly , cells to be transfected were seeded at 2 × 105 cells/well in six-well plates , and incubated at 37 °C overnight . Vector DNA was introduced to the cells using FuGENE 6 transfection reagent ( Roche Diagnostic , http://www . roche . com ) according to the manufacturer's instructions . The following day , the medium was changed to fresh complete medium containing the antibiotic G418 ( concentration determined by toxicity curve for each cell line ) to select for those cells that had taken up the vector . The cells were then grown under antibiotic selection until the cells were at confluence . For U87p75NTR , U251p75NTR , U118p75NTR , U343p75NTR , U87p75FasTM , U87p75FasS , U87p75CRD130 , U251p75FasTM , and U251p75FasS transfection , transfected cells were identified by flow cytometry and western blot . The desired cells were washed in ice-cold PBS and lysed by gentle rocking in lysis buffer ( 50 mM Tris-HCl [pH 7 . 4] , 150 mM NaCl , 10 mM NaF , 0 . 02% NaN3 , 0 . 5% sodium deoxycholate , 0 . 1% SDS , 1% Nonidet P-40 , 1% Triton X-100 , 1 mM EDTA , 60 mM β-octyl glucoside , 25 μg/ml aprotinin , 10 μg/ml leupeptin , 3 mM sodium orthovanadate , 1 mM PMSF ) at 4 °C . Cellular debris was removed by centrifugation , and protein quantification was performed using the bicinchoninic acid ( BCA ) assay ( Pierce Biotechnology , http://www . piercenet . com ) . Proteins were resolved on 12% SDS-PAGE gels , and western blots were performed using the following primary antibodies: rabbit polyclonal anti-human p75NTR intracellular domain ( Promega , http://www . promega . com ) , mouse monoclonal anti-human p75NTR ECD ( Upstate Biotechnology ) , mouse monoclonal anti-β-tubulin ( Sigma-Aldrich , http://www . sigmaaldrich . com ) , or mouse monoclonal anti-β-actin ( Cell Signaling Technology , http://www . cellsignal . com ) . The appropriate HRP-conjugated secondary antibody ( Pierce Biotechnology ) was used , and blots were visualized using enhanced chemiluminescence ( Amersham Biosciences ) . A total of 1 × 106 cells stably transfected with p75NTR wild type or p75NTR cleavage-resistant constructs p75FasTM and p75FasS were collected using Puck's EDTA at 37 °C and then washed in PBS containing 1 mM EDTA ( PBS/EDTA ) . Cells were exposed to the monoclonal anti-p75NTR , clone ME20 . 4 ( which recognizes the extracellular domain; Upstate Biotechnology , http://www . upstate . com ) , diluted 1:250 in PBS/EDTA for 30 min on ice . Cells transfected with pcDNA vector alone were used as negative controls . After washing with PBS/EDTA , cells were incubated with Alexa-488 conjugated goat anti-mouse IgG ( Invitrogen/Molecular Probes , http://www . probes . invitrogen . com ) diluted 1:500 in PBS/EDTA for 30 min on ice . Cells were then washed with PBS/EDTA , resuspended in PBS/EDTA , and analyzed using a FACScan flow cytometer ( Becton , Dickinson and Company , http://www . bdbiosciences . com ) . U87 and U251 glioma cells stably transfected with p75NTR wild type or the cleavage-resistant constructs were allowed to condition culture medium for 5 d . The conditioned medium was then collected , centrifuged , and filtered through a 0 . 2-μm syringe filter ( VWR International , http://www . vwr . com ) . The remaining cells were washed with ice-cold PBS , and total cellular lysates were extracted as described for western blot . Protein quantification was performed using the BCA assay ( Pierce Biotechnology ) , and BDNF , nerve growth factor ( NGF ) , or neurotrophic factor 3 ( NT-3 ) ELISA ( R&D Systems , http://www . rndsystems . com ) was performed as per the company protocol . Briefly , MaxiSorp ELISA plates ( Nalge Nunc International , http://www . nalgenunc . com . com ) were coated with monoclonal anti-human BDNF , NGF , or NT-3 ( R&D Systems ) , nonspecific binding was blocked , and then the standards of serial dilutions of recombinant human BDNF , NGF , or NT-3 ( Sigma-Aldrich ) and equal volumes of conditioned medium or equal quantities of lysate were added . Bound antigen was detected using the corresponding biotinylated antibody , streptavidin HRP , and a tetramethylbenzidine substrate ( R&D Systems ) . Absorbance was measured at 450 nm . For in vitro p75NTR cleavage assessment , the desired cells were treated for 4 h at 37 °C and 5% CO2 with the proteasome inhibitor epoxomicin ( 1 μM ) ( Calbiochem , http://www . emdbiosciences . com ) and/or γ-secretase inhibitor Compound X ( 2 μM ) ( Calbiochem ) . DMSO was used as the vehicle control . Cells were then washed one time with cold PBS on ice , lysed in lysis buffer ( 50 mM Tris-HCl [pH 7 . 4] , 150 mM NaCl , 10 mM NaF , 0 . 02% NaN3 , 0 . 5% sodium deoxycholate , 0 . 1% SDS , 1% Nonidet P-40 , 1% Triton X-100 , 1 mM EDTA , 60 mM β-octyl glucoside , 25 μg/ml aprotinin , 10 μg/ml leupeptin , 3 mM sodium orthovanadate , 1 mM PMSF ) at 4 °C with protease inhibitors , and centrifuged for 5 min at 14 , 000×g; supernatants were quantified by BCA assay ( Pierce Biotechnology ) for use in SDS-PAGE . The CTF ( 24 kDa ) and ICD ( 19 kDa ) fragments were detected using an antibody specific to the p75NTR ICD ( Promega ) . Migration assays were performed using a microliter-scale radial monolayer migration assay as described previously [15] . Briefly , ten-well Teflon-masked microscope slides were coated with 20 μg/ml laminin , followed by the addition of 50 μl of medium to each well . Sedimentation manifold ( Creative Scientific Methods , http://www . creative-sci . com ) was placed over the laminin-coated slide . Cells were seeded through the central lumen of the cell sedimentation cylinder at 2 , 000 cells/well ( five wells per cell type/condition ) to establish a circular 1-mm diameter confluent monolayer . Slides were placed on ice for 60 min and then incubate at 37 °C for approximately 6 h . Attachment of the cells was confirmed prior to removing the sedimentation manifold . Once the sedimentation manifolds were removed , cells were given complete medium containing the γ-secretase inhibitor ( Compound X , 2 μM ) . A digital image of the cells was taken ( before migration = 0 h ) using a Zeiss Axiovert 200M inverted fluorescent microscope ( Carl Zeiss , http://www . zeiss . com ) . The cells were then incubated in a humidified chamber at 37 °C and 5% CO2 , and a second digital image was taken 48 h later . Best-fit circles were drawn around the area covered by the cells at the 0 h and 48 h time points , and the actual cell area was determined using Axiovision 4 . 2 imaging software ( Carl Zeiss ) . Quantitative migration scores were calculated as the increase in the area covered by the cells beyond the initial area of the cells . To test the invasive ability of the p75NTR cleavage-resistant constructs , actively growing glioma cells U87 and U251 stably transfected with p75NTR and p75NTR cleavage-resistant constructs were suspended in a collagen gel solution and plated in transwell chambers with 8 . 0-μm pore size polycarbonate membrane ( Costar , http://www . costar . com ) . The collagen gel was prepared by mixing collagen solution ( Chemicon International 3D Collagen cell culture system , Cat# ECM675 , http://www . chemicon . com ) with 5× DMEM F12 medium on ice . Neutralization solution ( 40:1 ) and extracellular matrix ( ECM ) proteins were added at a concentration of 10 μg/ml ( laminin , fibronectin , chondroitin sulfate proteoglycan , Chemicon ) . A total of 1 × 105 cells were suspended in 350 μl of collagen gel solution , and 70 μl of the collagen/cell mixture was pipetted into the Transwell chambers ( five chambers for each cell line ) . Chambers were immediately transferred to a 37 °C incubator for 60 min to allow the matrix to polymerize . Once polymerized , 100 μl of serum-free DMEM was added to the upper chamber and 1 . 0 ml of 10% FBS complete medium with the γ-secretase inhibitor Compound X ( 2 μM ) was added to the lower chamber . Transwell chambers were kept at 37 °C for 6 h , at which time the chamber was washed with PBS , fixed with acid-alcohol for 15 min at room temperature , and then stained with hematoxylin . Any cells remaining in the top chamber were removed , and membranes were mounted on glass slides . Four different fields were counted for each membrane . Six- to 8-wk-old female SCID mice were purchased from Charles River Laboratories ( http://www . criver . com ) . The animals were housed in groups of three to five and maintained on a 12-h light/dark schedule with a temperature of 22 °C ± 1 °C and a relative humidity of 50% ± 5% . Food and water were available ad libitum . All procedures were reviewed and approved by the University of Calgary Animal Care Committee . Actively growing glioma cells stably transfected with p75NTR and p75NTR cleavage resistant constructs were harvested by trypsinization , washed , and resuspended in sterile PBS ( 137 mM NaCl , 8 . 1 mM Na2HPO4 , 2 . 68 mM KCl , and 1 . 47 mM KH2PO4 [pH 7 . 5] ) . These cells were implanted intracerebrally into the right putamen of SCID mice ( 1 × 105 cells/mouse ) at a depth of 3 mm through a scalp incision and a 0 . 5-mm burr hole made 1 . 5–2 mm right of the midline and 0 . 5–1 mm posterior to the coronal suture . All mice were anaesthetized by intraperitoneal administration of ketamine ( 85 mg/kg ) plus xylazine ( 15 mg/kg ) ( MTC Pharmaceuticals ) . The stereotactic injection used a 5-μl syringe ( Hamilton Co . , www . hamiltoncompany . com ) with a 30-g needle mounted on a Kopf stereotactic apparatus ( Kopf Instruments ) . After withdrawal of the needle , the incision was sutured . Animals were sacrificed at specific time points ( generally weekly , from 2–6 wk postinjection ) or when they lost 20% of their body weight or had difficulty ambulating , feeding , or grooming . For some experiments , BrdU was given by intraperitoneal injection 24 h prior to sacrifice . Following sacrifice , the brains were removed , frozen in Tissue-Tek O . C . T . compound ( Electron Microscopy Sciences , http://www . emsdiasum . com ) , and cryo-sectioned into 7–9-μm sections for examination by immunohistochemistry and in vivo p75NTR proteolysis assessment . Frozen sections were air-dried at room temperature , fixed with cold acetone , and then rinsed with PBS . Endogenous peroxidases in the sections were inactivated with 0 . 075% H2O2/methanol , and nonspecific binding was blocked with 10% normal goat serum in PBS . The sections were incubated with rabbit polyclonal anti-human p75NTR ICD antibody ( Promega ) or mouse monoclonal anti-human nuclei ( Chemicon ) in blocking buffer overnight at 4 °C . Following washing with PBS , the appropriate biotinylated secondary antibody ( Vector Laboratories , http://www . vectorlabs . com ) was applied . Avidin-biotin peroxidase complexes were then formed using the VECTASTAIN Elite ABC kit ( Vector Laboratories ) and detected by addition of SIGMAFAST DAB ( 3 , 3′-diaminobenzidine tetrahydrochloride ) ( Sigma-Aldrich ) , which was converted to a brown reaction product by the peroxidase . Toluidine blue ( for frozen sections ) was used as a nuclear counterstain . Sections were then dehydrated in an ethanol/xylene series and mounted with Entellan ( Electron Microscopy Sciences ) . For detection of p75NTR proteolytic processing in vivo , the desired cells were implanted intracerebrally into SCID mice as described previously . Mice were sacrificed 3–4 wk later . Following sacrifice , the brains were removed , frozen in Tissue-Tek O . C . T . compound ( Electron Microscopy Sciences ) , cryosectioned into 7–9-μm sections , and alternating sections were stained with toluidine blue . Based on the size of tumor , cryosections were lysed in 2× loading buffer ( 0 . 1 M Tris-HCl [pH 6 . 8] , 4% SDS , 20% glycerol , 10% β-mercaptoethanol , 0 . 02% bromphenol blue ) . Proteins were resolved on 12% SDS-PAGE gels , and western blots were performed using an anti-p75NTR cytoplasmic specific antibody ( Promega ) . Tumor and normal tissues were obtained from the Canadian Brain Tumor Tissue Bank in London , Ontario , and the Brain Tumor Tissue Bank at the Clark Smith Brain Tumor Center within the Southern Alberta Cancer Research Institute . Briefly , tissue was taken during surgery while patients were under a general anesthetic , and was placed immediately in liquid nitrogen and stored at −80 °C . An institutional ethics board approved the collection and use of all of the surgical tissue used , and all of the patients gave signed informed consent . Frozen sections of patient tumor tissue were lysed in lysis buffer ( 50 mM Tris-HCl [pH 7 . 4] , 150 mM NaCl , 10 mM NaF , 0 . 02% NaN3 , 0 . 5% sodium deoxycholate , 0 . 1% SDS , 1% Nonidet P-40 , 1% Triton X-100 , 1 mM EDTA , 60 mM β-octyl glucoside , 25 μg/ml aprotinin , 10 μg/ml leupeptin , 3 mM sodium orthovanadate , 1 mM PMSF ) with protease inhibitors on ice using a homogenizer ( Life Technologies ) . Lysates were centrifuged for 5 min at 14 , 000×g to remove debris , and supernatants were quantified by BCA assay ( Pierce Biotechnology ) . In this study , based on our previous immunohistochemistry results of p75NTR expression in GBM patient specimens , western blot analysis was performed on nine GBMs and five mid-grade glioma samples using an antibody specific for the intracellular domain of p75NTR . Tumor and normal tissues were obtained from the Tumor Tissue Bank in Foothills Hospital , Calgary , Alberta . Operative samples of human gliomas were obtained during brain tumor surgery and transported to the laboratory in serum-free DMEM-F12 . Primary cultures of brain tumor-initiating cells ( BTICs ) were established . Briefly , necrotic and connective tissue and any blood clots were removed using forceps , and the remaining tissue was washed in PBS and cut into pieces of approximately 1 mm3 . The tissue was then incubated for 5–10 min at 37 °C in an enzyme cocktail of trypsin ( 0 . 25% ) and DNase I ( 10 μg/ml ) in PBS . The digested tissue was strained through a 100-μm mesh and washed with PBS . Following lysis of the red blood cells , the remaining cells were washed with PBS and strained through a 40-μm mesh . After spinning at 1 , 000 rpm for 5 min , cells were resuspended in stem cell medium ( M medium ) or stem cell medium plus EGF and bFGF ( EF medium ) . M medium is NeuroCult NS-A basal medium ( human ) 450 ml plus NeuroCult NS-A Proliferation Supplements ( human ) 50 ml ( StemCell Technologies ) . EF media is M media plus human recombinant EGF ( 20 ng/ml; Sigma ) and bFGF ( 20 ng/ml; Chemicon ) . Eight-well LAB-TEK chamber slides ( Nalgel Nunc , http://www . nuncbrand . com ) were coated with poly-l-ornithine ( Sigma ) and incubated at 37 °C for 1 h . The desired BTICs were plated into chambers with stem cell culture medium to equilibrate overnight at 37 °C , 5% CO2 . Chambers were then rinsed with PBS , fixed in 3 . 7% paraformaldehyde diluted in PBS for 20 min , and rinsed twice with PBS . Anti-p75NTR cytoplasmic specific antibody ( 1:3 , 000 , Promega ) and antibodies to the progenitor markers: Nestin ( 1:1 , 000 ) , hSOX2 ( 1:5 , 000 ) , and mushashi ( 1:200 ) ( R&D System ) were diluted in 0 . 3% Triton X-100/PBS/10% goat serum , and 200 μl of these solutions were added to each chamber , incubated overnight at 4 °C . Following washing with PBS , the appropriate Cy-3– or FITC-conjugated secondary antibodies ( 1:2 , 000 ) ( Cedarlane , http://www . cedarlanelabs . com ) were applied and incubated for 30 min in the dark at room temperature . The chambers were removed , and slides were mounted with DAPI counterstained mounting medium ( Vector Laboratories ) and imaged with an Olympus IX70 Delta Vision RT microscope and the SoftWoRx software package . Based on the immunocytochemistry staining results , BTICs were collected , dissociated by polished glass pipette , aliquoted into six-well plates , and treated with the proteasome inhibitor epoxomicin ( 1 μM ) ( Calbiochem ) and/or the γ-secretase inhibitor Compound X ( 2 μM ) ( Calbiochem ) , or DMSO vehicle alone , for 4 h at 37 °C and 5% CO2 . Cells were then washed twice with cold PBS on ice , lysed in lysis buffer with protease inhibitors , and quantified by BCA assay . Western blots for p75NTR using a p75NTR cytoplasmic-specific antibody were performed . Actively growing glioma cell line U87p75 and BTICs were implanted intracerebrally into SCID mice as described previously . Three days later for the U87p75 cell line , and 5 d later for BTICs , mice were administered s . c . vehicle ( corn oil ) or 10 mg/kg γ-secretase in corn oil once/day for 2 wk ( U87p75NTR ) or for 3 wk ( BTIC ) . At 3 wk for animals bearing U87p75NTR tumors or 4 wk for animals bearing BTIC tumors , animals were sacrificed , the brains were removed , frozen in Tissue-Tek O . C . T . compound , and cryosectioned into 7–9-μm sections . The cryosections were used for tumor immunohistochemistry staining and for assessment of in vivo p75NTR cleavage . For survival studies ( eight animals per group ) , U87p75NTR glioma cells were implanted intracerebrally into SCID mice . Animals were given daily s . c . injections of 10 mg/kg γ-secretase inhibitor DAPT or vehicle ( corn oil ) alone , once/day beginning on day 3 . Animals were followed until sacrifice was required . Statistical analysis of data was performed using GraphPad Prism software ( GraphPad Software ) . Survival curves were generated using the Kaplan-Meier method . The log-rank test was used to compare the distributions of survival times . A p-value of less than 0 . 05 was considered statistically significant .
Despite technical advances , clinical prognosis of patients with malignant glioma , with an average survival of less than one year , has not changed . The highly invasive nature of these tumors , together with the recently identified brain tumor-initiating cells , provide disease reservoirs that render these tumors incurable by conventional therapies . Here , we present the first evidence to our knowledge that regulated intramembrane proteolysis of the neurotrophin receptor p75NTR is a critical regulator of glioma invasion . Inhibition of this process by clinically relevant γ-secretase inhibitors dramatically impairs the highly invasive nature of genetically distinct glioblastomas and brain tumor-initiating cells and prolongs survival . These data highlight regulated intramembrane proteolysis as a therapeutic target of malignant glioma and implicate the application of γ-secretase inhibitors in the treatment of these devastating tumors .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "cell", "biology", "neurological", "disorders", "neuroscience" ]
2008
Gamma-Secretase Represents a Therapeutic Target for the Treatment of Invasive Glioma Mediated by the p75 Neurotrophin Receptor
Climate warming is predicted to increase the frequency of invasions by pathogens and to cause the large-scale redistribution of native host species , with dramatic consequences on the health of domesticated and wild populations of plants and animals . The study of historic range shifts in response to climate change , such as during interglacial cycles , can help in the prediction of the routes and dynamics of infectious diseases during the impending ecosystem changes . Here we studied the population structure in Europe of two Microbotryum species causing anther smut disease on the plants Silene latifolia and Silene dioica . Clustering analyses revealed the existence of genetically distinct groups for the pathogen on S . latifolia , providing a clear-cut example of European phylogeography reflecting recolonization from southern refugia after glaciation . The pathogen genetic structure was congruent with the genetic structure of its host species S . latifolia , suggesting dependence of the migration pathway of the anther smut fungus on its host . The fungus , however , appeared to have persisted in more numerous and smaller refugia than its host and to have experienced fewer events of large-scale dispersal . The anther smut pathogen on S . dioica also showed a strong phylogeographic structure that might be related to more northern glacial refugia . Differences in host ecology probably played a role in these differences in the pathogen population structure . Very high selfing rates were inferred in both fungal species , explaining the low levels of admixture between the genetic clusters . The systems studied here indicate that migration patterns caused by climate change can be expected to include pathogen invasions that follow the redistribution of their host species at continental scales , but also that the recolonization by pathogens is not simply a mirror of their hosts , even for obligate biotrophs , and that the ecology of hosts and pathogen mating systems likely affects recolonization patterns . Understanding the dynamics of emerging infectious diseases and their routes to colonize new geographic regions is a major challenge for ecologists in an effort to prevent negative impacts upon human , domestic , and natural populations . Because pathogens causing emerging diseases have not coevolved with the host or the ecosystem in which they emerged , they may be more likely to pose a threat to biodiversity through biomass loss and extinction of host species than those responsible for endemic diseases [1] . In recent years , concerns about emerging diseases have been increasing in light of the first evidence of a current period of global climate change . Indeed , the increase of average temperatures in many areas of the world is thought to promote the expansion of exotic pathogens [2] . In particular , invasion by fungal pathogens is a major concern in agricultural and biodiversity management , as they infect many crops and wild plants [3] , [4] . About 30% of emerging infectious diseases of plants are caused by fungi , and the change of environmental conditions is thought to be the major driver of fungal invasions [1] and disease outbreaks [5] . Fungal disease outbreaks in humans have also been suggested to be linked to climate change [6] , [7] . Warmer and wetter conditions favour the growth and transmission of fungal pathogens , and host shifts often occur in conjunction with episodes of global climate change [8] . Based on current trends , emerging infectious diseases caused by fungal pathogens are likely to increase in the near future , with significant severe ecological , economic and social consequences . One way to predict the invasion routes and dynamics of emerging infectious diseases in response to current climate warming is to study the past migrations of pathogens and their hosts during historic periods of climate changes . During the last glacial maximum , the Arctic ice sheet extended into a large part of Europe and limited the survival of most organisms into Southern Mediterranean refugia ( i . e . , Iberia , Italy and the Balkans [9] , [10] ) . As the climate warmed and the ice sheet retreated , many species that had persisted inside the glacial refugia experienced massive migrations into the newly available temperate territories [11] . Such processes are expected to lead to a strong , large-scale geographic structure of genetic variation , consistent with what is observed in many widespread European plants ( e . g . [12]–[17] ) . Genetic differences between spreading populations are likely to result from both natural selection and stochastic processes in small populations . Successive founder events during the process of range expansion are expected to lead to a loss of variation and further divergence between lineages derived from different refugia [9] , [18]–[21] . Few studies have investigated whether the population structures of pathogens have also been impacted by the glaciations in Europe ( but see e . g . [22]–[25] ) . In the case of host-pathogen systems , comparative phylogeography can also provide insights into host and pathogen co-evolutionary histories and identify causal factors determining their combined distributions [26]–[28] . In fact , pathogen populations are often more differentiated than their hosts , and the study of pathogens can complement or improve our knowledge on the host population genetic structure [29]–[37] . The extent to which the phylogeographic structure of pathogen populations mirrors that of the host depends on the degree of specificity and the obligate nature of pathogenic interaction [38] . A significant co-structure between the populations of the host and the pathogen suggests that the distribution and migration of the host impose a major constraint on the distribution of the pathogen [8] . On the other hand , the absence of congruence in population structure is consistent with independent host and pathogen colonization routes . In addition to pathogen specialization , the hosts' niche breadth and demographic characteristics may affect the persistence of disease and opportunities for host range expansion during large-scale migrations that follow climate change [39]–[41] . Thus , an approach that integrates knowledge of host and pathogen biology is essential to many theoretical and applied issues related to disease emergence in response to climate change . Microbotryum violaceum sensu lato is a species complex of basidiomycete fungi responsible for anther smut disease in many plants in the Caryophyllaceae . These fungi are obligate pathogens that sterilize their hosts . Infected plants contain fungal teliospores in place of the pollen and female structures do not mature; female plants in dioecious species also develop spore-bearing anthers . Teliospores are transmitted from diseased to healthy plants mostly by insects that normally serve as pollinators . Therefore , the dispersal routes of the host's pollen and of the pathogen's spores are constrained by the same vectors . Plants also disperse by seed , while the fungus is not vertically transmitted , resulting in higher genetic differentiation in the pathogen than in the host [42] . The sibling species encompassed in Microbotryum violaceum sensu lato [43]–[49] show strong host specificity [45] , [47] , [50] . The most widely studied species are Microbotryum lychnis-dioicae [51] ( called MvSl in [46] and hereafter ) and M . silenes-dioicae [51] ( called MvSd in [46] and hereafter ) , which infect respectively Silene latifolia ( white campion ) and S . dioica ( red campion ) . These two closely related host-pathogen systems are interesting models for studying the combined demographic histories of pathogens and their hosts because ( i ) populations of this pathogen are more differentiated than those of its hosts [42] , ( ii ) the fungus is completely dependent on its hosts and the same vectors disperse the fungus and the host pollen , ( iii ) these Microbotryum species are highly host specific in the field ( [52] ) , ( iv ) Silene and Microbotryum species have similar generation times ( one per year [53] , [54] ) , ( v ) there has been no attempt to control the disease because it affects plants without economic interest , and ( vi ) Silene and Microbotryum are model organisms for a variety of topics in ecology and evolution , with therefore numerous studies available on their life-history and ecology [55] . Recent studies on the phylogeographic history of the two host plants showed genetic evidence of post-glacial recolonization from Mediterranean refugia . In S . latifolia , analyses of chloroplast DNA ( cpDNA ) polymorphism showed clearly structured haplotype variation in Europe , with haplotypes from Eastern and Western Europe forming divergent groups descended from haplotypes currently distributed in southern Europe , and in particular from the Iberian and Balkan Peninsulas [56] . The phylogeography of S . dioica in Europe has been less well studied , although the pattern of cpDNA polymorphism was also suggestive of post-glacial recolonisation from multiple refugia [57] , [58] . A goal of the current study was therefore to determine the extent to which population structure of Microbotryum species parasitizing S . latifolia and S . dioica showed similar patterns of post-glacial history . We also investigated whether life history differences between the two host species constrained the distributions of the pathogens within the host migration pathways . S . latifolia and S . dioica differ with respect to their ecologies , which might strongly impact the genetic structure and diversity of their specialized pathogens . S . latifolia has an extensive range and occurs in most of Europe , as well as in Middle Asia and the Steppe area of south Siberia [59] . This plant is found mainly in open areas , such as hedgerows and in arable fields , therefore often experiencing extinction-recolonisation events in frequently disturbed habitats . In contrast , the distribution of S . dioica covers mainly Central , Northern , and Western Europe [59] , but not the Mediterranean regions . This plant is found in meadows , cliffs , moist forest , and mown pastures at higher elevations , preferring colder and more humid habitats than S . latifolia , and experiencing more stable population dynamics [59]–[62] . It has been suggested that these differences in host life history have affected the distribution of genetic diversity at a small geographical scale in the pathogen species , with lower microsatellite variation and higher differentiation among populations in the anther smut fungus parasitizing S . latifolia than in the fungus parasitizing S . dioica [63] . It is likely that the phylogeographic structure of the European populations of the two pathogen species will also be influenced by differences in the dynamics of the host-pathogen systems . We therefore determined the population structures of the Microbotryum species infecting S . latifolia and S . dioica using microsatellite markers in order to address the following specific questions: ( i ) Do the phylogeographical structures of the Microbotryum species show signatures of post-glacial recolonisation of Europe , and in particular from Southern refugia ? ( ii ) do the population structures of the two pathogens differ from each other , and if so , are these differences consistent with expectations based upon known ecological differences of their plant hosts ? ( iii ) are the phylogeographic patterns of Microbotryum species comparable at a continental scale to those of their respective hosts ? Among Microbotryum samples collected on S . latifolia and on S . doica across Europe ( Figure S1 ) , analysis of variation at 11 microsatellite markers revealed that both pathogen species displayed much lower levels of heterozygosity than expected under Hardy-Weinberg Equilibrium ( HWE ) . The dataset included 701 MvSl individuals from 187 localities and 342 MvSd individuals from 68 localities , where hybrids and cross-species disease transmission between MvSl and MvSd identified in a previous study [52] were removed from the dataset . Descriptive statistics on the polymorphism of MvSd and MvSl and on deviations from HWE are shown in Table 1 and additional details are given in Text S1 and Tables S1 and S2 . MvSl for instance exhibited only 3% of heterozygous genotypes while 73% were expected under HWE , which is consistent with the high selfing rates previously reported in Microbotryum . One marker , SL19 , showed extreme FIS values in MvSl , between −1 and 1 , and was almost fixed in the heterozygous state in MvSd ( Table 1 ) . Analyses were therefore performed with and without this marker for subsequent analyses , but the results were highly similar . For MvSl , multiple estimates of the genetic structure at the European scale showed the existence of at least three to five strongly supported clusters , i . e . populations genetically differentiated from each other . We used the model-based Bayesian clustering algorithms implemented in STRUCTURE , InStruct and TESS . The program STRUCTURE assumes a model with K clusters , each of which being characterized by a set of allelic frequencies . Assuming HWE and linkage equilibrium among loci within clusters , the program estimates allelic frequencies in each cluster and the proportion of ancestry from the different clusters in each individual . The program InStruct is an extension of the approach implemented in STRUCTURE , relaxing the assumption of HWE within clusters . InStruct instead jointly estimates selfing rates and individual membership on the basis of selfing rates , and is therefore well suited to selfing organisms such as Microbotryum . TESS is another extension of STRUCTURE , incorporating a spatial component into the clustering algorithm , so that geographically closer individuals are a priori more likely to belong to the same cluster . This may help revealing subtle geographical structure [64] . We attempted to identify the number of clusters ( K ) that best described the population structure using ( 1 ) the probability of the data under the considered value of K , i . e . Ln ( Pr ( X|K ) ) , and its rate of change when increasing K; and ( 2 ) the Deviation Index Criterion ( DIC ) , i . e . a model-complexity penalized measure of how well the model fits the data . For MvSl , the programs STRUCTURE and InStruct showed that values of DIC decreased and LnP ( X|K ) increased from K = 1 to 10 ( Figures S2a–c ) , indicating that increasing the number of clusters continuously improved the fit of the model to the data . However , the variation in LnP ( X|K ) showed a marked break at K = 5 in STRUCTURE analyses , with a much weaker increase of probability with increasing K afterwards ( Figures S2a and b ) . The inclusion of space in the clustering modelling , as implemented in TESS 2 . 3 , resulted in minimal DIC values at K = 5 and K = 6 ( Figure S2d ) . Increasing K above 5 may therefore add little information for understanding large-scale population structure in Europe , although it would likely reveal a genuine population structure , relevant at smaller scale . The admixture proportion ( α ) between clusters was low , as shown by the mean α = 0 . 033±0 . 000 over all the runs between K = 2 to 15 ( 10 replicates for each K ) in the STRUCTURE analysis . This indicates that most of the genotypes are drawn from a single cluster , with little admixture among clusters ( see Figure S3 for K = 5 ) . There is therefore almost complete lack of gene flow among clusters . Replicates conducted for each of the three algorithms showed dominant and minor modal solutions for membership probabilities ( Figure S4 ) . However , the dominant clustering solutions recovered from the three analyses ( InStruct , STRUCTURE and TESS ) were highly similar ( see Figure S3 for K = 5 ) . The three methods were therefore congruent in their inference of the population structure of MvSl in Europe . The differences between the dominant and minor modal solutions most often corresponded to a genetic structure appearing at higher K values ( Figure S4 ) . For instance , the Italian cluster was assigned to the Eastern group at K = 2 in the dominant solution , and to the Western group in other simulations . Figure 1 shows the maps of mean membership probabilities per locality for MvSl genotypes from the InStruct analysis for K = 2 to 5 . At K = 2 , the analyses revealed a clear West-East partitioning . Simulation of a third cluster separated the Italian genotypes from the Eastern group . At K = 4 , the Western cluster was subdivided into two clusters , one with a more northern distribution ( blue , called hereafter Northwestern and abbreviated as Nwestern ) and the other more to the south ( yellow , called hereafter Southwestern and abbreviated as Swestern ) . At K = 5 , the Eastern group splitted into two clusters , one bordering the Balkan peninsula ( red , called hereafter the Balkan cluster ) and one spreading toward Eastern Europe and Russia ( purple , called hereafter the Eastern cluster ) . When increasing K , further clusters were identified , without evidence of admixture , and corresponding to more local geographical regions: for instance the UK became isolated , and then the most eastern part of Europe ( Figure S4 ) . We also applied a Principal Component Analysis ( PCA ) on the microsatellite allele frequencies , which is a multivariate approach that does not rely on any model assumptions . It instead transforms a number of possibly correlated variables into a smaller number of uncorrelated components , the first principal components accounting for as much variability in the data as possible . The PCA fully recovered the population structure inferred by the three Bayesian clustering methods , as shown by the first four PCs , which explained 35% of the total variance in allelic frequencies ( Figures S5 and S6 ) . The clusters displayed large and significant differences in allelic frequencies ( global FST = 0 . 38 , 95% CI: [0 . 29–0 . 46] , P<0 . 001 for all pairs of clusters ) . The Nwestern and Swestern clusters showed the lowest differentiation ( FST = 0 . 24 ) while the Balkan and Swestern clusters were the most different ( FST = 0 . 47 ) . The clusters also differed significantly with respect to their genetic diversities ( Table 2 ) , with the Italian cluster displaying significantly higher gene diversity ( He ) than the Balkan , Eastern and Nwestern clusters ( Wilcoxon Signed Rank ( WSR ) tests , P = 0 . 008 , P = 0 . 033 , and P = 0 . 026 , respectively , Table 2 ) . The Balkan cluster exhibited a significantly lower allelic richness ( number of alleles controlling for differences in sample size ) than the Eastern and Italian clusters ( P = 0 . 016 and P = 0 . 003 , respectively ) , while the others had intermediate values . Within clusters , significant isolation by distance ( IBD ) was detected in the Balkan , Nwestern , and Italian clusters ( Table 2 ) , indicating that genetic differentiation increased with geographic distance in these clusters . No significant IBD was detected within the Swestern and Eastern clusters ( Table 2 ) . The level of spatial structure was quantified by the Sp statistic , which accounts for variation in sampling intensities; high values of Sp are indicative of low population density and/or limited dispersal [65] . Sp values were close to 0 within the Italian , Swestern , and Eastern clusters , but were much higher within the Balkan and Nwestern clusters ( Table 2 ) . Within-cluster selfing rates estimated from InStruct analyses were extremely high ( s = 0 . 91±0 . 03 on average ) , in agreement with previous studies and with the high FIS values within clusters ( Table 2 ) . A European spatial map of genetic diversity was generated by aggregating geographically close samples together on a grid , considering only grid cells where the sample size was higher than 4 . The interpolated values of allelic richness showed that genetic diversity increased in the southward direction , with the highest value observed in the Italian and Iberian peninsulas and the lowest values in northern Europe ( Figure 2 ) . Such a latitudinal trend was confirmed by the highly significant negative correlation observed between latitude and allelic richness ( r = −0 . 57 , P<0 . 0001 ) ; no significant correlation was found between longitude and allelic richness ( r = 0 . 036 , P = 0 . 892 ) . High genetic diversities were also observed in the northern half of France and along a longitudinal line separating the Eastern and Western parts of Europe ( Figure 2 ) . We analyzed the relationships among clusters using neighbour-joining population trees , respectively based on Nei's DA distance , shared allele distance DSA , Chord's distance and Goldstein's ( δµ ) 2 distance . As the different trees provided similar topologies , only the tree based on Nei's DA distance is presented ( Figure 3 ) . The trees suggested that the Eastern groups would have diverged first , followed by the Italian cluster and then by the Western groups . The Eastern and Western group would then have further split into two clusters each . Rough estimate of separation time between clusters can be deduced from distances between clusters assuming that the divergence between the two species occurred 400 , 000 yr BP [52] and assuming clocklike evolution of microsatellite markers [66] . The separation of the 5 clusters can thus be roughly estimated to have occurred between 200 , 000 and 350 , 000 yr BP ( Figure 3 ) . In MvSd , multiple estimates of the genetic structure at the European scale provided confidence in existence of several distinct clusters . As for MvSl , the three Bayesian clustering analyses ( InStruct , STRUCTURE and TESS ) all indicated that DIC decreased and LnP ( X|K ) increased with increasing K ( Figure S7 ) . Again , genotype assignment probabilities were always very high , with very little admixture among clusters ( mean α = 0 . 030±0 . 002 over the 140 runs from K = 2 to 15 simulated clusters; Figure S8 ) , and were similar for the three algorithms used ( data not shown ) . The spatial distributions of the two clusters identified at K = 2 appeared highly intermingled , with however a slight West-East trend of separation . Further clusters differentiated as K increased , but without any obvious large-scale geographical pattern ( Figure 4 ) . Similar genetic partitioning was recovered using PCA ( Figure S9 ) . The first PC accounted for 20% of the variance in the allelic frequencies and clearly separated genotypes into the same two groups as those identified using Bayesian clustering approaches at K = 2 ( Figure S9 ) . The differences in allelic frequencies between them were high , with a FST value of 0 . 34 ( 95% CI: 0 . 17–0 . 49 ) . The successive PCs accounted for less than 11% of the total variance in allelic frequencies each and revealed the same clusters of genotypes as those observed in Bayesian clustering analyses ( Figure S9 ) . The two clusters identified at K = 2 represented the only structure with a large-scale geographical pattern . The FST values between sites where the sampling was higher or equal to 10 samples showed that a very high level of genetic differentiation between clusters was observed , even in the regions where populations from different clusters were intermingled ( Figure S10 ) . Within clusters , there was no significant IBD , i . e . no significant increase in FST with geographic distance ( Mantel test , P = 0 . 418 ) . The two clusters showed a spatial genetic structure of a similar level to that observed in MvSl , with Sp values of 0 . 06 and 0 . 15 for the clusters 1 and 2 , respectively ( Table 2 ) . Selfing rates within each of the two clusters , inferred from Instruct , were high and similar to those in MvSl ( mean selfing rates at K = 2: 0 . 93±0 . 01 ) , consistent with the high FIS values ( Table 2 ) . The two clusters of MvSd showed genetic diversities comparable to those observed in MvSl ( Table 2 ) , and did not differ significantly from each other with respect to gene diversity ( WSR test , P = 0 . 424 ) and allelic richness ( WSR test , P = 0 . 594 ) . In contrast to MvSl , spatially interpolated values of allelic richness increased northwards ( Figure 2 ) , although the correlation with latitude was significant only at a marginal level ( r = 0 . 43 , P = 0 . 073 ) . The correlation with longitude was not significant ( r = −0 . 008 , P = 0 . 975 ) . Very high selfing rates were inferred in both Microbotryum species ( s = 0 . 91 for MvSl and s = 0 . 93 for MvSd ) , in agreement with the high deficits in heterozygotes ( Text S1 , Table 1 ) . Microbotryum species are in fact known to have a selfing mating system [67] , [68] , but the estimations of selfing rates in natural populations inferred here are more precise and even higher than previously thought [67] . These high selfing rates appear to result both from an intrinsic preference for intra-tetrad mating [69] and from lack of outcrossing opportunities when the spores are deposited on a new host plant . The lack of outcrossing opportunity is supported by the observation that selfing rates under choice experiments ( when given the opportunity to self or outcross on plants ) are lower ( ca . 0 . 70 [70] ) than those inferred here in natural populations . The marker SL19 showed extreme FIS values in MvSl and was almost fixed in the heterozygous state in MvSd . This was not particularly surprising given that Microbotryum species undergo mostly intra-tetrad mating , which can lead to an excess in heterozygosity in regions of the genome near the centromeres and on the sex chromosomes carrying the mating type locus [69] , [71] . Because the mating type segregates at the first meiosis division , intra-tetrad mating automatically restores heterozygosity in all regions linked to centromeres and linked to the mating type locus , as they also segregate at the first meiotic division [69] , [71] . In addition to selfing , the study of local genetic structure and diversity for both Microbotryum species across Europe revealed patterns consistent with the dynamics of a metapopulation [72] . In particular , we observed very low genetic diversity within demes , and strong differences in allele frequencies ( high FST values ) between demes ( see text S1 ) . Metapopulation dynamics involve frequent extinctions and recolonizations , thus creating strong genetic drift in local populations . In addition , selfing reduces the local effective population size and the frequency of gene exchange between individuals and populations , which reinforces the effects of genetic drift upon allelic frequencies [72] , [73] . These results are consistent with previous population genetics and demographic studies conducted at more local scales on Microbotryum species infecting S . latifolia and S . dioica , also showing patterns consistent with metapopulation dynamics [42] , [74]–[77] . From a biogeographic point of view , Europe is a large peninsula with an East-West orientation , delimited in the south by a strong barrier , the Mediterranean Sea . During glaciation epochs , many species likely went through alternating contractions and expansions of range , involving extinctions of northern populations when the ice-sheet extended southward , and spread of the southern populations from different refugial areas as the glaciation receded . Such colonization processes were likely characterized by recurrent bottlenecks that would have led to lower diversity in the northern populations compared with the southern refugia [21] . The idea that refugia were localized in three areas ( Iberia , Italy , Balkans ) in Europe is now well-established [10] , [11] , [15] , [17] , although increasing evidence suggest that northern and eastern refugia also existed [78]–[84] . In MvSl , the strong phylogeographic structure observed at the European scale was composed of at least three genetic clusters with distributions strikingly similar to the major glacial refugia commonly recognized to have existed in Europe for many plant and animal temperate species ( e . g . , [14] ) . This pattern suggests that the pathogen likely colonized Northern Europe from at least the three main Mediterranean refugia ( Iberian , Italian and Balkan ) . The scenario may have been more complex , however , as the Eastern and Western clusters each further split into two groups , with divergence times of the five clusters roughly estimated between 200 , 000 and 350 , 000 yr BP . One of the eastern clusters was located north of the Balkans ( mainly in Hungary and Czech Republic ) and the other from Germany eastward . This pattern is consistent with colonization from distinct refugia located in the Balkans and further East in Eurasia , following a similar scenario as those reported in some animals , such as the bear Ursus actor [10] , the vole Myodes glareolus [79] , [80] , some plant species [78] , [85] , [86] , and also in some pathogens ( e . g . , [22]–[25] ) . The two clusters identified in Western Europe had more diffuse geographic distributions , with a slight longitudinal partitioning . One of the clusters was distributed more towards the West of France while the second was more present in east-central France and in Eastern UK . Such a pattern may be due to the pathogen having survived in distinct regional refugia in Western Europe , from which they would have expanded their range over France and UK . Such a hypothesis is consistent with recent findings that the main glacial refugia in Europe were probably not composed of a single population , but instead could have been structured into several local refugia more or less isolated from one another ( see the concept of “refugia within refugia” [87]–[91] ) . While the north-south gradient in genetic diversity can be taken as a sign of range expansion from southern glacial refugia , a band of high genetic diversity was observed north of Italy and extending into Germany , as well as a hotspot of diversity in the centre of France . These areas of high of genetic diversity likely come from the colonization history of Europe by the different genetic clusters , establishing suture zones where genetic clusters meet and become intermingled . Such a pattern has been observed previously in a comparative approach of the history of colonization of 22 widespread and co-distributed European trees and shrubs [92] , where hotspots of genetic diversity in the colonised ranges were found to be the result of mixed colonization from genetically isolated eastern and western European refugia [92] . The high genetic diversity found in MvSl in the Iberian peninsula also likely results from the co-occurrence of genotypes from four clusters . Previous studies indicated that the phylogeographic pattern of the host plant S . latifolia similarly showed genetic evidence of post-glacial recolonization from Mediterranean refugia [56] . Analyses of cpDNA haplotypes revealed clear biogeographic structure in Europe , with haplotypes from Eastern and Western Europe forming divergent groups descending from haplotypes currently distributed in Iberian and Balkan Peninsulas [56] . The phylogeographic patterns in the plant S . latifolia and in its anther smut pathogen therefore seem to be congruent . In particular , the Eastern and Western clades identified in the host could correspond to the Eastern and Western genetic clusters in the pathogen MvSl . The pathogen however seems to display a finer genetic structure than its host , with particularly clear genetic evidence of an Italian glacial refugium for the pathogen , but not for the host plant ( see figure 4 in [56] ) . More pronounced geographic structure is in fact expected in anther smut pathogens compared to their hosts , as has been observed at smaller scales [42] . This can be explained by the following observations: 1 ) the distribution of the pathogen is necessarily embedded within the range of its host , 2 ) anther smut pathogens are dispersed by the same vectors as the pollen of the plants , without being dispersed by seeds , so that their dispersal ability is lower than that of their host plants [42] . It is therefore likely that MvSl persisted in more fragmented refugia compared with its host . This highlights the potential use of pathogens as proxies for understanding host past migrations and distributions: the finding of distinct clusters in Italy and the Balkan in MvSl reveals that S . latifolia persisted in both these refugia during last glaciations , which was not obvious based solely on our current knowledge of the plant's phylogeograpy . However , statistically explicit comparative analyses linking the host and pathogen genetic polymorphisms , using comparable genetic markers , would be required to draw firm conclusions regarding correlations between the biogeographic structure of S . latifolia and MvSl ( e . g . [93] ) . The anther smut pathogen MvSd also exhibited a strong genetic structure , albeit with biogeographic patterns more difficult to interpret . The two main clusters had largely intermingled distributions , with an estimated time of divergence of the same order of magnitude as observed for MvSl . The distinct clusters in MvSd could correspond to genetic groups having diverged in distinct southern refugia during the glaciations , similar to MvSl , although the locations of the putative refugia are more difficult to identify . This may be due to the restricted distribution of MvSd , constrained by ecological specificities of the host and disease: the plant S . dioica is very rare in Mediterranean regions , and even more so the disease ( we did not find anther smut symptoms on any S . dioica plant in the Pyrenees despite several years of searching ) . On the other hand , given the more northern current distribution of the plant S . dioica compared to S . latifolia , one can alternatively speculate that its tolerance to cold temperatures [62] might have allowed the host and the disease to remain in more northern refugia , as suggested for other species adapted to cold environments [84] . This could provide an explanation of the marginally significant increase in allelic richness with latitude in MvSd , although we cannot rule out that this pattern resulted from the co-occurrence of a greater number of different clusters in the north . The phylogeography of the host plant S . dioica based on cpDNA RFLP similarly indicated the existence of genetically distinct groups , more or less longitudinally separated , albeit with large overlap in their ranges [58] . The distribution of the common cpDNA haplotypes was suggested to result from a post-glacial expansion of S . dioica across Europe from multiple southern refugia [57] , [58] . However the absence of sampling from Mediterranean peninsulas in prior studies prevents any definitive conclusion regarding the number and location of these refugia . In addition , the geographic distribution of the shared haplotypes in S . dioica and S . latifolia was consistent with a history of hybridization and introgression events , making it difficult to assess whether the present distribution of these haplotypes resulted from the recolonization history of S . dioica or S . latifolia [58] . A striking pattern observed in both Microbotryum species was the low level of admixture among genetic clusters ( ≤3% ) , suggesting almost complete lack of gene flow , despite the existence of contact zones . Such low levels of gene flow among clusters are likely influenced by the very high selfing rates in Microbotryum . High selfing rates have been invoked to explain reproductive isolation between sympatric Microbotryum species [67] , [94] , and there could be a similar effect in keeping the genetic clusters distinct within species . The high selfing rates also explain why increasing the number of clusters in Bayesian analyses always increased the explanatory value in describing the population genetic structure , without the appearance of admixed clusters , even for very high K values: this is because each diploid individual mostly reproduces with itself and therefore the smallest ‘panmictic unit’ may indeed be the individual . In selfing species , the genetic structure extends to a much finer scale than in outcrossing species [32] , [95] . The lack of gene flow among clusters may result in addition to metapopulation dynamics and rapid expansion during post-glacial recolonization . A theoretical study [96] indeed showed that rapid growth in population size after founding events resulted in gene frequency divergence that is resistant to decay by gene exchange . Large-scale congruence between the pathogens' phylogeographic patterns and those of their respective hosts indicates that their glacial refugia and migration pathways during recolonization have been similar . While this may be expected for obligate pathogens like Microbotryum species , highly dependent on their hosts for survival and using the same dispersal vectors , we interestingly found that the pathogens likely subsisted during glaciations in a more fragmented distribution , with their genetic diversity divided among a higher number of smaller refugia . Moreover , the extent of large-scale dispersal across Europe after recolonization was less for the pathogen than for its host: in particular , the clusters were much more clumped in MvSl than in S . latifolia , and footprints of refugia appeared in MvSl that were absent in S . latifolia , such as the Italian peninsula . Our findings thus indicate that vector-borne , obligate pathogens may colonize new areas following climate warming with some delay compared to their hosts , and to a lesser extent . The invasive potential of pathogens following climate change is therefore likely to depend on the obligate nature of the interactions with their host and on the dispersal modes , as could be expected . However , once the original host and its fungal pathogen invade a geographic region , the pathogen poses a risk of emerging as an infectious disease on new host species found in that area . For instance , MvSl was introduced in the United States some time after its host plant S . latifolia , and has remained in a much more restricted geographic area [97] . Cross-species disease transmission was nevertheless documented in the United States to another non-native species , S . vulgaris , that is otherwise free of anther smut disease in the continent [98] . In Europe , we have previously detected rare events of cross-species disease transmission between S . dioica and S . latifolia and of hybridization between MvSl and MvSd that occurred after secondary contact [52] . Host shifts are frequent in fungal pathogens [4] , [99] , [100] in particular in Microbotryum , where co-phylogenetic analyses showed that speciation events were most often associated with host shifts [47] . This suggests that climate warming may cause emerging infectious diseases , by resulting in contacts between different potential hosts that were allopatric , even when the intrinsic dispersal capacity of the pathogens is limited and their migration pathways are constrained by those of their hosts . Climate warming can also bring into contact differentiated populations from the same species , promoting introgression between previously geographically isolated populations , which can have important and unpredictable evolutionary consequences . We showed in the present study that secondary contact between genetically differentiated clusters happened after the glaciations in MvSl , and that the highly selfing mating system was here important in preventing introgression . The substantive contrast in phylogeography for the anther smut fungi on S . latifolia and S . dioica , which may be attributed to differences in the hosts' ecology , is also relevant for predicting the fate of infectious diseases following global warming . The redistribution of pathogens under warmer climatic conditions should indeed be highly dependent on the hosts' ecological preferences and adaptive potentials , in particular regarding the temperature and competition in new ecological communities [39]–[41] . In this study , we showed that high selfing rates and metapopulation dynamics in two plant pathogenic fungi had strong impact on their genetic diversity and structure . At the scale of the species' distribution ranges , the population structures in the two fungal species were quite different , likely due to differences in the ecological preferences of the two host-pathogen systems . The broadly distributed S . latifolia and its anther smut pathogen have kept clear genetic footprints of postglacial colonization from the major southern European refugia . The pathogens showed striking evidence for more numerous and localized refugia than their hosts . On the other hand , the ecological preference of the plant S . dioica for wetter and colder habitats [62] probably led to a more restricted and more northern distribution of the plant and its anther smut pathogen , and may have induced a drastic contraction of their distribution ranges with the post-glacial warming and the fragmentation of suitable habitat conditions . The European genetic structures of the anther smut fungi seem to match those of their respective hosts , with even a finer genetic structure , so that the geographic distribution of genetic variation in the pathogens may be useful to draw inferences about host phylogeography . Beyond the interest of our study for understanding the dynamics of diseases under climate warming and the impact of host life histories on the genetic structure of pathogens , our study illustrates several important points to take into account when performing clustering genetic analyses , which are still often poorly recognized . First , several K values are often interesting to consider in clustering analyses , and it may be non-heuristic to search for a “single optimal” number of clusters . As long as increasing K does not lead to admixed clusters , the new clusters revealed by increasing K probably reveal a genuine genetic structure that may be interesting to investigate . This appears especially true in selfing species , for which the smallest panmictic cluster may be the individual . The individuals of Microbotryum analyzed in this study were collected as diploid teliospores from 187 localities on S . latifolia ( n = 701 ) and 68 localities on S . dioica ( n = 342 ) across Europe ( Figure S10 ) and stored in silica gel ( see Figure S1 for a detailed description of the sampling ) . DNA from teliospores of one flower per diseased plant was extracted for genetic analyses . Multiple infections by different genotypes are frequent in the Silene-Microbotryum system , but teliospores within a single flower originate from a single diploid individual [101] . DNA was extracted as described in [77] . Teliospores were genotyped using 11 microsatellite markers following the protocol of [77] ( Table 1 ) . Among the 11 microsatellite loci used , E14 , E17 , E18 were described in [102] , SL8 , SL9 , SL12 , SL19 , SVG5 , SVG8 , SVG14 described in [103] , and SL5 was described in [104] .
Global change is expected to cause the large-scale redistribution of species , including pathogens that threaten the health of domestic populations and natural ecosystems . Predicting the dynamics of invasive pathogens is therefore a major challenge for the 21st century ecologists and epidemiologists . Because past climatic events have shaped the current distribution of species , the study of migration of pathogens during glaciation cycles provides insights into the constraints upon pathogen spread . We studied the structure of European populations of two pathogenic fungal species infecting two species of wild plants . The pathogen with the host's broadest ecological tolerance has followed the postglacial colonisation pathway of its host from the major refugia in southern Europe , although the pathogen likely persisted in more fragmented refugia . The other pathogen showed less clear-cut genetic patterns and some evidence of possible northern refugia , in agreement with the host's more fragmented distribution and ecological preference . These results indicate that pathogen invasions are likely to follow large-scale migration events of their host species in response to climate change , but also that the recolonization by pathogens is not simply a mirror of their hosts , and that the correlation between the colonization patterns of hosts and pathogens depends on host ecology .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "ecology/evolutionary", "ecology", "infectious", "diseases/fungal", "infections", "ecology/spatial", "and", "landscape", "ecology", "infectious", "diseases/sexually", "transmitted", "diseases", "ecology/population", "ecology", "genetics", "and", "genomics/population", "genetics" ]
2010
Glacial Refugia in Pathogens: European Genetic Structure of Anther Smut Pathogens on Silene latifolia and Silene dioica
The Arabidopsis thaliana Somatic Embryogenesis Receptor Kinases ( SERKs ) consist of five members , SERK1 to SERK5 , of the leucine-rich repeat receptor-like kinase subfamily II ( LRR-RLK II ) . SERK3 was named BRI1-Associated Receptor Kinase 1 ( BAK1 ) due to its direct interaction with the brassinosteroid ( BR ) receptor BRI1 in vivo , while SERK4 has also been designated as BAK1-Like 1 ( BKK1 ) for its functionally redundant role with BAK1 . Here we provide genetic and biochemical evidence to demonstrate that SERKs are absolutely required for early steps in BR signaling . Overexpression of four of the five SERKs—SERK1 , SERK2 , SERK3/BAK1 , and SERK4/BKK1—suppressed the phenotypes of an intermediate BRI1 mutant , bri1-5 . Overexpression of the kinase-dead versions of these four genes in the bri1-5 background , on the other hand , resulted in typical dominant negative phenotypes , resembling those of null BRI1 mutants . We isolated and generated single , double , triple , and quadruple mutants and analyzed their phenotypes in detail . While the quadruple mutant is embryo-lethal , the serk1 bak1 bkk1 triple null mutant exhibits an extreme de-etiolated phenotype similar to a null bri1 mutant . While overexpression of BRI1 can drastically increase hypocotyl growth of wild-type plants , overexpression of BRI1 does not alter hypocotyl growth of the serk1 bak1 bkk1 triple mutant . Biochemical analysis indicated that the phosphorylation level of BRI1 in serk1 bak1 bkk1 is incapable of sensing exogenously applied BR . As a result , the unphosphorylated level of BES1 has lost its sensitivity to the BR treatment in the triple mutant , indicating that the BR signaling pathway has been completely abolished in the triple mutant . These data clearly demonstrate that SERKs are essential to the early events of BR signaling . Brassinosteroids ( BRs ) are naturally produced plant hormones regulating many developmental processes from seed germination to flowering and senescence [1] . BR deficiency or response mutants show typical phenotypic defects including decreased rate of seed germination , rounded and epinastic rosette leaves , extremely dwarfed stature , delayed flowering time , reduced male fertility , postponed leaf senescence , and extremely de-etiolated phenotypes grown under dark conditions [2]–[5] . Although both plants and animals use steroids as growth regulators , the signaling pathways in the two kingdoms are divergent [6] . While animal steroids are known to be perceived by nuclear receptors which can directly regulate gene transcription upon ligand binding , BRs are sensed by a single-pass transmembrane leucine-rich repeat receptor-like protein kinase ( LRR-RLK ) named Brassinosteroid Insensitive 1 ( BRI1 ) and two BRI1 paralogs , BRI1-Like 1 ( BRL1 ) and BRL3 [3] , [7]–[9] . When BR is absent , BRI1 was found to exist as a homodimer whose cytoplasmic domain interacts with a membrane-anchored protein termed BRI1 Kinase Inhibitor 1 ( BKI1 ) , blocking the interaction between the kinase domains of BRI1 and its co-receptor BRI1-Associated Receptor Kinase 1 ( BAK1 ) [10]–[13] . Recent crystal structure analyses demonstrated that the LRRs of BRI1 form an extremely twisted helical solenoid structure and the hydrophobic pocket formed by LRRs and the “island” domain provides a direct binding site for BRs [14] , [15] . The ligand-receptor interaction initiates the BR signaling cascade , mostly via reversible phosphorylation and dephosphorylation [16] . It was proposed that during early events of BR signaling , the BR receptor BRI1 and its co-receptor BAK1 follow a reciprocal and sequential phosphorylation process before downstream components can be activated [17] . Interaction of BR with the extracellular domain of BRI1 triggers a conformational change of the cytoplasmic domain of BRI1 , causing phosphorylation of BKI1 on a conserved tyrosine residue , resulting in the dissociation of phosphorylated BKI1 from BRI1 [12] , [18] . It is likely that the BRI1 kinase domain is autophosphorylated and activated via an intermolecular mechanism , and the activated BRI1 then recruits BAK1 , via a kinase-to-kinase and extracellular domain-to-extracellular domain double lock mechanism , in close proximity and phosphorylates several Thr residues within the activation loop of BAK1 , activating the co-receptor [19] , [20] . The active BAK1 then phosphorylates multiple residues within the juxtamembrane and carboxyl terminus regions of BRI1 , fully activating BRI1 and creating proper docking sites for association of other BRI1 downstream components such as BR-Signaling Kinases ( BSKs ) [21] . The activated BSKs can inhibit kinase activity of a negative regulator Brassinosteroid Insensitive 2 ( BIN2 ) by activating a protein phosphatase named bri1 Suppressor 1 ( BSU1 ) to dephosphorylate a phosphotyrosine residue ( pTyr200 ) on BIN2 [22] . Inactivation of BIN2 causes the accumulation of two unphosphorylated transcription factors Brassinazole-Resistant 1 ( BZR1 ) and bri1-Ems-Suppressor 1 ( BES1 ) in nuclei , directly mediating the expression of BR responsive genes [23]–[28] . Phosphorylated forms of BES1 and BZR1 , on the other hand , are trapped in cytoplasm by interacting with 14-3-3 proteins and eventually degraded via a 26S proteasome-mediated pathway [29]–[32] . The role of BAK1 has been mainly defined by various gain-of-function genetic and biochemical analyses [10] , [11] , [17] , [20] . The significance of the function of BAK1 , however , has so far not been demonstrated by a loss-of-function genetic analysis which is considered as the most reliable approach to reveal biological functions of a given gene . A BAK1 null mutant only exhibits a subtle bri1-like defective phenotype suggesting either additional homologues of BAK1 play redundant roles with BAK1 , or BAK1 and its homologues only provide an enhancing but not an essential role to BR signaling . The significance of BAK1 and its homologues in mediating BR signaling should be determined in a mutant plant with lesions of BAK1 and all its functionally redundant genes . Recent studies indicated that BAK1 and its homologues also play important roles in regulating several BR-independent signaling pathways such as anther development , cell-death control , and disease resistance [33] . For example , the serk1 serk2 double mutant shows an anther defective phenotype [34] , [35]; the bak1 bkk1 double null mutant displays light-dependent spontaneous cell death at the seedling stage [36] , [37]; and the bak1 single mutant exhibits uncontrolled cell death and reduced innate immunity responses to a variety of pathogens [38]–[42] . These findings add additional complexity to our efforts towards understanding the significance of BAK1 in BR signaling pathway . In this study , we show that four out of five members of the SERK subfamily ( SERK1 to SERK4 ) , in the wild-type Arabidopsis Columbia background ( Col-0 ) , may play functionally redundant roles in BR signaling . In Col-0 , SERK5 contains a mutation in an important amino acid residue which likely abolishes the kinase activity of SERK5 [36] . We subsequently isolated null mutants for all four kinase active SERKs , and generated double , triple , and quadruple mutants using two sets of independent null mutants . Our detailed analysis indicates that dark grown serk1 bak1 bkk1 triple mutants show a typical de-etiolated phenotype resembling a null bri1 mutant . Physiological and biochemical analyses indicate that the triple mutant is insensitive to BR treatment similar to a null bri1 mutant . Furthermore , the phosphorylation level of BRI1 in the triple mutant is completely unresponsive to BR treatment , suggesting that BRI1 cannot initiate BR signaling without BAK1 and its homologues . These results provide clear genetic and biochemical evidence that BAK1 plays an essential role in the BR signal transduction pathway . BAK1 was previously identified as a coreceptor of BRI1 in mediating BR signaling [10] , [11] . Genetic data demonstrating BAK1 is essential to BR signal transduction is still lacking . If BAK1 plays a role which is as critical as BRI1 , a mutant plant with loss-of-function mutation of BAK1 and all its functionally redundant genes should exhibit a typical bri1 null mutant phenotype ( Figure 1A ) . A bak1 null mutant , however , shows a subtle bri1-like phenotype suggesting that there may be the LRR-RLK II subfamily genes that are functionally redundant with BAK1 . The five SERKs are grouped in a single clade of the LRR-RLK II subfamily according to phylogenetic analyses [43] , [44] . Based on sequence similarity , it is logical to hypothesize that any BAK1 functionally redundant proteins would be members of the LRR-RLK II subfamily . To test this hypothesis , all 14 LRR-RLK II members were overexpressed in the intermediate bri1-5 mutant in the WS2 background [45] . Our results indicated that only SERK1 , SERK2 , BAK1 , and BKK1 could partially suppress bri1-5 phenotypes when overexpressed ( Figure 1B ) . These overexpressed transgenic plants showed elongated petioles and wild-type like bolting and flowering time . Previous studies already indicated in vivo physical interactions of BRI1 with SERK1 , BAK1 , and BKK1 , respectively [10] , [11] , [36] , [46] . In this study , we tested the in vivo interaction between BRI1 and SERK2 using transgenic plants overexpressing BRI1-FLAG and SERK2-GFP . Our result indicated that BRI1-FLAG can weakly interact with SERK2-GFP in vivo . Unlike the interactions of BRI1 with BAK1 and BKK1 , the interaction between BRI1 and SERK2 cannot be significantly enhanced with exogenously applied BR ( Figure S1 ) , but the phosphorylation of SERK2 can be dramatically enhanced by the supplementation of BR ( Figure S1 ) . These results suggest that SERK2 may have fewer roles in BR signaling compared to the other three SERKs , but unnatural manipulation such as overexpression of SERK2 and exogenous application of BR can reveal its functions in BR signaling . To further confirm the function of SERKs in BR signaling , kinase-inactive versions of all 14 LRR-RLK II members were generated by mutating a conserved lysine residue in the ATP binding site of each of these genes . These mutated genes were named mSERK1 , mSERK2 , mBAK1 , mBKK1 , etc . All 14 mutated genes were overexpressed in bri1-5 . If mutated mSERKs still can interact with bri1-5 , the resulting transgenic plants should show a dominant negative phenotype . Our results indicated that most of the transgenic plants obtained for all the four constructs of mSERKs showed phenotypes resembling that of a null bri1 mutant , such as bri1-4 [45] ( Figure 1C ) . These data suggest that SERK1 , SERK2 , BAK1 , and BKK1 are the only 4 LRR-RLK II genes that are involved in BR signaling . To better understand the genetic significance of SERKs in BR signaling , single , double , triple , and quadruple mutants for all four SERKs were generated . Two independent sets of T-DNA insertion lines for all the four SERKs were obtained from the Arabidopsis Biological Resource Center ( ABRC ) ( Figure 2 ) . RT-PCR reactions were performed to confirm that all the lines used do not express full-length wild-type mRNAs ( Figure S2 ) . Therefore , these lines are likely null mutants . A novel BRI1 T-DNA insertion line named bri1-701 was also obtained from ABRC . bri1-701 not only showed no full-length mRNA expression but also exhibited a phenotype identical to a typical null bri1 mutant . bri1-701 was therefore used as a null bri1 control throughout the entire studies . Double serk mutants were generated by crossing two different serk mutants . Because serk1 serk2 , serk1 bak1 , and bak1 bkk1 showed male sterility , reduced male fertility , and cell death phenotypes respectively , we had to be strategic about generating triple mutants , as discussed in materials and methods . We first phenotypically analyzed the first set of single mutants of the four SERKs , serk1-8 , serk2-1 , bak1-4 , and bkk1-1 ( Figure 2 ) . Only bak1-4 showed subtle bri1-like phenotypes such as shortened petioles , reduced rosette size , and reduced height when grown in the light . When grown in the dark , bak1-4 showed slightly shortened hypocotyls compared to wild-type seedlings as reported previously ( Figure 3; [10] , [11] ) . None of the other SERK mutants showed any visible defective phenotypes . We then generated double mutants with the four single mutants . Among all 6 possible double mutants generated , only serk1-8 bak1-4 showed a weak bri1-like phenotype which is more severe than the bak1-4 single mutant , including more compact rosette leaves and more shortened hypocotyls ( Figure 3 ) . As a matter of fact , the hypocotyls of serk1-8 bak1-4 are only about half of the length of wild-type ( Figure 3B , 3C ) , which is still significantly taller than the bri1-701 null mutant , suggesting that BR signaling is severely but not completely disrupted in serk1-8 bak1-4 . We confirmed that serk1-8 serk2-1 shows a defective male gametogenesis phenotype; and bak1-4 bkk1-1 shows seedling lethality phenotypes about two weeks after germination as previously reported [34]–[36] . Our priority in these genetic studies was to investigate whether knocking-out BAK1 and its functionally redundant genes in a single plant can completely abolish BR signaling pathway and recapitulate a bri1-like phenotype . Because bak1-4 bkk1-1 shows a seedling lethality phenotype due to failure of a light-dependent cell death control [36] , we did not anticipate observing a light-grown null bri1-like phenotype for the triple or quadruple mutants . Therefore , the phenotypes of the triple and quadruple mutants were mainly analyzed within the dark-grown conditions . To our surprise , some of the serk1-8 serk2-1 bak1-4 triple mutant displayed an embryo-defective phenotype , and the serk1-8 serk2-1 bak1-4 bkk1-1 quadruple mutant are most likely embryo-lethal ( data not shown ) . Our attention was drawn to one of the triple mutants , serk1-8 bak1-4 bkk1-1 , because this mutant showed an extreme de-etiolated phenotype similar to that of bri1-701 including shortened hypocotyls and opened cotyledons ( Figure 3B , 3C ) . To further confirm that the triple mutant phenotypes result from the null mutations of the corresponding SERKs , we generated double , triple , and quadruple mutants using a different set of single null mutants , serk1-1 , serk2-2 , bak1-6 , and bkk1-2 ( Figure 2 ) . All the defective phenotypes observed are similar to the mutants generated by the first set of null alleles ( Figure S3 ) . Most importantly , serk1-1 bak1-6 bkk1-2 also showed a severe bri1-like de-etiolated phenotype ( Figure S3 ) . The phenotypic resemblance suggests that the BR signaling pathway is abolished in the serk triple mutant similar to that in the bri1 null mutant . To verify that the observed phenotypes are caused by the loss-of-function of the SERK genes , we performed complementation experiments using native SERK promoters . Because the double , triple , and quadruple mutants generated from 2 sets of independent mutants look very similar , we performed the complementation and all other biochemical experiments using the mutants generated from the 1st set of single null mutant . We were never able to clone the BKK1 promoter into these constructs; therefore , the BAK1 promoter was used to drive the expression of BKK1 . When native promoter-driven SERK1 and BAK1 were transformed into serk1-8 bak1-4 , the double mutant phenotypes were largely rescued ( Figure 4A ) . When BAK1 promoter driven BAK1 and BKK1 were transformed into serk1-8 bak1-4 bkk1-1 triple mutant background , the lethality phenotype of the triple mutant was also rescued ( Figure 4A ) . When SERK1 promoter driven SERK1 was introduced into the serk1-8 bak1-4 bkk1-1 background , no rescued plants were ever obtained because of cell death resulted from knock-out of BAK1 and BKK1 ( data not shown ) . The transgenic plants were also grown in the dark to examine whether they restored the de-etiolated phenotype of the mutant plants . Indeed , SERK1 and BAK1 restored the mutant phenotypes of serk1-8 bak1-4 in the dark . BAK1 and BKK1 completely rescued the mutant phenotypes of serk1-8 bak1-4 bkk1-1 in the dark . The complementation of SERK1 driven by its own promoter only partially restored the mutant phenotypes , producing semi-dwarf hypocotyls ( Figure 4B , 4C ) . The reason why pS1::SERK1 only partially rescued the hypocotyl phenotype of serk1-8 bak1-4 bkk1-1 is not known . Results from two sets of independent null mutants and from the complementation experiments clearly indicated that the defective mutant phenotypes were caused by the null mutations in the SERKs . To examine whether the null bri1-like phenotype seen in the dark grown serk1 bak1 bkk1 triple null mutant was caused by the disruption of BR signaling , a classic root growth inhibition assay for BR sensitivity was performed [2] . If SERKs play an essential role in BR signaling , SERK mutants should show a reduced response to exogenously applied BR . Plants were grown for 7 days on half strength MS medium agar plates supplied with or without different concentrations of BR . Wild-type and bak1-4 are sensitive to the root growth inhibition of different concentrations of 24-epiBL ranging from 1 to 1000 nM , with bak1 showing slightly reduced sensitivity ( Figure 5A ) . The root growth of serk1-8 bak1-4 was insensitive to 24-epiBL from 1 to 100 nM , but showed some sensitivity at 1000 nM . Analyses of hypocotyls also showed reduced sensitivity of serk1-8 bak1-4 to exogenously applied 24-epiBL ( Figure 5B ) . The root and hypocotyl growth of bri1-701 and serk1-8 bak1-4 bkk1-1 , however , was completely insensitive to 24-epiBL at concentrations from 1 to 1000 nM . These results indicate that the triple mutant plants are insensitive to exogenously applied BR ( Figure 5A , 5B ) . To confirm that the de-etiolated phenotype seen in the triple mutant is caused by the disruption of the BR signaling pathway instead of the general photomorphogenesis pathways , we used two constitutive photomorphogenesis ( COP1 ) mutants , cop1-4 and cop1-6 , as controls to determine whether they also show insensitivity to exogenous BR treatment ( Figure S4A , S4B ) . Our results indicated that although COP1 mutants exhibit a de-etiolated phenotype , they are sensitive to exogenous BR treatment . In Col-0 , the expression of CPD is down-regulated by exogenously applied BR via a negative feedback mechanism . When BR signaling is disrupted as in bri1 null mutants , however , the expression of CPD is not responsive to BR treatment [47] . To further confirm that the BR signaling is blocked in serk1 bak1 bkk1 triple mutant , quantitative RT-PCR experiments were performed to detect the expression levels of CPD and DWF4 in wild-type and mutant plants treated with or without BR ( Figure 5C , 5D ) . Similar to previous reports , the expression level of CPD was decreased to about 20% of wild-type plants when treated with BR . In bri1-701 null mutant , the expression of CPD was not significantly down-regulated when treated with BR ( Figure 5C ) . Consistent with its weak bri1-like phenotype , the expression level of CPD in bak1-4 was decreased dramatically similar to wild-type upon BR treatment . However , the double knock-out mutant serk1-8 bak1-4 showed drastically reduced sensitivity to BR treatment with slightly decreased CPD expression upon BR treatment . The expression level of CPD in the BR treated serk1-8 bak1-4 bkk1-1 triple null mutant was not decreased ( Figure 5C ) . Similar to the CPD response , the expression level of DWF4 was down-regulated to about 20% in wild-type plants when BR was applied exogenously . However , BR treated serk1-8 bak1-4 bkk1-1 mutant showed dramatically reduced sensitivity to exogenous BR application similar to the bri1-701 mutant plant ( Figure 5D ) . These data indicate that the BR signaling pathway in the triple mutant of SERKs is blocked to the same extent as bri1 null mutants . To biochemically test whether the serk1 bak1 bkk1 triple null mutant is insensitive to exogenously applied BR , the phosphorylation status of BES1 was investigated with a specific anti-BES1 antibody after the wild-type and triple mutant were treated with or without 1 µM 24-epiBL ( Figure 5E , 5F; Figure S5 ) [48] . In Col-0 wild-type seedlings without BR treatment , two BES1 bands with almost equal signal intensity were observed , indicating that both phosphorylated and unphosphorylated BES1 were present . Upon BR treatment , unphosphorylated BES1 in wild-type was increased dramatically and phosphorylated BES1 disappeared , suggesting that the BR signaling pathway was activated . In the untreated seedlings of the weak allele of bri1-301 , the amount of phosphorylated BES1 was slightly higher than that of unphosphorylated BES1 . In the BR-treated bri1-301 seedlings , the amount of unphosphorylated BES1 became greater than phosphorylated BES1 . However , the untreated null mutant bri1-701 showed higher levels of phosphorylated than unphosphorylated BES1 , and the ratio between the two types of BES1 was not changed when treated with BR . All single SERK null mutants showed response to BR in a way similar to that of wild-type plants . Although serk1-8 bak1-4 showed an enhanced bri1-like phenotype compared to bak1-4 single mutant ( Figure 3 ) , BES1 phosphorylation levels in the double mutant still show a wild-type like response ( Figure 5E ) . A previous report showed that BAK1 and BKK1 function redundantly in BR signaling [36] , which is also supported by the result from this study that untreated bak1-4 bkk1-1 seedlings showed predominantly phosphorylated BES1 protein , suggesting that BR signaling is dramatically impaired in the double mutant . Upon BR treatment , both phosphorylated and unphosphorylated BES1 were detected although the phosphorylated BES1 was still dominant , indicating that the BR signaling pathway was not disrupted completely in bak1-4 bkk1-1 . Interestingly , the serk1-8 bak1-4 bkk1-1 triple null mutant only showed the phosphorylated BES1 band with or without the exogenous BR application , suggesting that BR signal transduction was entirely blocked in the triple mutant . serk2-1 bak1-4 bkk1-1 exhibited a BES1 phosphorylation response similar to bak1-4 bkk1-1 . When serk1-8 serk2-1 bak1-4 was treated with BR , the amount of unphosphorylated BES1 increased dramatically ( Figure 5E ) . These results indicate that serk2 has an undetectable effect on BR signaling in Arabidopsis seedlings; and BR signaling appears to be entirely blocked in the serk1 bak1 bkk1 triple null mutant . Similar results were obtained from the second set of knockouts ( Figure S5 ) . Although BR insensitive mutants showed a de-etiolated phenotype , de-etiolated mutants do not always show BR insensitivity . For example , cop1-4 and cop1-6 showed wild-type like BES1 response to BR treatment ( Figure S4C ) . It was previously reported that overexpression of BRI1 can drastically increase hypocotyl growth of wild-type plants [7] , [20] . To test whether BRI1 is still able to promote hypocotyl growth of the serk1 bak1 bkk1 triple null mutant , we overexpressed BRI1-GFP in wild-type and the serk1-8 bak1-4 bkk1-1 respectively . Our results indicated that overexpression of BRI1-GFP can increase hypocotyl growth of wild-type plants but has no effect on the triple null mutants ( Figure 6A , 6B , 6C ) . To understand why BRI1 has lost its physiological roles in the triple mutant , we next analyzed whether the phosphorylation levels of BRI1 can respond to exogenously applied BR . In the wild-type plants , exogenous BR treatment could significantly increase the phosphorylation levels of BRI1 as reported ( Figure 6D; [17] , [20] ) ; whereas in the serk1 bak1 bkk1 triple null mutant , phosphorylation of BRI1 remains at an extremely low level regardless of BR treatment ( Figure 6D ) . These results suggest that BR signaling is blocked in the triple mutant most likely because BRI1 has lost its responsiveness to internal bioactive BRs . The function of BAK1 in mediating BR signaling was independently identified by using a yeast-two hybrid screen for BRI1 interacting proteins and activation tagging for genetic suppressors of an intermediate BRI1 mutant , bri1-5 [10] , [11] . Since then , numerous data supported the biochemical roles of BAK1 in regulating early events of BR signal transduction [17] , [20] , [49] . The biological significance of BAK1 in BR signaling , however , has never been convincingly substantiated due to lack of loss-of-function genetic evidence . If BAK1 is a key component in BR signaling , a plant lacking BAK1 and all its functionally redundant genes should exhibit a phenotype identical to a bri1 null mutant . In addition , the mutant plant should show no response to BR treatment in a way similar to what has been revealed for null bri1 mutants . To resolve these questions , we set to identify all genes in the Arabidopsis genome which might play redundant roles with BAK1 . We overexpressed all 14 genes from the LRR-RLK II subfamily , to which the 5 SERKs belong , in the bri1-5 background to evaluate their possible roles in BR signaling . Interestingly , only SERK1 , SERK2 , BAK1 , and BKK1 can suppress the defective phenotypes of bri1-5 when overexpressed . None of the other 10 genes showed any bri1-5 suppression phenotypes ( Figure 1A , 1B ) . We also overexpressed kinase-inactive mutants of all these 14 genes in bri1-5 . Consistent with the SERK overexpression results , only mSERK1 , mSERK2 , mBAK1 , and mBKK1 give a dominant negative phenotype ( Figure 1C ) . We therefore focused on generating single , double , tripe , and quadruple mutants of these four genes in order to estimate the genetic contribution of these four SERKs to BR signaling . Early studies indicated that bak1 bkk1 double nulls are lethal due to failure of a BR-unrelated light-dependent cell death control pathway [36] , [37] , therefore we did not expect to observe that a multiple null mutant plant would recapitulate the bri1 null mutant phenotype shown under light grown conditions , such as dark green , round and compact leaves , and extreme dwarfism [2] . Rather , we anticipated seeing that a multiple null mutant would express a de-etiolated phenotype resembling that of a bri1 null mutant if SERKs play a key role in regulating BR signal transduction . From our current results , we conclude that BAK1 and its homologues play an indispensable role in initiating BR signaling ( Figure 7 ) . This conclusion is mainly supported by the following key observations described in this study . First , the serk1 bak1 bkk1 triple null mutant showed a characteristic de-etiolated phenotype similar to that of a null bri1 mutant under dark grown conditions ( Figure 3B , Figure S3B ) . Second , the triple null mutant is insensitive to BR according to the root growth inhibition analysis and the hypocotyl growth analysis ( Figure 5A , 5B ) , CPD , DWF4 feedback inhibition analysis ( Figure 5C , 5D ) , and accumulation of unphosphorylated BES1 assay ( Figure 5E , Figure S5 ) . In the triple null mutant , no unphosphorylated forms of BES1 can be detected , indicating that the BR signaling pathway has been blocked , at least under a normal physiological setting; and the unphosphorylated levels of BES1 cannot be induced by exogenously applied BR , as shown in wild-type plants and other SERK single mutants ( Figure 5E; Figure S5 ) . Finally , overexpression of BRI1 cannot alter the growth of the triple null mutant most likely because the phosphorylation of BRI1 is unresponsive to the fluctuation of the amount of internal biologically active BR ( Figure 6 ) . Together , these results suggest that the biological function of BRI1 in regulating plant growth is entirely dependent upon the action of SERKs . SERK2 is apparently critical for the earlier development of embryos , as the development of the serk1 serk2 bak1 bkk1 quadruple null mutant is completely arrested at an early embryo stage ( unpublished data ) . No viable quadruple mutant seeds were ever recovered from these genetic analyses . Therefore , analysis of BR response in quadruple mutant was impracticable . Evidently , SERK2 plays no significant role at an early postembryonic seedling developmental stage; and the interaction between SERK2 and BRI1 is extremely weak compared to that of other SERK members and BRI1 ( Figure S1 ) [10] , [36] , [46] . Exogenous application of BR cannot increase BRI1/SERK2 interactions ( Figure S1 ) . Under an unnatural condition , SERK2 may show BAK1-like biochemical properties . For example , seedlings treated with exogenously applied BR can drastically induce SERK2 phosphorylation ( Figure S1 ) ; and overexpression of SERK2 can partially suppress the defective phenotypes of bri1-5 ( Figure 1B ) . Our genetic and biochemical results , however , clearly indicate that SERK1 , BAK1 , and BKK1 are the major players for BR signaling at the Arabidopsis seedling stage . It is worth noting that phenotypes of single , double , triple , and quadruple mutants of SERK1 , SERK2 , BAK1 , and BKK1 were discussed in a previous research article [50] . In that report , the authors claimed that serk3 serk4 double mutant showed an early senescence but not a lethality phenotype . It was also reported that the serk1 serk3 serk4 triple or serk1 serk2 serk3 serk4 quadruple mutants did not show any enhanced phenotype over the serk1 serk3 double mutant phenotype . The main cause for the discrepancy of our observations and the results from that report is that the mutant allele of BAK1/SERK3 used in their genetic analyses , serk3-1/bak1-3/SALK_ 034523 , is actually a leaky mutant . bak1-3 contains a T-DNA insertion in the 4th intron of the BAK1 genomic DNA ( Figure S6A ) . RT-PCR analysis and DNA sequence analysis indicated that bak1-3 can express a reduced amount of wild-type BAK1 mRNA in bak1-3 bkk1-1 background , although the transcription level of BAK1 in bak1-3 single mutant is not detectable ( Figure S6B ) . Consistent with these observations , bak1-3 single mutant does exhibit a typical null bak1 mutant phenotype which is indistinguishable from bak1-4 ( Figure S6C ) . bak1-3 bkk1-1 double mutant , however , shows a much reduced early senescence phenotype than bak1-4 bkk1-1 ( Figure S6C ) . Therefore , bak1-3 is not a true null mutant of BAK1 , especially in the situation when BKK1 is also knocked out ( Figure S6B , [33] ) . In this study , we performed the genetic analysis by using two independent sets of confirmed transcriptional nulls ( Figure S2B , S2C ) . Identical results were obtained from these two sets of mutant analyses ( Figure 3A , 3B; Figure 5E; Figure S3A , S3B; Figure S5 ) . In addition , the null bri1-like phenotype seen in the dark-grown serk1 bak1 bkk1 triple mutant can be complemented with BAK1 or BKK1 driven by the BAK1 promoter , but cannot be rescued by SERK1 with its native promoter ( Figure 4A , 4B ) . The later result is consistent with our previous discovery that the bak1 bkk1 double null mutant is a seedling lethal mutant [36] . Our current observations suggest that SERKs play a critical role in the early events of BR signaling likely via a reciprocal and sequential phosphorylation model as proposed previously , with some modifications [20] . In wild-type plants , BR interacting with its receptor BRI1 in the extracellular domain triggers a conformational change within the cytoplasmic domain , leading to the basal activation of cytoplasmic BRI1 kinase , releasing of the BKI1 inhibitor , and inducing interaction between BRI1 and BAK1 or its homologues . The initially activated BRI1 evidently only can activate SERKs but not other downstream components such as BSKs . Activation of downstream components by BRI1 requires full activation of BRI1 by BAK1 and its functionally redundant homologues , most likely as a consequence of transphosphorylation . As a result , unphosphorylated forms of BES1 are accumulated which can directly regulate BR responsive gene expression ( Figure 7 ) . In a serk1 bak1 bkk1 triple null mutant plant , on the other hand , BR signaling apparently is entirely blocked from BRI1 to BES1 due to lack of the involvement of BAK1 and its functionally redundant proteins ( Figure 7 ) . As a consequence , BES1 accumulates as the phosphorylated form , which is incapable of mediating the expression of BR-responsive genes . Therefore the triple null mutant plant exhibits a phenotype similar to a bri1 null mutant . Both are the outcome of disrupted BR signaling . Although unphosphorylated BES1 level in both the bri1 and serk1 bak1 bkk1 triple null mutants showed almost an undetectable response to exogenously applied BR , the bril null mutant showed both phosphorylated and unphosphorylated BES1 ( Figure 5E; Figure S5 ) , suggesting a BR signal leakage in the bri1 null mutant . This could be contributed by BRL1 and BRL3 , both of which play partially redundant roles with BRI1 [9] , [51] . In a previous report , it was hypothesized that without SERKs , BRI1 has basal kinase activity towards downstream components [20] . The hypothesis was based upon several observations from the bak1 bkk1 double null mutant including that the de-etiolation of the bak1 bkk1 is not as severe as the bri1 null mutant; overexpression of BRI1 can significantly increase hypocotyl growth of the bak1 bkk1 double null mutant; and the phosphorylation levels of BRI1 can still respond to exogenous BR treatment . From this study , we now propose that without SERKs , BRI1 does not appear to have basal activities towards downstream components because the serk1 bak1 bkk1 triple null shows a bri1 null mutant phenotype; overexpression of BRI1 cannot increase the hypocotyl growth of the triple mutant; and in the triple null mutant the phosphorylation of BRI1 is completely unresponsive to BR treatment , hinting that BRI1 also cannot respond to internal BR levels . The BR signaling appears to be entirely blocked due to a blocked full BRI1 activation event by SERKs . In the future , analysis will be conducted to determine why phosphorylation of BRI1 cannot respond to BR in the absence of SERKs . The ultimate understanding of the roles of SERKs in BRI1-mediated signaling may rely on a combination of genetics and structural biology . Arabidopsis accessions WS2 and Columbia-0 ( Col-0 ) were grown at 22°C in a long-day condition ( 16 h of light and 8 h of dark ) in a greenhouse except those for phenotypic analysis in the dark which were grown in half strength MS agar plates with 1% ( w/v ) sucrose . To create knock-out mutants used in this study , T-DNA insertion lines were obtained from The Arabidopsis Biological Resource center ( ABRC ) for serk1-1 ( SALK_044330 ) , serk1-8 ( SALK_071511 ) , serk2-1 ( SALK_058020 ) , serk2-2 ( SAIL_119_G03 ) , bak1-3 ( SALK_ 034523 ) , bak1-4 ( SALK_116202 ) , bak1-6 ( SAIL_513_A11 ) , bkk1-1 ( SALK_057955 ) , bkk1-2 ( SALK_105409 ) , serk5-1 ( SALK_089460 ) , and bri1-701 ( SALK_003371 ) . Reverse transcription-polymerase chain reactions ( RT-PCR ) were performed to examine the expression of BRI1 and SERKs in the used mutants . To amplify the full-length CDS and the flanking mRNA sequence of the T-DNA insertion site of BRI1 and SERKs , primer pairs BRI1FL-F/BRI1FL-R , BRI1M-F/BRI1M-R , SERK1F-F/SERK1F-R , SERK1M-F/SERK1M-R , SERK2F-F/SERK2F-R , SERK2M-F/SERK2M-R , BAK1F/BAK1R , SERK3M-F/SERK3M-R , SERK4F-F/SERK4F-R , and SERK4M-F/SERK4M-R were used , respectively . ACTIN2 was amplified as a control by primers RT-actin2F and RT-actin2R . All the used primers are listed in Table S1 . The T-DNA mutant plants were genotyped by PCR . Homozygous single knock-out lines were used to generate double knock-out mutants . Double knock-out mutants of serk1 serk2 , and bak1 bkk1 were obtained by segregating from corresponding mutant plants with homozygous insertion for one gene and heterozygous for the second gene . Triple knock-out mutants were obtained by crossing fertile pairs serk1+/− serk2 and serk2 bak1 , serk1+/− serk2 and serk2 bkk1 , serk1 bak1 and bak1+/− bkk1 , serk2 bak1 and bak1+/− bkk1 . The triple knock-out mutants were segregated from self-pollinated mutant plants serk1+/− serk2 bak1 , serk1+/− serk2 bkk1 , serk1 bak1+/− bkk1 and serk2 bak1+/− bkk1 which contain heterozygous insertion for one gene and homozygous insertions for two other genes . Gateway technology was employed to clone all the coding sequences of SERK cDNA sequences for overexpression in bri1-5 and complementation experiments in mutants as previously described [44] using the primers listed in Table S1 . The amplified CDS sequences of SERK genes were introduced into the destination vector pB35GWF with the help of Gateway technology . Site-directed mutagenesis was carried out according to the manual of the QuickChange Site-directed Mutagenesis Kit ( Stratagene , La Jolla , CA ) . Entry clones of cloned SERK genes were used as templates for chain extension with primers listed in Table S1 . The mutated entry clones of SERK genes were used for in vitro DNA recombination with the destination vector pB35GWF to create expression constructs for Arabidopsis transformation . To generate constructs for native promoter-driven expression of SERKs , promoter sequences of SERKs were PCR amplified from Arabidopsis genomic DNA and inserted into the pBIB-BASTA-GWR-GFP vector [44] before the gateway cassette by using the primers listed in Table S1 . The resulting constructs were named as pSERK1-GWR-GFP , pSERK2-GWR-GFP and pSERK3-GWR-GFP , respectively . Then the cloned coding sequences of SERK genes were transferred into these destination vectors by in vitro DNA recombination to create expression constructs of pS1::SERK1-GFP , pS2::SERK2-GFP , pS3::SERK3-GFP and pS3::SERK4-GFP , respectively . All the cloned sequences were confirmed by sequencing analysis and the expression constructs were transferred into appropriate Arabidopsis plants by the floral dip method [52] . Seeds were surface sterilized and placed on half strength MS plates with 0 . 8% ( w/v ) agar , 1% ( w/v ) sucrose and different concentrations of 24-epiBL ( Sigma , St . Louis , MO ) . The plates were cold treated at 4°C for 2 days to ensure uniform germination . Seeds were considered to begin germination after the plates were kept at 22°C for 24 hr . The root length was measured seven days after germination in the light and the hypocotyl length was measured five days after germination in the dark . Seven-day-old seedlings of transgenic plants with 35S::BRI1-GFP and 11-day-old liquid-cultured seedlings of transgenic plants harboring 35S::SERK2-GFP and 35S::BRI1-FLAG were treated with or without 24-epiBL for 90 min , respectively , and ground to fine powder in liquid N2 [17] . Membrane protein isolation was performed as previously described [10] . BRI1-FLAG was immunoprecipitated from solubilized membrane protein with agarose-linked α-FLAG antibody ( Sigma , St . Louis , MO ) . SERK2-GFP and BRI1-GFP were immunoprecipitated with α-GFP antibody ( Invitrogen , Carlsbad , CA ) and protein G beads ( Roche , Indianapolis , IN ) . The immunoprecipitated proteins were separated on 7 . 5% SDS polyacrylamide gel for Western analyses with α-GFP , α-FLAG , α-phosphothreonine antibodies as previously described [10] . Arabidopsis seedlings grown on half strength MS plates were harvested and treated with or without 1 µM 24-epiBL for 4 hr and the total protein was extracted and separated on 12% SDS polyacrylamide gel to detect the phosphorylation status of BES1 with an anti-BES1 antibody . Horseradish peroxidase-linked anti-rabbit or anti-mouse antibodies were used as secondary antibodies and the signal was detected by Western Lightning Chemiluminescence Reagent Plus ( Perkin-Elmer , Waltham , MA ) .
Brassinosteroids ( BRs ) are a group of plant hormones critical for plant growth and development . BRs are perceived by a cell-surface receptor complex including two distinctive receptor kinases , BRI1 and BAK1 . Whereas BRI1 is a true BR-binding receptor , BAK1 does not appear to have BR-binding activity . Therefore , BAK1 is likely a co-receptor in BR signal transduction . The genetic significance of BAK1 was not clearly demonstrated in previous studies largely due to functional redundancy of BAK1 and its closely related homologues . It was not clear whether BAK1 plays an essential role or only an enhancing role in BR signaling . In this study , we identified all possible BAK1 redundant genes in the Arabidopsis thaliana genome and generated single , double , triple , and quadruple mutants . Detailed analysis indicated that , without BAK1 and its functionally redundant proteins , BR signaling is completely disrupted , largely because BRI1 has lost its ability to activate downstream components . These studies provide the first piece of loss-of-functional genetic evidence that BAK1 is indispensable to the early events of the BR signaling pathway .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "signal", "transduction", "plant", "science", "model", "organisms", "plant", "and", "algal", "models", "molecular", "cell", "biology", "membrane", "receptor", "signaling", "mechanisms", "of", "signal", "transduction", "plant", "biology", "plant", "genetics", "signaling", "pathways", "biology", "molecular", "biology", "arabidopsis", "thaliana" ]
2012
Genetic Evidence for an Indispensable Role of Somatic Embryogenesis Receptor Kinases in Brassinosteroid Signaling
Mechanisms of gene regulation are poorly understood in Apicomplexa , a phylum that encompasses deadly human pathogens like Plasmodium and Toxoplasma . Initial studies suggest that epigenetic phenomena , including histone modifications and chromatin remodeling , have a profound effect upon gene expression and expression of virulence traits . Using the model organism Toxoplasma gondii , we characterized the epigenetic organization and transcription patterns of a contiguous 1% of the T . gondii genome using custom oligonucleotide microarrays . We show that methylation and acetylation of histones H3 and H4 are landmarks of active promoters in T . gondii that allow us to deduce the position and directionality of gene promoters with >95% accuracy . These histone methylation and acetylation “activation” marks are strongly associated with gene expression . We also demonstrate that the pattern of histone H3 arginine methylation distinguishes certain promoters , illustrating the complexity of the histone modification machinery in Toxoplasma . By integrating epigenetic data , gene prediction analysis , and gene expression data from the tachyzoite stage , we illustrate feasibility of creating an epigenomic map of T . gondii tachyzoite gene expression . Further , we illustrate the utility of the epigenomic map to empirically and biologically annotate the genome and show that this approach enables identification of previously unknown genes . Thus , our epigenomics approach provides novel insights into regulation of gene expression in the Apicomplexa . In addition , with its compact genome , genetic tractability , and discrete life cycle stages , T . gondii provides an important new model to study the evolutionarily conserved components of the histone code . Toxoplasma gondii is an obligate intracellular apicomplexan parasite responsible for encephalitis in immunocompromised individuals and birth defects when a fetus is exposed in utero [1 , 2] . The life cycle of T . gondii is complex , with multiple differentiation steps that are critical to survival of the parasite in its human and feline hosts [3] . The genetic tractability of T . gondii has caused it to emerge as a model for the study of apicomplexan parasites [3] , and the recent sequencing of the T . gondii genome ( http://www . toxodb . org ) is adding to our appreciation of the unusual nature of apicomplexan genomes [4 , 5] . A remarkable finding is the relative paucity of genes encoding proteins with motifs that indicate transcription factor function in apicomplexan genomes [6 , 7] . This has led to the proposal that gene regulation in apicomplexan parasites is controlled mainly via RNA stability [6] , despite the tightly regulated patterns of gene expression observed in different stages of the life cycle of T . gondii [8] and Plasmodium falciparum [9] . However , that certain DNA motifs are recurrent in the promoters of these organisms and bind to nuclear factors [10−14] suggests that unrecognized transcription factors may exist , but are not encoded by genes with recognizable structural features . On the other hand , the RNA polymerase II machinery [7 , 15] and genes with motifs indicating potential chromatin remodeling and modification functions [6 , 16] are conserved within the Apicomplexa . Epigenetic processes have significant clinical relevance in light of studies that implicate the histone deacetylase Sir2 homolog in regulation of antigenic variation in P . falciparum [17 , 18] . To obtain a genome-wide view of gene expression in T . gondii tachyzoites , we examined the epigenetic organization and transcription patterns of a contiguous 1% of the T . gondii genome using custom microarrays . Histone modifications—including acetylation of histone H4 ( H4ac ) , acetylation of lysine 9 ( H3K9ac ) , and trimethylation of lysine 4 of histone H3 ( H3K4me3 ) —have been identified at certain individual active loci in T . gondii [19] , suggesting a role in gene expression . We hybridized the tiled genomic microarrays with material derived from chromatin immunoprecipitations using antibodies to modified histones . By simultaneously hybridizing the microarray to tachyzoite-derived cDNA , we tested the genome-wide association of specific histone modifications with gene expression . We generated a custom oligonucleotide microarray containing 12 , 995 50-mer features tiling a 650-kb region of Chromosome 1b , with an average resolution of one oligonucleotide every 50 bp ( Figure 1 ) . Chromosome 1b of the RH strain of the 63-Mb T . gondii genome has been extensively annotated and has a single nucleotide polymorphism frequency comparable with the rest of the genome , an average of 5 . 7 exons per coding sequence ( CDS ) , and a gene density of one gene per 7 . 4 kb [20] . Currently , 91 genes are predicted within the 650-kb region of the RH strain of T . gondii . The amino acid sequences of the tails of eukaryotic histones H3 and H4 are strongly conserved ( Figure S1 ) , allowing us to use a panel of commercial antibodies for chromatin immunoprecipitation ( ChIP ) in T . gondii . After screening antibodies to modified histones for T . gondii nuclear localization ( Table 1; Figure S2 ) , we performed ChIP using DNA isolated from the intracellular tachyzoite stage of T . gondii . As a control , we used an antibody against a T . gondii kinase with no DNA-binding potential ( M . Gissot and K . Kim , unpublished data ) . The immunoprecipitated DNA was amplified , tested to ensure enrichment for control loci was maintained , and co-hybridized to the 650-kb tiling array with input DNA . We studied the distribution of three modified histones ( H4ac , H3K9ac , and H3K4me3 ) previously described as activation marks in other eukaryotes [21 , 22] . The ChIP material applied to the microarray ( ChIP-chip ) generated strong focal peaks of enrichment for the three different modified histones . Signal was readily discriminated from noise , even looking at the raw ChIP/input DNA ratio ( Figure 1 ) , a finding confirmed by the p-values derived from the use of the ChIPOTle analytical approach [23] , which approached zero for each locus . We observed 52 clear , discrete , and coincident H4ac , H3K9ac , and H3K4me3 peaks within the 650-kb region tiled on the microarray ( Figure 1B; Table S1 ) . The H3K9ac and H4ac peaks have a median size of 1 , 550 bp , whereas the H3K4me3 peaks are relatively smaller ( median size of 1 , 300 bp; Table 1 ) . As previously observed for other eukaryotes [21 , 22] , these modifications co-localize and associate to form a complex pattern at focused loci in the T . gondii genome ( Figure 1 ) . More than 96% of the H3K4me3 , H3K9ac , and H4ac ( Figure 1B ) peaks are placed in the predicted intergenic regions . Moreover , the identified peaks for the three modifications are located close to the 5′ of predicted genes . Indeed , the distance between the identified peak and the start codon of the closest gene is less than 1 , 000 bp for more than 85% ( 45/52 ) of the H3K9ac and H4ac peaks ( Table 1 ) , and less than 1 , 500 bp for more than 90% ( 48/52 ) . Similarly , for more than 90% ( 49/52 ) of H3K4me3 peaks , the end of the peak and the first predicted initiation codon was within 1 , 000 bp ( Table 1 ) . We also performed ChIP using antibodies against histone H3 dimethylated at arginine 17 ( H3R17me2 ) , another putative general activation mark in T . gondii [19] and other eukaryotes [24 , 25] . Recently , it was suggested that this histone modification is present at all active promoters in T . gondii [19] based upon PCR examination of selected promoters after ChIP with anti-H3R17me2 . Using the same antibody , we show that this modification is restricted to a subset of promoters ( Figure 1B ) . This histone mark overlapped with only four of the 52 modified histone peaks identified ( 4 . 5% of the genes present on the microarray ) . All four genes have expressed sequence tags ( ESTs ) for both tachyzoite and bradyzoite stages . The H3K4me1 and H3K4me2 marks were also investigated using ChIP-chip and were not specifically enriched , as determined by analysis of hybridizations by the ChIPOTLe software ( unpublished data ) . We also verified that the modified histone peaks identified were not due to local core histone enrichment by performing ChIP-chip with an antibody specific to the C-terminus histone H3 . The ChIP-chip results were validated using quantitative single-locus PCR ( Figure 2 is representative of eight loci validated ) . Using real-time quantitative PCR on ChIP samples , we amplified regions within the predicted gene ( primer set 1 ) or in intergenic sequences ( primer sets 2−6 ) . We found enrichment of the three modified histones in regions identified as peaks in the ChIP-chip experiments ( primer sets 2 , 3 , 5 , and 6 ) . In contrast , the three activation marks tested were not significantly enriched in a region located within the predicted gene ( primer set 1 ) and a region between the two identified peaks ( primer set 4 ) . We also verified that there was no significant local enrichment of the core histone H3 ( positive PCR for all primer sets ) . To verify the link between the modified histone peaks and transcription of the nearest predicted gene , we hybridized cDNA made from intracellular tachyzoites to the tiled microarray ( Figure 3 ) . Using three different analytical approaches , we identified regions on the tiled portion of the genome with significant gene expression ( Table S1 ) . Overall , 51 of the 52 regions with a cluster of H3K9ac , H4ac , and H3K4me3 peaks had a significant cDNA hybridization signal adjacent to them . These data were consistent with EST studies , with 46 of the 49 genes represented by at least one EST for the tachyzoite stage expressed in our dataset . In our study , 31% ( 21/67 ) of the genes expressed were not represented by any EST data , demonstrating the limits of the EST mapping approach for identifying expressed genes . Two transcribed loci did not correspond to a predicted gene ( Table S1 ) . One locus had associated H3K9ac , H4ac , and H3K4me3 peaks characteristic of active chromatin and corresponded to a transcription unit represented by two overlapping tachyzoite ESTs ( CN197705 and CK737836 ) . A partial open reading frame ( ORF ) was discovered after alignment of those ESTs . After comparing this sequence with the nr database ( http://www . ncbi . nlm . nih . gov/BLAST ) , we found the ORF had homology with the cytochrome oxidase subunit III ( COX3 ) gene of Plasmodium ( highest p-value = 5e-06 ) . This gene is not annotated in the current version of the T . gondii genome ( http://www . toxodb . org ) . The other locus was also represented by an EST ( BG659482 ) and appears to be driven by a promoter that displays promoter activity in both directions ( Table 2 ) . However , this transcribed locus does not have an ORF and appears to represent a non-coding RNA . We also found two regions of clustered genes with stage-specific expression based on EST data . One region predicts a set of five tandemly arrayed kinases with ESTs primarily from the oocyst stage ( Figure 3A ) . Another region is characterized by five genes predicted as BSR4 homologues with ESTs primarily from the bradyzoite stage ( Figure 3B ) . No significant expression during the tachyzoite stage could be detected , and neither region had any of the three histone modification peaks characteristic of active chromatin . For the bradyzoite-specific locus , two ESTs were recovered from a Type III strain ( VEG ) tachyzoite cDNA library . These ESTs could reflect differences in gene expression between strains or represent the low level of bradyzoite forms frequently present in Type II and Type III tachyzoite cultures . To test that the clustered peaks were located at active promoters , we performed luciferase reporter assays ( Table 2; Figure 4A and 4B ) . We cloned regions spanned by the H3K9ac and H4ac peaks and tested their ability to drive the expression of the luciferase in transient transfection assays . Of the 12 loci tested , 11 were able to drive expression of luciferase ( Table 2; Figures 4 and S3 ) . Regions 5′ of non-expressed genes that lacked clustered peaks of modified histones or regions spanned by a predicted ORF are not able to drive the expression of luciferase ( Table 2; Figure S3 ) . However , the two loci with overlapping H3K4me3 , H3K9ac , and H4ac peaks located within rather than 5′ to annotated gene coding regions were both able to drive the expression of a reporter gene ( Table 2; Figure 4B ) . Of the 52 activation peaks identified , only one lacked evidence of mRNA expression in its vicinity . This peak is located 5′ to a predicted gene ( Tg1b . 2420 ) , a locus with the characteristics of a DNA-repair protein , but not associated with any EST in the T . gondii database at any stage of the life cycle . The promoter of this gene yielded a background activity as low as the untransfected parasites ( Table 2; Figure S3 ) . H3K4me3 peak distribution is consistently shifted toward the 5′ end of genes in comparison with H3K9ac ( unpublished data ) and H4ac peaks ( Figure 4C and 4D ) . PCR studies confirmed that the shift of the H3K4me3 peak predicts the orientation of transcription . ( Four genes were tested with two represented in Figure 2 . ) As predicted by these data , most of the sequences tested have directional activity , as would be expected for genuine promoters ( Table 2; Figure 4C and 4D ) . However , seven of the 52 peaks are located in regions where two genes are transcribed in opposite directions , providing biological evidence for sequences in T . gondii that have promoter activity in both directions as shown in other Apicomplexa [26] . As illustrated , H3K4me3 , H3K9ac , and H4ac peaks identify promoters . We also found seven predicted genes ( as defined in [20] ) that were expressed but lacked modified histone peaks at their predicted promoter . In all such cases , these genes are preceded within 1 , 000 bp by an expressed gene that is transcribed in the same direction and bears histone activation peaks at its 5′ end . These genes likely represent gene prediction errors , since RT-PCR in two cases confirmed a single transcription unit with the adjacent gene ( Figure S4 ) . We have employed an integrative approach to epigenomics , combining simultaneous analysis of ChIP-on-chip and gene expression on a tiling array encompassing a 0 . 65-Mb contiguous portion of the T . gondii Chromosome 1b . The H3K9ac , H4ac , and H3K4me3 modifications co-localize at focused loci in the T . gondii genome and correlate with significant gene expression . We confirmed that the enrichment observed was not due to local enrichment of the H3 core histone by performing ChIP with an antibody directed against the C-terminus of the histone H3 . In contrast , in T . gondii , the H3K4me1 and the H3K4me2 modifications are present at equal amounts in active and inactive chromatin as previously shown for human promoters [22] and in contrast to Saccharomyces cerevisiae [23] . To our knowledge , this study is the first to explore the distribution of the H3R17me2 modification on a genomic scale . Surprisingly , this modification is enriched only at a subset of active promoters . Thus , T . gondii uses its histone modification machinery not only as a general landmark of activated promoters but also to specifically attribute a distinctive mark to certain promoters . ESTs have been sequenced from both tachyzoite and bradyzoite stages for those four genes , whereas only 26 of the 91 predicted genes on our chip ( 28% ) have ESTs in both tachyzoite and bradyzoite stages . The H3R17me2 mark may have significance during the tachyzoite to bradyzoite differentiation process , but the number of loci discovered in this study are too limited to speculate further upon the specificity conferred by this trait . The recent discovery of the importance of arginine methylation during early development of mouse embryo indicates a specific role for the H3R17me2 during differentiation [27] . The H3K9ac and H4ac peaks in T . gondii are larger than those previously observed in human ( approximately 700 nucleotides [nt] ) [28] but similar in size to those found in yeast [23] . It appears that the number of modified nucleosomes is in the same range for these three organisms despite their difference in genome compaction . Such similarity in the size of the peaks may have functional implications for RNA polymerase II . The placement of the three “gene activation” modifications coincides , but H3K4me3 peaks are shifted toward the 5′ end of expressed genes . This difference has been documented in human cell lines [29] and predicts the directionality of promoters in T . gondii . Although most promoters appear to be orientation-specific , the tiled region of the T . gondii genome encodes several regions that exhibit promoter activity in both directions . Further mapping studies are needed to determine whether these are true bi-directional promoters or two separate promoters facing in opposite directions . We observed an exceptional correlation between gene expression and the presence of co-localized modified histone peaks . The few discrepancies between the EST database and our gene expression data are likely due to differences in gene expression between the strain we used ( RH , Type I ) and the strains used to generate “tachyzoite” cDNA libraries . Type II and III tachyzoite cultures , in contrast to Type I strains , frequently have a low level of basal bradyzoite forms . One region represented on our array had a cluster of H3K9ac , H4ac , and H3K4me3 peaks but was unable to drive luciferase expression . Interestingly , these peaks are located 5′ to a gene ( Tg1b . 2420 ) predicted to encode a protein similar to DNA-repair protein XRCC3 , a protein essential for ultraviolet radiation–induced double-strand break repair from bacteria to mammals [30] . Expression of this gene was not detected by reverse transcriptase−PCR ( RT-PCR; Table S1 ) and there were no associated ESTs in the T . gondii database at any stage of the life cycle , which could be explained by rapid processing or degradation of the mRNA for this gene . Alternatively , the promoter could be in a poised state waiting for activation or for the release of a repression , as observed in a study of rapidly induced genes in human T cells [31] . As suggested for T cells , the activation marks associated with this promoter could signify the presence of epigenetic memory in T . gondii . In a study of human promoters , 20% of those genes with overlapping H3ac and H3K4me3 marks lacked evidence of mRNA expression [21] . Prior microarray gene expression studies in T . gondii have been based upon cDNAs [32] rather than tiled genomic microarrays . Our survey of tachyzoite gene expression for this contiguous 1% of the T . gondii genome enabled us to identify new tachyzoite-expressed genes and discover transcripts in regions where genes have not been predicted . For example , a cluster of modified histone “activation” peaks helped us to identify a gene coding for a cytochrome oxidase subunit III , which is not annotated in the current version of the T . gondii genome , and a possible non-coding RNA . Moreover , our study illustrates the power of empirical annotation of the genome in terms of promoters and their transcriptional orientation , enhancing gene prediction approaches beyond what is currently possible using DNA sequence-based approaches alone . In conclusion , we have performed the first mapping to our knowledge of the epigenome of an apicomplexan parasite . Taken together , the data indicate that T . gondii uses a multipart histone modification system to assign a functional role to certain DNA sequences and underscores the ability of this unicellular apicomplexan parasite to employ a complex set of tools to control its gene expression . These data are consistent with the extensive repertoire of proteins predicted to modify histones in the T . gondii genome [16] . Moreover , our study illustrates the power of empirical annotation of the genome in terms of promoters and their transcriptional orientation , enhancing gene prediction approaches beyond what is currently possible using DNA sequence-based approaches alone . T . gondii is a medically important pathogen and is genetically tractable . It is a powerful model for studying the gene regulation of apicomplexan parasites and may now represent a new model system for understanding evolutionarily conserved components of the “histone code . ” Further , epigenetic regulators may represent potential therapeutic targets and provide new tools to fight toxoplasmosis and other parasitic diseases like malaria . T . gondii RH strain was maintained in confluent monolayers of human foreskin fibroblasts ( HFF ) . Parasites were harvested 24 h after invasion of HFF cells and purified as previously described in [33] . ChIP was performed as described [34] with slight modifications . Briefly , chromatin from intracellular tachyzoites grown in HFF for 24 h was cross-linked for 10 min with 1% formaldehyde at room temperature and purified after a sonication step yielding fragments of 500−1 , 000 bp . Immunoprecipitations were performed with the appropriate rabbit serum ( Table 1 ) at 4 °C overnight and washed extensively as published previously [34] . DNA was further subjected to a treatment with proteinase K for 2 h and then purified using the Qiagen PCR purification kit ( http://www . qiagen . com ) . As a negative control , we used rabbit antiserum to PKA2 , a kinase that is not present in the nucleus ( M . Gissot and K . Kim , unpublished data ) . We generated a tiled array of 50-bp oligonucleotides with 12 , 295 oligos encompassing 650 , 000 bp ( 1 , 230 , 000−1 , 880 , 000 ) of Chromosome 1b [20] with a spacing of 50 bp between each oligonucleotide . The array was fabricated in the NimbleGen Systems ( http://www . nimblegen . com ) 12-plex format , which allows simultaneous hybridization of 12 identical arrays on a single slide . Amplification of immunoprecipitated DNA and 100-ng input DNA was performed using the ligation-mediated PCR technique [35] . After amplification , the immunoprecipitated DNA was tested for enrichment of control loci by qPCR and co-hybridized to the 650-kb tiling array with input DNA . DNA was labeled using random primers coupled to a fluorochrome and hybridized according to NimbleGen Systems procedures . At least two biological replicates were performed . Real-time quantitative PCR was performed on the 7300 ABI apparatus using the Power Sybr ( ABI , http://www . appliedbiosystems . com ) mastermix in a 20-μL volume according to the manufacturer's instructions . PCR primers were designed using the Primerexpress software ( ABI ) to amplify regions of 100−150 nt . A 10-fold dilution of input was compared with 0 . 5 ng of immunoprecipitated DNA . Each experiment was performed at least three times in duplicate . The RNA from three replicate flasks containing RH strain–infected HFFs and one control flask containing only HFFs was purified using TRIzol . RNA integrity was verified on the Agilent Bioanalyzer ( http://www . agilent . com ) . Ten micrograms of total RNA was retrotranscribed using the BD Sprint Powerscript kit ( http://www . bdbiosciences . com ) and random hexamers and made double-stranded cDNA ( dscDNA ) using Escherichia coli polymerase I . dscDNA labeling with fluorochrome-coupled random hexamer and hybridization to the array was performed following NimbleGen protocols . NimbleGen scanning and spot finding software were used . Significant peaks for ChIP-on-chip were identified with the ChIPOTle software [23] using a permutation simulation to estimate the background distribution ( with a window size of 500 bp , 300 permutations , and a p-value of 0 . 001 ) . Peaks with a p-value of less than 10−10 ( which produces about 50 times more significant regions than false regions ) and with a peak height cut-off of 2 were considered significant . The false discovery rate was 0 . 1% . After background correction using random probes , gene expression was calculated as the average of the log2 ratio of the intensity given by the HFF plus parasite dscDNA to the intensity given by the HFF-alone dscDNA . With ChIPOTle , expression was considered significant with a p-value < 0 . 05 and a high average ratio above 1 or 0 . 6 . Peaks of significant expression were also identified using the detection peaks tool in SignalMap software with a sliding window of 150 bp and a log2 ratio threshold of 1 or 0 . 8 . A peak is identified when there are at least four data points within a window above the threshold value . The height of the peak is the maximum of the data points within the window . In addition , the raw log2 ratios were normalized using loess regression to remove the dependence of the variance on the mean and partitioned into segments along the chromosome with the function segmentation within the Bioconductor package “tilingArray” ( http://www . bioconductor . org ) [36] , using 300 and 3 , 000 for the maxseg and maxk arguments , respectively . Since a one-to-one correspondence between the segments and the gene annotations does not exist ( e . g . , when several adjacent genes are not transcribed ) , tests of significance were carried out using the means of the probes that mapped fully to each annotated gene . The intensity threshold between the untranscribed and transcribed segments was determined by fitting a mixture model to the segment means using the “mclust” package from Bioconductor [36] . The significance of expression for each annotation was calculated using the binomial test on the signs of the differences between the probe intensities and the threshold [37] . The p-values were adjusted for multiplicity using the Benjamini–Yekutieli procedure from the “multtest” package of Bioconductor [36] with a false discovery rate of 0 . 1% . Regions of T . gondii DNA ( Tables 2 and S1 ) were subcloned into pCR8-GW vector ( Invitrogen , http://www . invitrogen . com ) , sequenced , and cloned into a Gateway vector expressing Firefly luciferase . Plasmid ( 50 μg ) was co-transfected with 20 μg plasmid expressing Renilla luciferase under the control of the Tubulin promoter ( both plasmids gift of M . W . White , Montana State University ) following standard transfection protocols [38] . Luciferase assay was performed after 24 h using the Promega Dual-Luciferase Kit ( http://www . promega . com ) according to manufacturer instructions . Each assay was repeated three times in duplicate . Gene predictions were as described in Khan et al . [20] . The sequences corresponding to the CDS were extracted for a 650-kb region of the RH strain Chromosome 1b [20] and were set up as a BLAST database using the BLAST program downloaded from NCBI ( http://www . ncbi . nlm . nih . gov/BLAST ) . We then used a perl script to blast the 88 , 535 EST sequences downloaded from the ToxoDB Web site ( http://www . toxodb . org/download/release-3 . 3/EST/nuc ) against the BLAST database . The e-value cut off of e-25 was considered significant . The European Bioinformatics Institute ( http://www . ebi . ac . uk ) accession numbers of genes and proteins used in this study are TgIb . 1560c; TgIb . 1570; TgIb . 1580c; TgIb . 1590; TgIb . 1600; TgIb . 1610c; TgIb . 1620; TgIb . 1630c; TgIb . 1640; TgIb . 1650c; TgIb . 1660; TgIb . 1670; TgIb . 1680c; TgIb . 1690c; TgIb . 1700c; TgIb . 1710; TgIb . 1720c; TgIb . 1730c; TgIb . 1740; TgIb . 1750c; TgIb . 1760c; TgIb . 1770c; TgIb . 1780; TgIb . 1790c; TgIb . 1800c; TgIb . 1810c; TgIb . 1820; TgIb . 1830; TgIb . 1840; TgIb . 1850c; TgIb . 1860; TgIb . 1870c; TgIb . 1880; TgIb . 1890; TgIb . 1900c; TgIb . 1910; TgIb . 1920; TgIb . 1930c; TgIb . 1940; TgIb . 1950c; TgIb . 1960c; TgIb . 1970; TgIb . 1980c; TgIb . 1990; TgIb . 2000; TgIb . 2010c; TgIb . 2020; TgIb . 2030; TgIb . 2040; TgIb . 2050; TgIb . 2060; TgIb . 2070c; TgIb . 2071; TgIb . 2080; TgIb . 2090; TgIb . 2100c; TgIb . 2110; TgIb . 2120c; TgIb . 2130c; TgIb . 2140c; TgIb . 2150c; TgIb . 2160c; TgIb . 2170c; TgIb . 2180c; TgIb . 2190; TgIb . 2200; TgIb . 2210c; TgIb . 2220c; TgIb . 2230; TgIb . 2240; TgIb . 2250; TgIb . 2260; TgIb . 2270; TgIb . 2280c; TgIb . 2290; TgIb . 2291; TgIb . 2300; TgIb . 2310; TgIb . 2320c; TgIb . 2330; TgIb . 2340; TgIb . 2350c; TgIb . 2360c; TgIb . 2370c; TgIb . 2380c; TgIb . 2390c; TgIb . 2400; TgIb . 2410; TgIb . 2420; TgIb . 2430; and TgIb . 2440c . GenBank dbEST ( http://www . ncbi . nlm . nih . gov/entrez/query . fcgi ? db=Nucleotide ) accession numbers of ESTs used in this study are BG659482 , CN197705 , and CK737836 . Microarray data have been submitted to the Gene Expression Omnibus database ( http://www . ncbi . nlm . nih . gov/projects/geo ) under accession numbers GSM139203–GSM139216 and GSM139134–GSM139136; the number for the complete series is GSE7262 .
Apicomplexan parasites , including Toxoplasma gondii , are responsible for a variety of deadly infections , but little is understood about how these important pathogens regulate gene expression . Initial studies suggest that alterations in chromatin structure regulate expression of virulence traits . To understand the relationship of chromatin remodeling and transcriptional regulation in T . gondii , we characterized the histone modifications and gene expression of a contiguous 1% of the T . gondii genome using custom DNA oligonucleotide microarrays . We found that active promoters have a characteristic pattern of histone modifications that correlates strongly with active gene expression in tachyzoites . These data , integrated with prior gene predictions , enable more accurate annotation of the genome and discovery of new genes . Further , these studies illustrate the power of an integrated epigenomic approach to illuminate the role of the “histone code” in regulation of gene expression in the Apicomplexa .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods", "Supporting", "Information" ]
[ "toxoplasma", "genetics", "and", "genomics" ]
2007
Epigenomic Modifications Predict Active Promoters and Gene Structure in Toxoplasma gondii
Honduras is endemic for soil-transmitted helminth ( STH ) infections , but critical information gaps still remain on the prevalence and intensity of these infections as well as on their spatial distribution at subnational levels . Firstly , to review the research activity on STH infections in Honduras and secondly , to carry out a national prevalence analysis and map the geographical distribution of these infections in children . A systematic search was conducted of the published and grey literature to identify scientific work on the impact and prevalence of STH infections done between May 1930 and June 30 , 2012 . International databases and Honduran journals were searched . Grey literature was gleaned from local libraries and key informants . Select studies conducted between 2001 and 2012 were used to produce prevalence maps and to investigate association between STH prevalence and socio-economic and environmental factors . Of 257 identified studies , 211 ( 21 . 4% peer-reviewed ) were retained for analysis and categorized as clinical research ( 10 . 9% ) , treatment efficacy studies ( 8 . 1% ) or epidemiological studies ( 81% ) . Prevalence analysis and geographical mapping included 36 epidemiological studies from Honduras's 18 departments and 23% of its municipalities . Overall STH prevalence was >50% in 40 . 6% of municipalities . Prevalences above 20% for each trichuriasis , ascariasis , and hookworm infection were found in 68% , 47 . 8% , and 7 . 2% of studied municipalities , respectively . Municipalities with lower human development index , less access to of potable water , and with higher annual precipitation showed higher STH prevalences . This is the first study to provide a comprehensive historic review of STH research activity and prevalence in Honduras , revealing important knowledge gaps related to infection risk factors , disease burden , and anti-parasitic drug efficacy , among others . Our decade-long prevalence analysis reveals geographical differences in STH prevalence and these findings suggest that differential intervention strategies might be necessary in Honduras for the control of these infections . Intestinal parasites including soil-transmitted helminths ( STH ) have been long recognized as public health problems in much of the developing world [1] . Soil-transmitted helminthiases are caused by four species of intestinal worms , namely , Ascaris lumbricoides , Trichuris trichiura , and the two hookworm species Ancylostoma duodenale and Necator americanus [2] . Current estimates show that more than 2 billion people worldwide are infected with STH , the majority residing in low and middle income countries ( LMICs ) [3] , [4] . Within LMICs , STH endemicity is concentrated in and around areas where ecological and environmental characteristics intersect with conditions that facilitate transmission [5] , [6] . In addition , recent studies have shown that soil-transmitted helminthiases and other neglected tropical diseases ( NTDs ) also cause a great burden among poor populations living in wealthy nations , including the United States [7] , [8] . Primarily and due to their widespread distribution and chronic nature , STH infections pose a high burden in endemic populations [2] , [4] , [9] among which , children and youth are disproportionally affected [10] , [11] . Hence , global efforts are currently focused on this vulnerable population [4] . As a highly effective and immediate intervention for reducing STH morbidity in high risk groups , the World Health organization ( WHO ) recommends to all disease-endemic countries periodic administration of anthelminthic medication ( a strategy called preventive chemotherapy , PC ) [12] , [13] . Implementing PC is , however , not without challenges . Barry et al ( 2013 ) recently calculated that for 2011 , 875 million children ( 70% of school age ) lived in high-risk areas worldwide but only 38% of pre-school and 34% of school age children were reached by PC activities [14] . Aware of this gap , and in support of WHO's roadmap to guide implementation of NTD's control strategies [15] , a number of private and public partners have agreed to join forces to assure that anthelminthic drugs and other interventions reach all people suffering from NTDs including STH infections [16] . Honduras , as most countries in Latin America , is endemic for STH infections [4] , [5] , [17] , [18] . Organized efforts to control these infections in the country can be traced back to the 1990s but the current nation-wide deworming program for school-age children was only implemented in 2001 [4] . Honduran data from 2003 onwards is available online on WHO's Preventive Chemotherapy ( PCT ) Databank [19] . Although coverage rates have been sub-optimal , a steady national coverage of around 70% is reported for the last three years for which information is available ( 2009–2011 ) . Despite this strong commitment to the fight against STH infections , adequate PC monitoring has yet to be implemented in Honduras [20] . Moreover , critical information gaps remain on the prevalence of STH infections as well as on infection intensity and polyparasitism at subnational levels [11] . While it is true that there is a paucity of STH research in Honduras , there is to our knowledge , a wealth of scattered information that has been produced for decades by a number of health professionals , scientists , and students ( mainly microbiologists and medical doctors ) as well as governmental institutions . Much of this information is , however , not only unpublished but inaccessible to interested stakeholders ( e . g . , scientific research community , civil society , and decision and policy makers ) . As shown previously by others , active in-country searches of unpublished data are essential to obtaining epidemiological information to assist in decision-making processes [21] . Therefore , to bring to light this important Honduran information , we carried out a systematic revision of the available published and unpublished literature pertaining STH infections produced in Honduras from 1930 to 2012 . Our first objective was to examine the research activity on STH infections , synthesize research evidence , and identify research gaps . Secondly , we selected key data from 2001–2012 to carry out a prevalence analysis for the last decade and map the geographical distribution and prevalence in children ≤15 years old of the three most common intestinal helminths in Honduras , Ascaris lumbricoides , Trichuris trichiura and the hookworms ( predominantly Necator americanus [5] ) . The information search was constrained to the major STH species circulating in Honduras: Ascaris lumbricoides , Trichuris trichiura and the hookworms . No restrictions in terms of study design , authorship , institutional affiliation , or year of publication were set . For online searches , language was restricted to Spanish and English ( the most likely languages to be utilized for international publication by Honduran authors ) . If review studies were identified , a search of the listed primary sources was done , and if retrieved , they were included in the study . To identify potentially relevant information ( i . e . , studies and reports pertaining STH infections in Honduras ) , we followed the strategy described below . All available studies and reports capturing information related to the major STH species circulating in Honduras were assessed by two researchers and two research assistants . Potentially relevant studies were scrutinized and only those providing primary data involving humans and conducted in Honduras were retained for analysis . Retained studies were analyzed , charted , and organized into three categories: those reporting clinical cases or investigating medical outcomes ( clinical research ) ; those reporting treatment efficacy , and those with an epidemiological scope . Data were entered twice for accuracy into spreadsheets ( MS-Excel 2010 ) and summary tables were produced for each category . Descriptive statistics were used to express frequencies . Prevalence of STH infections was calculated from epidemiological studies meeting selection criteria for prevalence analysis . Datasets from surveys done in the same department were averaged to obtain overall prevalence by any STH at the first administrative level . For municipalities , if multiple data were available for the same location , a weighted average prevalence was calculated ( accounting for the sample size in each survey ) . Based on the geographical coordinates of surveys' sites , prevalence maps were generated using ArcGIS 10 . 1 ( ESRI Inc . , California , USA ) . For surveys that had been conducted in small villages nearby municipal capitals , the available geographical coordinates of the latter were used as geo-reference . Prevalence was expressed in risk categories ( i . e . , low , <20%; moderate , ≥20% and <50%; high , ≥50% ) , corresponding to WHO's categories of risk for morbidity to determine preventive chemotherapy administration [4] . A multivariable linear regression model was used to assess association between STH prevalence and socio-economic and environmental variables at the municipality level . Socio-economic variables included Human Development Index ( HDI ) , household overcrowding ( defined as ≥3 individuals per room , excluding bathrooms and kitchen ) , households with potable water , and household with sanitary facility [28] , [29] . Environmental variables included the average annual temperature and average annual precipitation [30] . Other characteristics considered for analysis were dropped from the model because they were either already included in the HDI calculation ( e . g . , literacy , unsatisfied basic needs , poverty ) or because they showed high collinearity with other variables ( e . g . , altitude ) . Statistical analyses were carried out using IBM SPSS Statistics for Windows version 20 . 0 ( Armonk , NY: IBM Corp . ) and Stata 13 ( College Station , TX: StataCorp LP ) . As shown in Table 1 , of 257 initially identified studies , 76 ( 29 . 6% ) were scientific peer-reviewed articles published in national or international journals . The remaining 70 . 4% studies were in the grey literature , most of which only existed in paper on library shelves or researchers' filing cabinets . None of the grey literature was available online . Of the 257 studies selected for scrutiny , 47 ( 18 . 3% ) were either not found or deemed ineligible . In total , 211 studies comprising 329 datasets were retained . Of 211 studies retained , 23 ( 10 . 9% ) fell in the clinical research category , 17 ( 8 . 1% ) focused on treatment efficacy , and 171 ( 81% ) had an epidemiological scope . It was observed that the number of studies on clinical outcomes and treatment efficacy has gradually declined since the 1990s ( Figure 2 ) . We retrieved a total of 135 publications , 81 . 5% of which were dated before 2000 . The oldest article found containing STH data was published in 1930 [43] . Figure 3 shows an analysis of research productivity by decade and source of publication . Temporal trends were observed in publication activity . Interest in conducting STH research in the faculty of medical sciences is reflected by a 3-decade publications activity . After 1980s , however , a sharp decline in STH publications can be observed . According to library records , no medical theses or monographs related to STH have been written since 1992 . Peer-reviewed publications , on the other hand , were more numerous in the late 1950s and again in the 1990s . In the latter decade , 20 publications were produced , 17 of which were articles in Honduran and International journals ( of 14 international articles , 13 were in English and one in Spanish . Five were published between 1950 and 1956; six in the 1990s , and three in each 2001 , 2002 , and 2004 . Figure 2 depicts all studies found by category and period of time . Of the 171 epidemiological studies , 36 met the inclusion criteria for prevalence and geographic distribution analysis . We were able to disaggregate these studies by datasets and municipal level and obtained 108 datasets studying 9 , 336 children from all the country's 18 departments and 69 of the 298 ( 23% ) municipalities . Not all datasets were complete: 12 lacked information on the number of negative samples examined . For this reason , overall STH prevalence was based on only 96 datasets . The majority of municipal datasets derived from single cross-sectional surveys but multiple studies had been done in 18 ( 26% ) municipalities ( in which case weighted averages were calculated to estimate prevalence ) . Also , only 15% of the surveys had been conducted outside municipal capitals . Thus , such data was geo-referenced to the respective capitals' coordinates . Most datasets ( 70% ) were obtained from surveys done by the MoH but additional datasets provided by other authors doubled the sample size and increased the number of municipalities by 15% . Almost half ( 42% ) of the data represented three departments located in central and western Honduras: Francisco Morazán , Santa Bárbara and Copán . Scarcity of data was notorious for departments in the north and east of the country . Altogether , half ( 49 . 1% ) of the children studied were positive for at least one STH , and 27 . 8% , 35 . 3% , and 5 . 1% were positive for A . lumbricoides , T . trichiura , and hookworms , respectively . Consistently , T . trichiura prevalence was higher ( in average , up to 2 . 5 times ) than that of A . lumbricoides . At the departmental level , A . lumbricoides and T . trichiura prevalence were above 20% in 16 ( 89% ) departments . Among those , six departments had prevalences of ≥20–50% for both parasites , whereas in two departments ( Atlántida and Gracias a Dios ) these prevalences exceeded 50% . Hookworm prevalence was more dispersed , ranging from 0–1% and up to 5% in seven and five departments , respectively . The remaining six departments had prevalences ranging from 6% to 23 . 6% . One Department ( Gracias a Dios ) had the highest prevalences for all three parasite species: 51 . 5% , 63 . 8% and 23 . 6% for A . lumbricoides , T . trichiura , and hookworms , respectively . Figure 4 shows the overall and species-specific prevalence as well as the geographic distribution of STH infections according to data from studies done between 2001 and 2012 . Map 4A shows that overall STH prevalence was ≥20% in 84% of the municipal data and also that this prevalence was 50% or higher in 40 . 6% of represented municipalities . As shown in maps 4B and 4C , prevalence data above 20% were common for both A . lumbricoides and T . trichiura ( 47 . 8% and 68% of represented municipalities , respectively ) . Moderate and high-risk areas for these two parasites overlapped in less than 50% of cases . Hookworm infection was observed throughout the country with prevalence ≥20% in 7 . 2% of municipalities ( Fig . 4D ) . Half of the study sites had reports of 0% prevalence for hookworm infection . It is important to note that compared with the rest of the country , municipalities in the South , typically with dryer climate and hotter temperature , had consistently lower STH prevalences . Table 5 shows the results from the multivariable linear regression model testing for associations between selected municipal characteristics and STH prevalence . Human Development Index ( HDI ) was significantly inversely associated with overall STH prevalence ( adjβ = −19 . 3 , 95% CI = −36 . 12 to −2 . 48 , p = 0 . 025 ) and A . lumbricoides infections ( adjβ = −14 . 2 , 95% CI = −27 . 16 to −1 . 24 , p = 0 . 032 ) . A decrease in about 19% and 14% of overall STH and ascariasis prevalence , respectively , was observed per a 0 . 1 increase in the HDI value . Likewise , access to potable water in the household was significantly associated with a decrease in the overall STH prevalence ( adjβ = −0 . 57 , 95% CI = −1 . 01 to −0 . 12 , p = 0 . 014 ) . A similar effect , although only marginally significant , was observed for hookworm infections ( p = 0 . 069 ) . Conversely , the average annual precipitation was significantly associated with increased overall STH prevalence ( adjβ = 0 . 02 , 95% CI = 0 . 01 to 0 . 03 , p = 0 . 006 ) , as well as with the individual species prevalence [A . lumbricoides ( adjβ = 0 . 01 , 95% CI = 0 . 00 to 0 . 02 , p = 0 . 013 ) , T . trichiura ( adjβ = 0 . 01 , 95% CI = 0 . 00 to 0 . 03 , p = 0 . 014 ) ; hookworm ( adjβ = 0 . 01 , 95% CI = 0 . 00 to 0 . 01 , p = 0 . 023 ) ] . Major strengths of this study are its breadth and depth . We made every possible effort to identify , locate , and retrieve a vast amount of work and data from both published and unpublished sources , thereby reducing many of the well-known biases that affect systematic review studies [67] . Importantly , by conducting our search in two languages and not excluding the grey literature in our analysis , we reduced biases in location [67] , selective publication [68] and dissemination [61] . Almost certainly , however , there may remain many other studies or data sources that we were not able to identify ( e . g . , from non-governmental organizations providing deworming ) . As well , our prevalence analysis has unavoidable limitations inherent to pooling of historical data , as indicated in recent publications [69] , [70] . Aware of the diverse quality of studies included ( in terms of sampling strategies and diagnosis accuracy [71] , [72] ) , we aimed at reducing bias by selecting within the epidemiological studies those that were less dissimilar , namely , using data gathered from 2001 onwards , avoiding pooling data from different age groups , and restricting provenance of studies to community and school-based only . Further , to mitigate diagnostic differences , we only selected studies utilizing single-stool examination by the Kato-Katz method . Still , it is widely known that Kato-Katz is subject to variations , and while our prevalence data for A . lumbricoides and T . trichiura are probably reliable , the same cannot be said for hookworm data . Limitations notwithstanding , we provide further evidence that STH infections are widespread in Honduras and are likely affecting the quality of life of the poorest of the poor [3] , [73] . Moreover , we reveal prevalence differentials at sub-national administrative levels , which can prove useful for establishing a historical trail of these infections , and most importantly help design better interventions for their prevention and control [60] . Honduras is making good strives toward sustained implementation of a nation-wide deworming program of both pre-school and school-age children . Here , we propose a five-year outlook of the types of strategies and activities that Honduras as a country could prioritize ( Table 6 ) . Implementing such strategies would help Honduras not only overcome current challenges for sustainable control but also to fill the knowledge gaps identified in the present study . In conclusion , we believe the way forward is to increase the amount and quality of STH research done in Honduras and to make this knowledge publicly available to the scientific community as well as to national and international policy and decision makers . At the same time , efforts directed to STH control and prevention should continue with firm determination and more diversification . As PC coverage reaches the national goal , we advocate for integrated , multi-sectoral approaches [5] , [63] , [74] prioritizing communities where focal transmission shows singular patterns . Differential endemicity is possible because even though Honduras is a small country ( 112 , 492 km2 ) ; it is characterized by a mountainous territory comprising distinct ecological areas with important variations in precipitation , temperature , soil composition , etc . It is also a nation of diverse cultures and ethnicities , and with profound social inequalities [28] . Ultimately , with strong support from the national and international community , Honduras's strategic plan for NTD control has the potential to greatly reduce the health burden of STH infections and other neglected diseases in the country .
Soil-transmitted helminthiases are infections of public health importance in Honduras . Although research data on this topic in the country is somewhat inconsistent and scattered , a wealth of information has been produced by Honduran researchers and practitioners over the years . The vast majority of this information , however , remains inaccessible in the gray literature , thus missing its potential to inform research , policy , and practice . We undertook a thorough review of the literature produced from 1930 to 2012 in order to identify research gaps and , based on a select number of studies , conducted a prevalence analysis with data generated between 2001 and 2012 . Our study reveals that these parasitic infections have not been a focus of sustained research efforts in Honduras . Literature analysis identified current knowledge gaps related to infection risk factors , disease burden , and anti-parasitic drug efficacy , among others . Evaluating and monitoring the national control program also emerged as a priority . Our study also reveals geographic areas of very high endemicity , suggesting that targeted interventions might be appropriate in localized areas of the country . Honduras is at present expanding the deworming program to include pre-school children and the data presented here could serve as a baseline for future monitoring and research .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "medicine", "infectious", "disease", "epidemiology", "epidemiology", "biology", "microbiology", "parasitology" ]
2014
A Scoping Review and Prevalence Analysis of Soil-Transmitted Helminth Infections in Honduras
The spliceosome , a sophisticated molecular machine involved in the removal of intervening sequences from the coding sections of eukaryotic genes , appeared and subsequently evolved rapidly during the early stages of eukaryotic evolution . The last eukaryotic common ancestor ( LECA ) had both complex spliceosomal machinery and some spliceosomal introns , yet little is known about the early stages of evolution of the spliceosomal apparatus . The Sm/Lsm family of proteins has been suggested as one of the earliest components of the emerging spliceosome and hence provides a first in-depth glimpse into the evolving spliceosomal apparatus . An analysis of 335 Sm and Sm-like genes from 80 species across all three kingdoms of life reveals two significant observations . First , the eukaryotic Sm/Lsm family underwent two rapid waves of duplication with subsequent divergence resulting in 14 distinct genes . Each wave resulted in a more sophisticated spliceosome , reflecting a possible jump in the complexity of the evolving eukaryotic cell . Second , an unusually high degree of conservation in intron positions is observed within individual orthologous Sm/Lsm genes and between some of the Sm/Lsm paralogs . This suggests that functional spliceosomal introns existed before the emergence of the complete Sm/Lsm family of proteins; hence , spliceosomal machinery with considerably fewer components than today's spliceosome was already functional . The modern spliceosome is a sophisticated molecular machine consisting of over 200 protein and 5 RNA components . The appearance of the spliceosome was abrupt; it is absent in prokaryotic cells , yet simple eukaryotic organisms have a rather complex spliceosome containing at least 78 proteins [1] . The question addressed here is , can we discern the steps in the evolution of the spliceosome ? The Sm/Lsm family of proteins provides potential insight into this question since this family is one of the earliest pieces of the spliceosomal complex , one which stabilizes the RNA components in the “heart” of the spliceosome [2] , [3] . Even though most previous studies discuss the role of Lsm ( Comment #1 ) proteins in splicing , they perform multiple other functions in eukaryotic cells; modification and degradation , protein chaperoning and degradation , and even translation [4] , [5] . Eukaryotic Sm proteins , on the other hand , are dedicated almost exclusively to splicing , but even they exhibit at least one exception [6] . Sm/Lsm counterparts exist in archaea ( Sm proteins ) and bacteria ( Hfq protein ) where no spliceosomal introns and spliceosomal apparatus has been found . Bacterial Hfq is similar to eukaryotic Lsm in its many roles in RNA/protein biogenesis [5] . Archaeal Sm-like proteins are associated with RNase P and thus likely involved in pre-tRNA processing [7] . It is possible that additional functions of Sm-like proteins in archaea are yet to be discovered . The association of Sm/Lsm proteins with all five snRNA components ( U1 , U2 , U4 , U5 and U6 ) of the spliceosomal complex is critical for splicing [8] . Sm/Lsm proteins assemble as multimers to form a toroid ( doughnut-shaped ring ) around the U-rich motif of each snRNA thus stabilizing the RNA structure and promoting the binding of other U-specific proteins to the spliceosomal RNP as they assemble [2] , [4] . Structurally , each Sm/Lsm protein monomer is a small five-stranded β-barrel in which β-strands 4 and 5 are linked through a 3–10 helix to form a wide-open hinge over the rest of the barrel . These two strands are involved , on the external side , in monomer-monomer interactions to maintain the doughnut-shaped heptameric ring , and surround the RNA [2] ( see PDBid 1i81; ( Figure S1 ) . The loops between β-strands 2 and 3 and between β-strands 4 and 5 ( the 3–10 helix ) face into the lumen of the ring , where they interact directly with the RNA . Residues within each loop and the adjacent strand form two nucleotide binding pockets ( one per loop ) ; these are among the most conserved residues in the entire structure ( Fig S3 ) . Each of the two pockets is contained within a different sequence motif . Motif I ( also called SM1 ) includes β-sheets 1–3 , while motif II ( SM2 ) includes β-sheets 4 and 5 ( 1 ) ( Pfam PFO1423 , Interpro IPR001163 ) . The loop between β-strands 3 and 4 is quite long ( up to 25 residues ) in some eukaryotic Sm proteins but much shorter or practically absent in Hfq , the bacterial counterpart [9] ( Figure S4 ) . The structure of the β-barrel is preserved among the three superkingdoms of life in spite of a low level of sequence identity ( Figure S4 ) . The Sm fold ( b . 38 in the SCOP classification ) [10] is closely related to the SH3 fold ( b . 34 ) , sharing the same topology , but varying structurally in the loops , and to the OB fold ( b . 40 ) , with a topological permutation [11] ( Figure S5 ) . The SH3 and OB folds are small β-barrels found in many proteins . They are involved in a broad range of interactions with nucleic acids ( OB ) , and in protein-protein interactions ( SH3 ) . These β-barrels are likely ancient and derived from a single framework from which many functions emerged , including RNA binding as described here . The Sm fold , in its shortest form , namely bacterial Hfq , exhibits approximate internal pseudo C2-symmetry; β-strands 1 , 2A and 2B can be superimposed onto β-strands 3 , 4 and 5 ( Figure S2B ) . This suggests a possible even earlier ( initial ) duplication event in bacteria . The ring formed by Sm/Lsm proteins around RNA can be homomeric or heteromeric . In bacteria , where there is typically only one copy of the Hfq ( Sm-like ) gene , the ring is homo-hexameric . In archaea , there are one or two genes and consequently one or two Sm rings each formed by homomeric components ( it is also possible to have one hexameric and one heptameric homomer [12] . In eukaryotes there are a total of 8 distinct Lsm and 7 distinct Sm genes . Several types of rings exist . The most abundant and best studied are those involved in splicing . The Lsm ring involved in splicing is formed by seven distinct Lsm proteins ( Lsm2–8 ) and the Sm ring involved in splicing is formed by 7 distinct Sm components ( SmB , D1 , D2 , D3 , E , F , G ) . The Sm ring interacts with the U1 , U2 , U4 and U5 RNA components of the spliceosome , while the Lsm ring interact in a similar manner with U6 [4] , [8] . Several additional hetero heptameric rings have been identified [4] that are associated with other functions . The most prominent ring is the Lsm1–7 ring involved in mRNA decapping [13] . For the sake of clarity of presentation we will not consider the Lsm1 gene further in this paper , nor will we consider other rings besides the Lsm and Sm rings described above . Thus , while there are 8 Lsm genes , we will only consider 7 Lsm genes , Lsm2–Lsm8 . The conversion of homomeric into heteromeric complexes has occurred frequently in eukaryotic evolution , for example , the eukaryotic 20S proteasome [14] , exosome [15] , type II chaperonines [16] and ubiquitin-like proteins [17] . In all these examples there is extensive gene duplication and subsequent sequence divergence that results in multiple distinct paralogs all coming together to assemble into a structure quite similar or nearly identical to that constructed by their homomeric counterparts in prokaryotes . The reasons for such extravagant gene family expansions in eukaryotes are not completely understood , though heteromeric complexes represent a simple and elegant way to make more specific functional interactions among individual subunits and to establish a specific order of subunit interaction by breaking symmetry [16] . More generally it offers a means to achieve more complex regulatory mechanisms , by converting essentially a one-component system into a multi-component system [18] . We argue that in the case of Sm/Lsm rings , the recruitment into the complex spliceosomal machinery , at least in part , is responsible for creating such a large paralogous family . What were the origins of the spliceosomal introns which triggered the development of the spliceosomal machinery ? Several authors have suggested that the emergence of spliceosomal introns was caused by the introduction of self-splicing type II introns into the early eukaryotic ancestor [3] , [19] , [20] . The self-splicing introns then evolved into spliceosomal introns , by gradually losing their conserved RNA structural elements necessary for correct assembly and self-splicing . These elements gradually migrated from the introns into the cellular genome , becoming snRNA genes and were provided in trans to serve a similar role of aligning the exons during the spliceosomal process . Indeed , extensive base pairing between snRNAs and pre-mRNA in the spliceosome , which is required for the formation of tertiary RNA structure in which exons are juxtaposed [21] , is similar to that found in self-splicing type II introns . In particular , the domain 5 stem-loop structure is similar to U6 RNA [22] , while the ID3 step-loop structure is functionally similar to , and can be rescued by , U5 RNA [23] . Thus self-splicing introns appear to be sources of both spliceosomal introns and parts of spliceosomal machinery ( RNA components ) . Group II self-splicing relies almost exclusively on RNA for alignment of splice junctions as well as the splicing reaction itself; the only protein component required is maturase ( coded within the self-splicing intron ) . It has been proposed by several authors [2] , [3] that Sm/Lsm proteins perform a function similar to that of maturase by reducing electrostatic repulsion between RNA components [2] . In this scenario Sm/Lsm proteins are indeed the first protein components of the developing spliceosome . This notion is further supported by the fact that an Sm/Lsm ring is formed around each snRNA; thus Sm/Lsm rings precede , functionally and temporally , most of the other spliceosomal components which are unique to each snRNA . Later , Sm/Lsm rings around snRNA begin to also serve as a structural platform that enabled additional and more specific interactions between other snRNP components [24] . Like most eukaryotic genes , Sm and Lsm genes have spliceosomal introns . The presence of the spliceosomal introns in the genes , which themselves are involved in the removal of introns , is intriguing and useful in pinpointing some evolutionary events , as we will see subsequently . It is important to bear in mind that when the intron position is conserved in orthologous genes , the parsimonious approach argues that the insertion of the intron occurred in an ancestral gene . If the identical intron position can be traced all the way back to deep branching eukaryotes , it can be argued that this intron existed in the Last Eukaryotic Common Ancestor ( LECA ) . Identity of the intron position can be complete ( when not only the position , but also the phase is conserved ) or partial ( when intron phases are different ) . The latter occurs when intron positions vary by one or two bases within DNA and is referred as intron ‘sliding , ’ ‘slippage , ’ or ‘frameshift . ’ Clearly documented cases of intron sliding have been reported [25] , [26] and even opponents of intron sliding theory admit that the phenomenon cannot be ruled out [27] . Recent work provides strong support for intron sliding and suggests it as the main mechanism for intron loss and gain [28] . The possibility of intron sliding by one base has strong statistical support [29] . The presence of introns in identical positions across multiple species may also have resulted from multiple independent insertion events into proto-splice sites [30] . Although this possibility cannot be discarded , recent studies have found that such multiple insertions are statistically infrequent events [31] . In this work we combine previously known ( but disjointed ) functional/structural information about Sm/Lsm proteins with new evidence coming from the phylogenetic analysis of the Sm/Lsm protein family and molecular analysis of intron positions in Sm and Lsm genes . Jointly these data point to some important events in the evolution of the early spliceosomal machinery . Comment #1 . There are several different nomenclatures used for these proteins , hence causing confusion . The original eukaryotic proteins were coined Sm by Michael Lerner and Joan Steitz after the name of one of the patients with systemic lupus erythematosis from whose cell extracts snRNPs were immunopercipitated [32] . Lsm proteins ‘like Sm’ were called so because of their structural similarity to already identified Sm proteins [4] . The term Sm is also frequently applied to archaeal proteins with similar sequence and structure . In bacteria the protein is shorter , due to the absence of one of the internal loops; it was originally identified as virulence factor in E . coli required for phage Qβ replication , hence its name Hfq [33] . Recently an Hfq-like protein was identified in archaea M . jannaschii [34] , indicating plasticity and interchangeability among Sm and Sm-like proteins . Sometimes the term Lsm is applied to the entire family [35] , unfortunately this somewhat ambiguous term , which is particularly ill-suited to this paper where we discuss similarities , differences and evolutionary relationship between Sm and Lsm proteins . In this paper we refer to Sm proteins as either eukaryotic or archaeal in origin , whereas Lsm proteins are all eukaryotic . Hfq is the Lsm counterpart in bacteria . We refer jointly to eukaryotic Sm and Lsm proteins as Sm/Lsm for the sake of brevity . A comparison of prokaryotic and eukaryotic genes provides evidence for a major evolutionary event early in eukaryote evolution . We collected and analyzed the sequences and gene structures of 335 Sm/Lsm genes covering 80 organisms from the three domains of life . All of the eukaryotes , with the exception of some early branching eukaryotes , have a complete set of 14 Sm/Lsm proteins ( Comment #2 ) as compared to only one or two copies in prokaryotes . Phylogenetic analysis based on maximum likelihood ( PhyMl ) detects pair-wise relationships between most of the Sm-Lsm gene pairs ( Figure 1 ) . The relationships between Lsm and Sm genes are as follows: Lsm2-SmD1 , Lsm3-SmD2 , Lsm4-SmD3 , Lsm5-SmE , Lsm6-SmF , Lsm7-SmG , Lsm8-SmB . This result suggests a scenario in which two subsequent waves of duplications occurred: the first wave resulted in 7 paralogous genes , while the second wave saw the duplication of each of the seven paralogs , bringing the total to 14 genes . To find out which of the genes , Sm or Lsm , arose on the first wave of duplication , we further constructed Lsm-only ( Figure 2 ) and Sm-only trees ( Figure 3 ) . A tree built from Lsm genes only ( Figure 2 ) has a similar topology to that of the eukaryotic Sm/Lsm tree ( Figure 1 ) , while the Sm-only tree indicates weaker relationship among Sm genes ( Figure 3 ) . Also some of Sm branches are longer than their Lsm counterparts: SmD3-Lsm4 , Lsm5-Sm4 , Lsm7-SmG , Lsm8-SmB ( Figure 1 ) . This suggests that the Sm genes have diverged further than Lsm genes , suggesting that they appear in the second wave of duplication , arising from already diversified Lsm paralogs and then proceeded to diversify further . Both waves of duplication are followed by subfunctionalization . This order of the events is further supported by functional analysis [5] . Lsm genes are involved in many RNA-processing functions , most of which evolutionary precede splicing . Sm genes , on the other hand , are almost exclusively dedicated to splicing . Although with uncertainty , it is possible to infer some order of events during the initial wave of duplication by inspecting Sm/Lsm and Lsm trees ( Figures 1 and 2 ) . One of the early duplications gave rise to the ancestor of the Lsm2–Lsm4 gene pair; the other early duplication gave rise to the ancestor of the four remaining genes: the Lsm7–Lsm8 pair and Lsm3–Lsm5 pair of genes . The pair-wise relationship among paralogs is still detectable: Lsm2–Lsm4 , Lsm3–Lsm5 , and Lsm7–Lsm8 . The Lsm6 gene is roughly equidistant from the remaining paralogs . While many of the bootstrap values on the maximum-likelihood trees are quite high , some others are rather low , indicating an uncertainty with regards to the branching order . The same order of branching was observed in the rooted trees when eubacterial sequences were used as an outgroup ( data not shown ) . However , use of an outgroup resulted in the reduction of the bootstrap values throughout the tree . We attribute this effect to the quality of the alignment between eubacterial and eukaryotic sequences , which is even shorter than eukaryotic alignment alone . The bacterial sequences are missing a long loop between beta-strands 3 and 4; and the second motif ( SM2 ) - which covers beta strands 4 and 5 - is matched rather poorly . ( Comment #3 ) Phylogenetic trees built using Bayesian inference ( Figures S6 , S7 , S8 ) are quite similar , though not identical to the trees built using a maximum likelihood approach . Sequence searches using each of the Lsm genes successfully recover their Sm counterpart with high levels of certainty ( data not shown ) . The type of duplication observed in Sm/Lsm genes is referred as ‘frozen duplications’ ( 9 ) . The number of paralogs reaches a certain number , and then stops without further expansion in any lineage . This phenomenon can be explained by the need to maintain a stochiometric balance among interacting proteins . Gene duplication resulting in gene paralogy and subsequent innovation was common during early eukaryotic evolution [18] , [36] . The most extensive duplications took place in gene families involved in information processing or associated with the formation of multimeric proteins [18] . The Sm/Lsm gene family fits both these criteria; they form a multimeric ring which consists of seven distinct , but related components . Sequence analysis reveals that the Sm/Lsm gene family had nearly achieved its current configuration by the time of the last eukaryotic common ancestor ( LECA ) emerged . The total sequence divergence among Sm and Lsm genes before LECA ( Figure 4 ) is 2–4 times ( see ‘Calculating the level of sequence conservation’ in Text S1 , Table S1 ) as extensive as the subsequent divergence that has taken place since the emergence of LECA approximately two and a half billion years ago ( Figure 5 ) . If we assume that the first eukaryotes appeared as early as 3 billion years ago , then the divergence that led to the LECA type of Sm/Lsm gene family took place during that half billion year period—10–20 times as rapid as the subsequent divergence in the two and a half billion years since LECA . We have attempted to assemble a complete set of Sm and Lsm genes for some of the eukaryotic lineages . We find that the completeness of Sm and Lsm gene families ( Table 1 ) correlates well with the number of introns present in each genome of these eukaryotes . For example , the microsporidian Encephalitozoon cuniculi , , the kinetoplastid Trypanosoma brucei and the protist Giardia lamblia all have fewer introns per genome and have less regular and less complete sets of Sm/Lsm proteins than other eukaryotes ( Table 1 ) . In contrast , the amoebozoan Dictyostelium discoideum and the apicomplexan parasite Plasmodium falciparum have many introns and a nearly regular set of Sm/Lsm proteins . Incompleteness of the Sm/Lsm families in these eukaryotes is most likely due to the evolution of individual Sm/Lsm components beyond sequence recognition . Indeed most of the detected Sm and Lsm sequences , while clustering correctly , have long branches indicating extensive divergence . It is also possible that some Sm or Lsm components were lost along with the majority of the introns in these organisms during streamlining of the genome . However , most of the above parasitic organisms ( as well as the nucleomorph G . theta ) could potentially use the host's Sm/Lsm components for splicing . Most of the eukaryotic Sm/Lsm genes from the 22 species included in this study contain several introns per gene ( Figures 6–13 ) . Within each of the seven Lsm genes , and within several Sm genes , the positions of some of these introns are highly conserved across species . Sometimes this conservation extends from D . discoideum , E . histolitica and P . falciparum , through plants , fungi and animals ( Figures 7–13 ) . The majority of the introns which exhibit conserved position and phase across multiple species are unique to each of the 14 Sm or Lsm genes ( Figure 6 ) . Several Sm-Lsm gene pairs share identical intron positions and phases ( Lsm6-SmF , Lsm7-SmG; Lsm4-SmD3 , Figures 7 , 8 , and 12 ) , or the same position but a different phase ( Lsm5-SmE; Figure 9 ) . Furthermore , Lsm6 and Lsm8 have two different introns in identical positions , though their phases are different ( Figure 6 ) ( Comment #4 ) . The phase difference in all cases is 1 base . Comment #2 . Some of the early branching eukaryotes have a subset of 14 Sm/Lsm genes ( Table 1 ) . Comment #3 . Archael Sm genes are themselves a diverse group of sequences and consequently they cluster at several points within the eukaryotic tree rather than serving as a genuine outgroup . We believe this is because the sequence is rather short and can absorb mutations with ease , as the structure of the small beta-barrel is nearly impervious to mutations . These two features ( short sequence and fully explored sequence space in both eukaryotes and archaea ) make it impossible to conduct a traditional outgroup analysis using archaeal sequences . Comment #4 . Another intron shares position between Lsm3 and SmE , suggesting an ancestral connection between Lsm3 and Lsm5 genes . This is a more complicated scenario in which the ancestral introns are present in Lsm3 and Lsm5 , transferred into the SmE genes after gene duplication and subsequently lost from Lsm5 . Phylogenetic analysis indicates that the expansion of the Sm/Lsm family in eukaryotes proceeded through two distinct waves of duplication . In the first wave of duplication seven copies that later resulted in either the Lsm or the Sm genes arose through duplication from an ancestral gene . These copies then underwent extensive sequence divergence before the second wave of duplication took place . During this second wave each of the seven genes duplicated again , bringing the total number to fourteen . The extent of divergences among the paralogs is so great that many of the relationships among the seven initial paralogs cannot be reconstructed with certainty . ( Figures 1 and 2 ) . Nevertheless , some order of duplication events during the first wave can be discerned from the phylogenetic tree . The Lsm6 gene is probably the original Lsm gene , as it is roughly equidistant from the remaining six Lsm genes . Two early duplications of the ancestral Lsm gene gave rise to what was the ancestor of the two major branches – one consisting of Lsm2–Lsm4 pair , the other consisting of two pairs Lsm3–Lsm5 , and Lsm7–Lsm 8 ( Figure 1 ) . Lsm7 and Lsm8 are the most closely related genes and possibly reflect the last duplication event of the first wave . A very similar scenario can be derived from trees built using Bayesian inference ( Figures S6 , S7 , S8 ) . The only difference is that Lsm3 and Lsm5 are more distant from each other and do not form a clear pair-wise relationship . The order of events in the second wave of duplication is impossible to predict , however the pairing between the original Lsm and the derived Sm counterpart is clearly detectable ( Figure 1 ) . The relationships between the 7 Sm genes are less clear , as would be expected if they took off and continued to evolve whereas the Lsm genes ceased to diverge . Extensive sequence divergence observed between prokaryotic and eukaryotic orthologs is a typical feature of early stages of eukaryogenesis , where orthologous genes diverge sometimes to the point where their common ancestry is only discernable from structure [36] . The levels of divergence among the 14 paralogous Sm and Lsm genes ( Figures 4 and S3 ) are noteworthy . Lsm genes are known to be involved in multiple cellular functions , all of which precede splicing [4] , [5] . Lsm proteins , or their precursors , were very likely ‘recruited’ into the splicing machinery , further expanding the functional roles of the Lsm ring . As the seven copies of the Lsm genes diverged from each other , they were under multiple functional constraints to accommodate the different functions of the Lsm ring . The evolving splicing machinery may have required features from the Lsm ring which were in conflict with its other functions . The second wave of duplication resulted in a second ring ( Sm ring ) dedicated exclusively to the spliceosomal machinery ( subfunctionalization ) . Sm genes continued to diverge extensively; some possible reasons for this divergence are discussed below . It is clear however that sufficient spliceosomal machinery was already in place to perform infrequent splicing before the appearance of the dedicated Sm ring . The evidence for Lsm-only splicing comes from close examination of intron positions within the Sm and Lsm genes . It is not surprising that Sm and Lsm proteins—the components of the spliceosome—have spliceosomal introns themselves , since the vast majority of the eukaryotic genes contain introns . What is remarkable is that some of the intron positions are highly conserved across most of the 22 species studied ( Figures 6–13 ) . This level of intron conservation in these genes is greater than most other gene families . A study by Rogozin et al . [37] of intron positions in 684 orthologous genes in 8 species showed that intron positions are conserved only rarely across more than three species . In our dataset of Lsm and Sm genes many of the intron positions are conserved across 4–7 of the same species reported by Rogozin et al . ( Comment #5 ) . A recent study identified intron positions in 19 eukaryotic species [38] . A small fraction of the introns are conserved in 12–16 species; most of these introns are in genes associated with DNA/RNA processing and protein chaperoning/secretion ( manuscript in preparation ) . Here we refer to such introns as ‘extremely conserved’ , implying the conservation of intron position . The presence of such ‘extremely conserved’ introns in the genes that are themselves key components of the spliceosome provides us with a unique opportunity to pinpoint the appearance of early functional spliceosomal introns relative to the development of the splicing machinery itself . The parsimonious approach argues that introns that exhibit highly conserved positions across multiple species are likely to stem from single intron insertion events that happened in the ancestral genes . The majority of introns which exhibit conserved position and phase across multiple species are unique to each of the 14 Sm or Lsm genes ( Figure 6 ) . This implies that these introns were introduced into the genes after the 14 separate Sm/Lsm paralogs arose by duplication in the lineage leading to the LECA . However , several Sm-Lsm gene pairs share identical intron positions and phases ( Lsm6-SmF , Lsm7-SmG; Lsm4-SmD3; Figure 7 , Figure 8 , Figure 12 ) or the same position but a different phase ( Lsm5-SmE; Figure 9 ) . These introns , it can be argued , were inserted into Lsm genes before the second duplication that gave rise to Sm-Lsm pairs , indicating that some successful splicing events took place before the Sm ring was established . Further , Lsm6 and Lsm8 have two different introns in identical positions ( though their phases are different ) and Lsm3 and Lsm5 share one intron position ( through SmE inference ) , arguing that some functional introns predate even the appearance of the complete set of seven Lsm genes ( Figures 1 and 2 ) . Thus , some successful splicing could occur before the formation of the Sm ring , that is , during the initial wave of duplication that led to the formation of 7 unique Lsm genes . The fraction of introns with ‘shared’ positions between Lsm genes or between Sm genes and the corresponding Lsm counterparts is relatively small , perhaps indicating the challenges facing early spliceosomes , but more likely indicating that spliceosomal introns were likely to have been uncommon at that stage of spliceosome development . Indeed it had been recently observed that ancient paralogs share dramatically fewer intron positions than more recently formed paralogs , or even most evolutionary distant orthologs [39] . As indicated by the cases of reduced eukaryotes , which have some highly divergent or even missing Sm/Lsm genes , infrequent splicing can be accomplished with less than a full complement of these genes ( Table 1 ) ( Comment #6 ) . Splicing , as we suggest here , could be conducted with the Lsm ring alone , yet an additional ring ( Sm ) dedicated exclusively to the spliceosome arises . As we discuss above , the original Lsm ring was involved in multiple functions and its further evolution could have been hampered by multiple contradictory constraints . The appearance of a dedicated Sm ring could have allowed splicing events to become more prevalent in the cell . This alone could explain the pressure for the dedicated Sm ring . However , a more detailed look into the differences between Sm and Lsm rings gives us further insights into possible evolutionary pressures leading to the appearance of the Sm ring . In the modern spliceosome the Lsm ring is associated with only one of the five snRNAs—namely , U6 RNA . U6 RNA is different from the four other snRNAs in several ways . First , it is the only RNA component that is transcribed by polymerase III and has a γ-monomethyl cap ( U1 , U2 , U4 and U5 are transcribed by polymerase II and have a m3G cap ) . Second , U6 never leaves the nucleus: the Lsm ring is assembled in the cytoplasm and migrates to the nucleus to bind U6 RNA ( which is quite different from the behavior of the other four snRNAs as we will see below ) . Third , U6 RNA is strikingly similar to the catalytic effector ( domain 5 ) of the of the self-slicing group II structure [22] . Recently determined crystal structure of self-splicing group II introns further shows detailed similarity between domain 5 ( DV ) and U6 RNA of the spliceosome [40] . The Sm ring , on the other hand , assembles around the remaining four snRNAs - U1 , U2 , U4 , and U5 . The interactions and particularly the assembly of the Sm ring around these snRNAs is much more complex than the assembly of Lsm ring around U6 RNA . Unlike U6 RNA , U1 , U2 , U4 and U5 RNAs are exported into the cytoplasm , where they associate with the Sm ring and then are re-imported back into the nucleus . The assembly of the Sm ring requires assistance of a large SMN protein complex [41] and a 20S methylosome . One of the reasons for such a complicated assembly might be that the U-rich track to which the Sm ring binds is buried deep in the tertiary structure of the snRNA molecule [12] ( this is different from U6 , where the track is close to the 3′-end and is exposed ) and some assisted refolding of the RNA by the SMN complex may be necessary . The SMN complex associates with snRNPs through the entire cytoplasmic biogenesis on its way toward nuclear import . The interaction between Sm proteins and the SMN complex takes place through RG-rich tails on Sm proteins . Several of the Sm proteins—SmD1 , SmB and SmD3 ( Comment #7 ) —are significantly longer than their Lsm counterparts due to such RG-rich tails . These tails are also involved in the import of the Sm-RNA complex back into the nucleus [42] . It is possible that the modifications we observe in the Sm proteins , and even the appearance of the Sm ring itself , is related to the formation of the nucleus in the early eukaryotic ancestor ( Comment #8 ) . In the compartmentalized cell the spliceosomal RNA components ( U1 , U2 , U4 U5 , but not U6 ) consequently had to be imported back into the nucleus and the association with Sm ring was essential for their nuclear import . In total the Sm proteins underwent many changes relative to their Lsm counterparts , including changes to the electrostatic charge distribution on the surface of the ring [2] , [12]—a further adjustment to the compartmentalization of the eukaryotic cell . It will be interesting to see if hitherto unrecognized features of the spliceosomal machinery can be linked to the formation of the nucleus . Using our data and other information we can partially reconstruct a possible sequence of events in the early formation of the spliceosome with respect to Sm/Lsm proteins . As self-splicing type II introns are gradually converting into spliceosomal introns , a primitive ‘proto-spliceosome’ is at work successfully removing some introns from the transcripts ( this includes removal of introns in the Sm and Lsm genes themselves ) . How functionally complex was the initial ‘proto-spliceosome’ is difficult to determine . Essential are the RNA components that assured formation of correct secondary structure that bring the ends of the adjacent exons into proximity . It is most likely that U6 RNA is one of the basal components of the proto-spliceosome . Were there other RNA components involved ? It has recently been demonstrated that splicing can proceed with just 2 of the 5 snRNAs; namely U6 and U2 can catalyze the spliceosomal reaction [43] . In order to achieve regular splicing events , several , if not all RNA components would be needed and would be gradually added to the developing spliceosome . While currently we can not determine the order in which snRNAs were added , it is likely that all of them were associated with the Lsm ring , which stabilized electrostatic charges around the splice site . The original Lsm ring involved in early splicing may not have yet developed its seven distinct components , but was somewhere within the first wave of duplication ( since Lsm 6 and Lsm 8 as well as Lsm3 and Lsm5 have shared intron positions ) . Once seven unique Lsm components of the ring were formed , there was a lengthy period in which the hetero-heptameric Lsm ring does splicing alone ( without the Sm ring ) , as evidenced by the extensive sequence divergence among the Lsm genes , as well as the accumulation of Lsm-specific introns . Sometime later a fully dedicated Sm ring appears , brought about by the duplication of each of the original Lsm components in the second wave of duplication . The appearance of the Sm ring could have been the result of the developing nucleus and the compartmentalization of the cell . Whether Sm-Lsm ‘hybrid’ rings ( Comment #9 ) were intermediary in this process is an interesting question to ponder . Gradually the Sm proteins loose their ability to self-assemble into a ring; instead an SMN complex controls Sm ring assembly around U1 , U2 , U4 and U5 snRNAs; the resulting snRNPs are transported into the nucleus and become a central part of the spliceosome . To some extent we had been lucky to have a ‘frozen event’—the association of U6 with the Lsm ring in the contemporary spliceosome—which helps us reconstruct a possible evolutionary history of Sm/Lsm proteins and strongly suggests that the Lsm ring was the original ring to be ‘recruited’ into the spliceosome and which later gave rise to the ‘dedicated’ Sm ring . In fact the use of the Sm/Lsm ring and other components from the major spliceosome in the minor spliceosome , which developed subsequent to LECA [1] and has many U12-specific components , is a good example of the continuation of the ‘recruitment’ phenomenon during the evolution of splicing . We suspect that similar scenarios of ‘recruitment’ followed by the emergence of a dedicated component through duplication exist for other spliceosomal components which were gradually added to the evolving spliceosome as its complexity increased . Whether the evolutionary history of spliceosome assembly can be teased out from the existing data remains to be seen . Notwithstanding , we hope that this type of molecular analysis , combined with structural and functional prior knowledge , can be extended to other components of the spliceosome to gain a better understanding of the events that took place at the dawn of spliceosomal introns . Comment #5 . Since we tested a total of 22 eukaryotic species for the presence of introns in Sm/Lsm genes , some intron position exhibit an even higher level of conservation than reported by Rogozin et al . Comment #6 . Since most of the simple eukaryotes in Table 1 are parasites , it is possible that absent Sm/Lsm genes are ‘supplemented’ by the host genome . Nevertheless , the fact that many of Sm/Lsm genes are retained in the parasite genome ( albeit being highly divergent ) suggests that they are used . Comment #7 . Interestingly , Lsm4—the proposed progenitor of SmD3—also has a RG-rich tail . Comment #8 . The appearance of the nucleus being a direct consequence of the appearance of spliceosomal introns was proposed recently [3] . Comment #9 . The Sm-Lsm ‘hybrid’ ring is detected in association with U7snRNA which is implicated in histone pre-mRNA processing rather than splicing [6] . The 335 sequences or the subsets of 335 sequences were aligned using ClustalW ( http://align . genome . jp ) under the following conditions: Scoring matrix used: BLOSUM62; Gap Open Penalty = 12 and Gap Extension Penalty = 0 . 1 . The alignment was trimmed at N-terminus and C-terminus ( to avoid regions rich in gaps ) ; Jalview tool was used for the purpose of alignment editing ( http://www . jalview . org ) . The final alignment used in phylogenetic analysis contains 96 residues . Two types of trees were constructed: For all eukaryotic Sm/Lsm genes the presence of introns was checked ( manually ) using the NCBI Gene database . For genes containing introns , the Wise2 tool ( http://www . ebi . ac . uk/Wise2/index . html ) was used to determine the exact position and the phase of each intron . TheWise2 tool was used in interactive mode under the default conditions . Both DNA and protein sequence which serve as an input into Wise2 were downloaded from NCBI . The results of Wise2 were processed manually; by marking intron positions on the protein sequences , using distinct colors to mark the intron's phase . Additional information on sequences in this analysis as well as calculation of conservation level can be found in the Text S1 .
The spliceosome is a complex molecular machine that removes intervening sequences ( introns ) from mRNAs . It is unique to eukaryotes . Although prokaryotes have self-splicing introns , they completely lack spliceosomal introns and the spliceosome itself . Yet even the simplest eukaryotic organisms have introns and a rather complex spliceosomal apparatus . Little is known about how this amazing machine rapidly evolved in early eukaryotes . Here , we attempt to reconstruct a part of this evolutionary process using one of the most fundamental components of the spliceosome—the Sm and Lsm family of proteins . Using sequence and structure analysis as well as the analysis of the intron positions in Sm and Lsm genes in conjunction with a wealth of published data , we propose a plausible scenario for some aspects of spliceosomal evolution . In particular , we suggest that the Lsm family of genes could have been the first and the most essential component that allowed rudimentary splicing of early spliceosomal introns . Extensive duplications of Lsm genes and the later rise of the Sm gene family likely reflect a gradual increase in complexity of the spliceosome .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "evolutionary", "biology/evolutionary", "and", "comparative", "genetics", "computational", "biology/molecular", "genetics", "evolutionary", "biology/genomics", "computational", "biology/evolutionary", "modeling", "evolutionary", "biology/bioinformatics", "computational", "biology/genomics" ]
2009
Sm/Lsm Genes Provide a Glimpse into the Early Evolution of the Spliceosome
An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species . More than 54 , 000 polymorphic SNPs provided an average inter-SNP spacing of ∼43 kb . The mean minor allele frequency across domestic horse breeds was 0 . 23 , and the number of polymorphic SNPs within breeds ranged from 43 , 287 to 52 , 085 . Genome-wide linkage disequilibrium ( LD ) in most breeds declined rapidly over the first 50–100 kb and reached background levels within 1–2 Mb . The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse . Multidimensional scaling ( MDS ) analyses demonstrated the tight grouping of individuals within most breeds , close proximity of related breeds , and less tight grouping in admixed breeds . The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS . Genotyping of other Perissodactyla ( zebras , asses , tapirs , and rhinoceros ) was variably successful , with call rates and the number of polymorphic loci varying across taxa . Parsimony analysis placed the modern horse as sister taxa to Equus przewalski . The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus ( MC1R ) and defining a conserved haplotype of ∼750 kb across all breeds . These results demonstrate the high quality of this SNP genotyping resource , its usefulness in diverse genome analyses of the horse , and potential use in related species . Horses have held a valued place in human civilization for over 5 , 000 years through service in war , agriculture , sport and companionship [1] . Over the last several centuries , more than 400 distinct horse breeds have been established by genetic selection for a wide number of desirable phenotypic traits [2] . In contrast to other large domestic animal species including cattle , chickens , sheep , swine , goats and camelids that are selectively bred mainly for production of food ( meat , milk , eggs ) or fiber , the domestic horse is primarily a utilitarian animal - bred for endurance , strength , speed , and metabolic efficiency [1] . The horses' use as a work animal and means of transport required selection for individuals that were able to perform daily physical activity even when feedstuffs were scarce . The natural athleticism of horses and their enforced intensive exercise regimes makes them outstanding models for study of the musculoskeletal , cardiovascular and respiratory systems , while their natural susceptibility and resistance to infectious agents is useful in studies of the immune system . Understanding the genetic basis for within and among breed variation in equine health , disease and performance traits will continue to provide important information on mammalian biology and genetic mechanisms of disease . The horse was selected by the National Human Genome Research Institute ( NHGRI ) for whole genome shotgun sequencing as a representative of the order Perissodactyla . The genome of the female Thoroughbred Twilight was sequenced to 6 . 8 fold coverage at the Broad Institute of Harvard and MIT accompanied by paired-end sequences from over 150 , 000 BAC clones performed at the Helmholtz Centre for Infection Research , and the University of Veterinary Medicine Hannover , Germany . This project has produced the EquCab2 . 0 assembly with a total contig length of 2 . 43 Gb , 96% of it assigned to chromosomes , and a predicted genome size of 2 . 67 Gb ( http://ncbi . nlm . bih . gov/genome/guide/horse ) . A significant SNP discovery component within the NHGRI project identified ∼750 , 000 SNPs from Twilight and ∼400 , 000 SNPs from seven horses of different breeds , enabling an estimate of the overall frequency of SNPs within the equine genome ( ∼1/1500 bp ) , and providing sufficient markers to construct a whole genome SNP panel for use in the domestic horse and related species [3] . This report describes the overall properties and several uses of an equine whole genome SNP array termed the EquineSNP50 BeadChip . Similar to other important domestic animal species , such as the dog , pig , chicken , sheep and cow , this resource has positioned the domestic horse as a viable large animal model for genetic research . Equine researchers are now in an excellent position to evaluate the structure of the genome within and across horse breeds as well as closely related species . Data from this assay will yield important information about selection and population history , and facilitate association mapping studies to allow for the identification of loci associated with both valuable and deleterious traits . 60 , 000 SNPs from the EquCab2 genome assembly that gave suitable design scores for the Illumina Infinium II assay were selected in an attempt to provide even coverage of the genome . SNPs observed in discovery horses ( in reference to the Twilight genome assembly ) , or in both discovery horses and Twilight , were utilized ( Table S1 ) . Of the 354 horses from 14 different breeds selected for genotyping , 3 individuals failed to genotype ( Table S2 ) . Analysis of 8 pairs of replicate samples ( Twilight and the seven SNP discovery horses ) resulted in perfect replication of 868 , 820 genotypes ( replication frequency of 1 . 0 ) . Mendelian inheritance was confirmed in 15 of 18 trios ( Table S3 ) . 54 , 602 SNPs provided genotype data , and 53 , 524 SNPs were validated ( defined as having at least one heterozygous genotype call ) , indicating overall assay conversion and validation rates of 0 . 910 and 0 . 980 , respectively . The validation rates were highest for SNPs that were observed in a single discovery breed ( 0 . 990 ) when compared to Twilight , or observed in any two discovery breeds ( 0 . 989 ) ( Table S1 ) . 53 , 066 of the validated SNPs ( 99 . 1% ) were polymorphic ( defined as minor allele frequency ( MAF>0 . 01 ) in the entire sample set . The average spacing between functional SNPs on the 31 autosomes was 43 . 1 kb . There were 12 gaps greater than 500 kb across the 31 autosomes , with the largest gap being 1 , 647 . 5 kb on ECA6 ( Table S4 ) . Coverage on ECAX ( average inter-SNP spacing of 48 . 88 kb ) was lower than the rest of the genome ( Table S4 ) . The number of polymorphic SNPs ( MAF≥0 . 01 ) within a breed ranged from 43 , 287 to 52 , 085 ( 79% to 95% ) ; 26 , 473 ( 48 . 5% ) SNPs were polymorphic in every breed ( Table S5 ) . 90% of informative SNPs ( MAF>0 . 05 across breeds ) were less than 110 kb apart , and 95% of informative SNPs were less than 150 kb apart ( Figure S1 ) . The discovery breed source of the SNPs did not greatly affect their informativeness ( MAF>0 . 05 ) in the 14 analyzed breeds individually , or as a whole ( Table S6 ) . Genotyping was attempted in 53 individuals from 18 species evolutionarily related to the domestic horse ( Table S7 ) . The extant Perissodactyla ( odd-toed hoofed mammals ) include three families: the Equidae ( horses , asses and zebras ) , the Rhinocerotidae ( rhinos ) , and the Tapiridae ( tapirs ) , divided into two suborders , the Hippomorpha ( horses , asses and zebras ) and the Ceratomorpha ( rhinos and tapirs ) [4] . Of the 53 individuals genotyped , one single zebra ( Equus zebra hartmannae ) completely failed to genotype . Individual genotyping rates were slightly lower across the Hippomorpha ( mean 0 . 959 ) , and dramatically lower across the Ceratomorpha ( mean 0 . 246 ) when compared to the domestic horse ( mean 0 . 996 ) ( Table S7 ) . Quality scores ( GC10 , see Materials and Methods ) in the Hippomorpha ( mean = 0 . 705 ) were similar to those in the domestic horse ( mean = 0 . 730 ) , however mean GC10 scores were much lower in Ceratomorpha ( mean = 0 . 236 ) ( Table S7 ) . Due to lower quality scores and lower genotyping rates in some species , the genotypes in the Perissodactyla were further filtered based on raw intensity scores , individual genotyping rates , and SNP genotyping rates ( see Materials and Methods and Text S1 for details ) . The number of loci called after filtering for signal intensity and genotyping rates are presented in Table S8 . In the Hippomorpha our filtering criteria had little impact on genotyping rates , decreasing the call rate by only 1 to 3% . In contrast , filtering criteria decreased the call rates by 45 to 57% in the Ceratomorpha , suggesting that a large portion of the initial genotyping calls were unreliable . Further , mean GC10 scores for the remaining SNPs after filtering were 0 . 721 across all Hippomorpha and 0 . 389 across all Ceratomorpha respectively ( Table S8 ) , suggesting that data quality in the Ceratomorpha was questionable even after additional filtering . Thus only the Hippomorpha data were analyzed further . In the Hippomorpha , conversion rates ranged from 0 . 891 in the Przewalski's Horse ( Equus przewalskii ) to 0 . 834 in the Hartmann's Mountain Zebra ( Equus zebra hartmannae ) . The number of validated loci ranged from 265 ( 0 . 8% ) in the Somali Wild Ass ( Equus asinus somalicus ) to 26 , 859 ( 50 . 8% ) in the Przewalski's Horse ( Table S8 ) . The average observed heterozygosity in the Hippomorpha ( excluding the domestic horse ) ranged from 0 . 003 in the Domestic Ass , Somali Wild Ass , Grevy's zebra and Hartmann's Mountain zebra to 0 . 168 in the Przewalski's Horse ( Table S8 ) . Mean MAF in the nine Przewalski's Horses was 0 . 126 . The number of informative SNPs within breeds ranged from 37 , 053 ( 68% ) in the Norwegian Fjord to 47 , 669 ( 87% ) in the Quarter Horse ( Table S5 ) . Mean MAF within breeds also ranged from 0 . 180 to 0 . 232 in the Norwegian Fjords and Quarter Horses , respectively . 17 , 428 SNPs were informative ( MAF≥0 . 05 ) in every breed and 49 , 603 SNPs were informative within the entire sample set ( across all breeds ) . The overall MAF across all breeds was 0 . 236 ( SD = 0 . 139 ) , and the median MAF was 0 . 224 . The Mongolian breed displayed the highest genetic diversity , HE = 0 . 292 , whereas genetic diversity was the lowest in the Thoroughbred HE = 0 . 247 ( Table S5 ) . Genotypes for all SNP pairs less than 4 Mb apart were evaluated to estimate genome-wide linkage disequilibrium ( LD ) ( as r2 ) within and across breeds . As expected , LD was higher within a breed than across breeds . Initial LD declined rapidly across all horses with mean r2 dropping below 0 . 2 by 50 kb ( Figure 1 and Figure S2 ) . Within breed r2 values dropped most rapidly in the Mongolian , however , r2 was below 0 . 2 within 100 to 150 kb in the majority of breeds . LD was initially highest in the Thoroughbred , where r2 does not drop below 0 . 2 until 400 kb , and remained higher than other breeds until approximately 1 , 200 kb . The extent of long-range LD was the highest in the Standardbred and French Trotter ( Figure 1 ) . Mean individual inbreeding coefficients ( F ) were highest in the Thoroughbred and Standardbred ( 0 . 15 and 0 . 12 , respectively ) , and lowest in the Hanoverian , Quarter Horse and Mongolian ( 0 . 06 , 0 . 04 , and 0 . 02 , respectively ) ( Table S9 ) . The average genetic distance ( D ) between pairs of individuals from different breeds was 0 . 270 ( sd = 0 . 014 ) , while the mean distance between pairs of individuals from the same breed was 0 . 240 ( sd = 0 . 020 ) . As seen in Figure 2a , the distribution of D between individuals drawn from different breeds is relatively smooth; however , the distribution of D within breeds is distinctly tri-modal . To further investigate this tri-modal distribution , the mean D was calculated for each breed separately ( Table S10 ) . D was lowest in the Norwegian Fjord and Icelandic horses ( 0 . 21 ) which accounted for a large proportion of the left peak in Figure 2a , whereas D was highest in the Hanoverian , Quarter Horse and Swiss Warmblood ( 0 . 25–0 . 26 ) which accounted for a large proportion of the right peak . Metric multidimensional scaling ( MDS ) of pair-wise genetic distances was used to visualize the relationships among the 335 horses from 14 breeds . Plotting dimension 1 versus dimension 2 resulted in tight clustering by breed , with the exception of the Quarter Horse , Hanoverian and Swiss Warmblood ( Figure 3 ) . The 7 SNP discovery horses and Twilight were outliers relative to other members of their breeds ( Figure 3 ) . MDS plots and breed relationships in dimensions 3 through 6 are provided in Figure S3 . Parsimony analysis with a set of 40 , 697 autosomal SNPs across all Hippomorpha ( horses , asses and zebras ) placed the modern horse as sister taxa to Equus przewalski , and both the modern horse and E . przewalski as a sister clade to all the other equids , which fell out into species groups ( Figure 4 ) . Pair-wise genetic distances were also calculated with all domestic horse breeds , and the Przewalski's Horses ( n = 9 ) ( Figure 2 ) . MDS revealed tight clustering of the Przewalski's Horse ( n = 9 ) with the Mongolian and Norwegian Fjord horse samples when dimension 1 was plotted against dimensions 2 , 3 or 4 ( Figures S4 and S5 ) . The Przewalski's Horse samples were not completely separated from the Mongolian and Fjord samples until dimension 6 ( Figure S5 ) . The average genetic distance ( D ) between Przewalski's Horses and domestic horses was greater than the average D between pairs of individuals drawn from any 2 different domestic horse breeds ( Figure 2b ) , however there was significant overlap in the distribution of D values in the Przewalski's-domestic horse pairs and the domestic horse-different breed pairs . To investigate this overlap , the distances between Przewalski's Horses and each breed were calculated ( Table S11 ) . The results show that D between Przewalski's Horse and other breeds ranged from 0 . 25–0 . 31 , and was smaller between Przewalski's Horse and Mongolians , Norwegian Fjords , Belgians and Icelandics than between Przewalski's Horse and Thoroughbreds . The relationships between the domestic horse breeds and the Przewalski's Horse are also demonstrated by parsimony analysis in Figure 5 , where the Przewalski's Horse falls out into a strongly supported , monophyletic clade that is basal to the remainder of the modern breeds . Parsimony analysis also supports most associations among the domestic horse breeds suggested by MDS ( Figure 3 ) . To demonstrate the utility for GWAS , within and across breed mapping was performed for 3 coat color loci . Phenotypes were inferred either from the genotypes of all 9 known coat color loci with consideration of known interactions , or from genotype only at the locus of interest to model a simple Mendelian trait . The three most common alleles in our data set included the recessive chestnut coat color locus ( MC1R ) on ECA3 [5] , the recessive black coat color locus ( ASIP ) ( agouti ) [6] on ECA22 , and the dominant gray locus ( STX17 ) on ECA25 [7] . Both basic chi-square case-control allelic association and Cochran-Mantel-Haenszel ( CMH ) association analyses identified the chestnut and black loci across breeds regardless of how phenotype was inferred ( Figure 6a and 6b , Tables S12 and S13 , and Figures S6 and S7 ) . Gray was not mapped across all breeds using allelic association , CMH , ( Figure 6c , Tables S12 and S13 , Figure S8 ) , or structured association mapping using principal components or mixed-model analyses to control for underlying population structure ( data not shown ) . Within breeds the chestnut locus was successfully mapped in Quarter Horses ( 22 cases and 24 controls ) and Thoroughbreds ( 11 cases and 26 controls ) ( Table S14 ) . The ASIP locus was successfully mapped in the Andalusian ( 6 cases and 10 controls ) , when black was considered as a simple recessive trait ( ignoring epistatic interactions ) . The gray phenotype was not successfully mapped within the two breeds attempted . The assay conversion rate was lower on this equine array when compared to a similar assay designed for cattle or pigs ( 91 . 0% versus 92 . 6% and 97 . 5% respectively ) ; however , SNP validation rates were slightly higher in the horse than in bovine or porcine ( 98 . 0% versus 95 . 1% and 94% , respectively ) [8] , [9] . SNPs discovered in any two breeds were somewhat more likely to be validated than SNPs discovered in a single breed . Regardless of the discovery source , a large proportion of SNPs were validated and informative in breeds not represented in the SNP discovery effort . In the array design , SNPs from the “across breed” SNP discovery resource rather than SNPs discovered in the genome assembly process were used . This strategy was predicted to increase the utility of the SNP resource in non-Thoroughbred breeds . The high success rate of the validation justifies the approach of using representatives of global breed groups to generate a SNP resource [3] . The 54 , 000 polymorphic SNPs are distributed across the autosomes with few large gaps ( >500 kb ) . One large gap on ECA6 was the result of a misplaced contig in a pre-release of the sequence assembly from which the array was designed; even though it was correctly placed in the released assembly , no SNPs were selected from this region . Coverage was slightly lower on ECAX , likely reflecting fewer SNPs to choose from for assay design . The SNP discovery algorithm rejects sequences that align equally to multiple locations . The repetitive nature of the X chromosome in most mammals means that this limitation rejects a large number of potential SNPs that would not be positionally informative . The number and mean MAF of polymorphic SNPs varied between breeds . On average the number of SNPs informative in any given domestic horse breed was higher than informativeness of similar assays within given cattle and dog breeds [8] , [10] . Mean MAF across all samples ( 0 . 24 ) was slightly lower than the mean MAF reported for bovine ( 0 . 26 ) , ovine ( 0 . 28 ) or porcine assays ( 0 . 27 ) [8] , [9] ( Illumina Data Sheets at http://www . illumina . com/applications/agriculture/livestock . ilmn#livestock_overview ) . Breeds with recent or ongoing admixture , such as the Quarter Horse , Hanoverian and Swiss Warmblood , had the highest mean MAF and the largest numbers of informative SNPs , while the lowest mean MAF were in the Norwegian Fjord , Belgian and Icelandic horse . The relatively high number of informative SNPs in the Icelandic horse may reflect its use in SNP discovery . Despite low genetic diversity and high levels of inbreeding , the mean MAF in the Thoroughbred was higher than any other non-admixed breed , and the fraction of informative SNPs exceeded that of any other breed included in the SNP discovery effort with the exception of the Quarter Horse . The high level of SNP informativeness in the Thoroughbred breed likely reflects bias due to its use in both SNP discovery and as the reference genome sequence . We attempted to use the EquineSNP50 BeadChip to genotype a limited number of individuals from 18 other Perissodactyl species . Due to the SNP discovery design , it was unlikely that a large proportion of the markers in this assay would be polymorphic in other species; however , the identification of even several hundred useful markers in any of these species would provide a dramatic increase in the number of autosomal markers available for conservation genetics applications . A variable number of genotypes were produced across species , with higher genotyping rates and better quality scores in the more closely related Hippomorpha ( horses , asses and zebras ) than in the Ceratomorpha ( rhinos and tapirs ) . After data filtering , the assay conversion rate of the remaining SNPs was fairly high , and quality scores in Hippomorpha species were similar to those in the domestic horse , suggesting it may be a useful tool for certain applications in species other than Equus caballus . SNP validation rates in Equus species other than Equus przewalski were low , which may reflect species divergence as well as the very limited number of individuals genotyped in most species; genotyping a larger cohort within each species would be necessary to determine the true polymorphism rates . Further work is also necessary to determine the accuracy of genotyping calls in Equus sp . by reproducibility , concordance with other genotyping methods and confirmation of Mendelian inheritance with parent-offspring trio data [11] . Lastly , low quality scores , even after data filtering and inconsistent genotyping rates in the Ceratomorpha , suggest that the EquineSNP50 BeadChip will likely have much more limited utility in these species . Measurements of genetic diversity , inbreeding and LD all reflect population demographic history . Our measurements of genome-wide LD within and across breeds agreed well with previous work based on ten randomly selected 2 Mb genome segments [3] . Due to population subdivision , the extent of LD within a given breed was greater than LD across breeds . LD in the domestic horse is lower than in dogs , which does not decline nearly as rapidly over the first 100 kb and has a very slow decline over the next 1–2 Mb [12] . Not surprisingly , within breed patterns of LD in horses were similar to those observed in domestic cattle , which typically share a similar system of mating using popular sires and at times extensive line breeding [13] . LD declined most rapidly in the Quarter Horse and Mongolian horse , with r2 values dropping below 0 . 2 within the first 50–100 kb . The short extent of LD in the Mongolian and Quarter Horse reflects the low level of inbreeding and high genetic diversity in both breeds . The short extent of LD in the Mongolian horse is likely a result of its age and large population size . This breed has been bred in domestication since approximately 2000 BC , and the current population size is ∼3 million individuals [2] . High diversity in the Mongolian horse is in concordance with previous studies based on microsatellite loci that demonstrated that the Mongolian horse had the highest heterozygosity and genetic diversity in a study of 13 domestic horse populations [14] . Unlike the Mongolian horse , other breeds with long histories had a moderate decline in LD . These include the Icelandic horse , which originated from stock imported to Iceland in ∼900 AD , the Norwegian Fjord horse thought to have been selectively bred for at least 2 , 000 years , and the Belgian draft horse believed to be descended from the war horse of the Middle ages [2] . Somewhat longer LD in these old breeds likely reflects the fact that their population histories have included severe population bottlenecks . An Icelandic horse bottleneck has been associated with the 1783 eruption of the volcano Lakagigar , in which an estimated 70% of the population was destroyed from volcanic ash poisoning [2] , and a population bottleneck in the Belgian and other draft horse breeds arose due to their disappearance as a utilitarian animal after World War II . It has been postulated that all present day Norwegian Fjords are descendants of a single stallion foaled in 1891 , however previous studies using microsatellite markers have not yet corroborated this assumed bottleneck [15] . Short LD in the Quarter Horse , a recently established breed with a registry less than 100 years old , is likely a result of a very large population size ( ∼4 million individuals ) , rapid population expansion and population admixture since the breed's formation [16] , [17] . In contrast , LD was clearly the highest in the Thoroughbred , reflecting the breed's low diversity , high inbreeding , and closure of the studbook to outside genetic influence for more than 300 years . Previous work has demonstrated that approximately 78% of Thoroughbred alleles are derived from 30 founders , and that a single founder stallion is responsible for approximately 95% of paternal lineages [18] . The long extent of LD in this breed also reflects the high level of inbreeding which has been shown to have an even greater impact on the extent of LD than diversity [17] . The impact of low diversity and high inbreeding on LD can also be seen in the Standardbred and the French Trotter , both breeds which , while having a more rapid decline in LD than the Thoroughbred , have long-range LD that persists further than the Thoroughbred . The mean pair-wise genetic distance between individuals within a breed was 0 . 24 , which is higher than reported in cattle , but lower than reported in sheep ( 0 . 21 and 0 . 25 respectively ) [19] . However , D was not normally distributed in horses , displaying three distinct peaks . When the distance matrix was partitioned by breed , the pair-wise distances were largest within the Quarter Horse , Swiss Warmblood and Hanoverian , all breeds with admixture and low to moderate levels of inbreeding , while the pair-wise distances were the smallest within the Norwegian Fjord and Icelandic horse , which may reflect their previous population bottlenecks . There is also substantial overlap between the within and across breed distributions , which was likely the result of high genetic diversity in admixed breeds , as well as close relationships between breeds such as the Standardbred and French Trotters . MDS plots demonstrated that individuals within most breeds were tightly clustered in relation to other breed groups . This was true even for the Thoroughbred population where two geographically distinct sample origins were represented ( United Kingdom , Ireland , and United States ) . The exceptions to this were the three breeds with recent and/or ongoing admixture; the Quarter Horse , Hanoverian and Swiss Warmblood . In addition , the Hanoverian and Quarter Horse , and to a lesser extent the Swiss Warmblood , had larger variation along dimension 1 than other breeds , suggesting that the admixture may be resulting in significant population substructure . The Andalusian breed was not tightly clustered in dimension 6 , suggesting population substructure as well . This is consistent with the practice of some American breeders crossing Andalusians ( from Spain ) with closely related Lusitano horses ( from Portugal ) in their breeding programs . Close relationships between some breeds were also visualized , including the clustering of the Standardbred and the French Trotter apart from the other breeds in dimension 3 . This may be the result of the influence of the Standardbred on the French Trotter , or similar selective pressures for the trotting phenotype in both breeds . The Norwegian Fjord , Icelandic , Mongolian , and Belgian clustered together in the first 3 dimensions , and Icelandic and Norwegian Fjord horses clustered tightly together in all 6 dimensions . This may reflect the suggested influence of Mongolian genes in the development of the Norwegian Fjord and subsequent development of the Icelandic horse from Scandinavian stock imported to Iceland [15] , [20] . However the close clustering of the Belgian horse with these older breeds does not fit this history and its clustering may also reflect the low MAF and lower number of informative SNPs in the Belgian , Icelandic and Norwegian Fjord . Ten horses are outliers relative to their breed: a Norwegian Fjord , a Mongolian , the seven SNP discovery horses , and Twilight . Increased heterozygosity due to SNP discovery bias likely accounts for the outlier status of Twilight and the seven SNP discovery horses . We expect to observe greater diversity in all SNP discovery breeds because observations of diversity in other breeds rely on across-breed allele sharing rather than direct allelic observation . Parsimony analysis supports many relationships suggested by MDS . For instance , breeds in which individuals cluster tightly in MDS , such as the Thoroughbred and Arabian , are represented in the cladogram as monophyletic clades with high bootstrap support; whereas breeds that have continuing admixture , such as the Quarter Horse , Swiss Warmblood , and Hanoverian , do not show monophyly and share a branch of the clade with the Thoroughbred . In some instances , relationships that were not clear from the MDS plot are demonstrated in the tree , such as the close placement of the Saddlebred and Arabian . In parsimony analysis of only Equus spp . using over 40 , 000 SNPs , high bootstrap support distinguishes Equus caballus from Equus przewalskii while also making a clear distinction between those species and the zebras and asses . With further work , the use of random nuclear SNPs in equid phylogeny studies should prove superior to the existing studies that use either mitochondrial SNPs , or SNPs from just a few nuclear genes [21]–[23] . The horse is thought to have been domesticated from the now extinct Tarpan ( also known as the European wild horse Equus ferus ) [1] . The close clustering of the domestic horse and the Przewalski's Horse is consistent with the hypothesis that the Przewalski's Horse ( also known as the Asiatic wild horse Equus przewalskii ) is a sister species to the Tarpan . This close relationship between the domestic horse and the Przewalski's Horse is also likely a result of relatively recent gene flow between these lineages since divergence from a common ancestor . While Equus przewalskii and Equus caballus have a different number of chromosomes ( 2n = 66 and 2n = 64 , respectively ) , they can interbreed and produce viable offspring . Since their discovery by the western world in the late 1880s , the question of admixture of the Przewalski's Horse and domestic horse has remained a topic of debate and controversy . Known introgressions took place in the early years of the propagation program that prevented the extinction of the species [24] and , more recently with the offspring of the last wild-caught mare at the Askania Nova breeding center [25] . In addition , there was likely interbreeding of Equus przewalskii and Equus caballus in the wild , as the range of the Przewalski's Horse and the domestic horse overlapped in China , Russia and Mongolia [26] . Gene flow from the domestic to Przewalski's Horse in our study is supported by the tight clustering of the Przewalski's Horse and several of the horse breeds in MDS , most notably the Mongolian horse and related breeds . This relationship is reiterated by parsimony analysis where the Mongolian , Icelandic , and Norwegian Fjord are in close association with the Przewalski's Horse . The pair-wise genetic distances between Przewalski's Horses and some domestic horse breeds falls within the range of within breed pair-wise differences in domestic horse breeds , which corroborates earlier findings [3] . Thus , while Equus ferus and Equus przewalskii are considered different species based on chromosomal number differences , surviving Przewalski's Horses today are truly Equus przewalskii and Equus caballus hybrids [1] . A major application of this genotyping technology will be in genome-wide association mapping of traits in the domestic horse [27]–[31] . The success of such studies will depend upon LD within the mapping population , properties of the loci themselves , population structure , and the mode of inheritance . Our attempt to map three known Mendelian coat color traits in a sample set not specifically designed for that purpose , met with varying success ( Tables S12 , S13 , S14; Figures S6 , S7 , S8 ) . The MC1R locus was successfully mapped both across breeds and within several breeds . This is a result of good informative SNP density in this region , larger sample sizes for several breeds in which the chestnut allele is segregating , and extended homozygosity surrounding the locus . The centromeric location of the MC1R locus that limits recombination , as well as selection for the chestnut trait in many breeds , resulted in a conserved haplotype within breeds ranging from 1 . 2–4 . 2 Mb and a 750 kb minimally conserved haplotype across breeds ( Figure S9 , Table S15 ) . The length of this conserved haplotype is nevertheless surprising given the presence of the MC1R chestnut allele since at least the fifth millennium before present [32] On the other hand , the mapping of ASIP , while successful across breeds , suffered from lower numbers of relevant samples within many individual breeds and low SNP density at the ASIP locus itself . Mapping the STX17 gray locus was unsuccessful due to confounding by population substructure , sparse marker density in the region , and poor power to detect a dominant locus due to low sample sizes both within and across breeds . Nevertheless , our results demonstrate the utility of whole genome mapping within breeds when studies are sufficiently powered , although power clearly varies among breeds , and the rate of false positives increases with small sample sizes . Further , due to across-breed haplotype sharing in the horse [3] , across-breed mapping of certain traits that are clearly conserved across breeds is possible if proper consideration is given to confounding population substructure . Ideally , increased genome coverage with additional , highly informative SNPs would be more effective for mapping studies , particularly in admixed and/or breeds with low LD . We have constructed and validated a 54 , 000 SNP genotyping assay that will enable mapping of loci associated with equine health and performance , as well as the study of breed diversity and relationships . The array will also likely have many uses in the study of the population genetics of other equid species . SNPs assayed on the EquineSNP50 BeadChip were selected from the “across breed” SNP set generated in the equine genome project . The SNPs used for the genotyping array had unknown validation status and minor allele frequency at the time of design . The discovery method used in the equine genome analysis ( SSAHA-SNP ) predicted a 98% validation rate . SNP quality scoring was conducted by Illumina Inc . and included estimates of sequencing quality on the Illumina platform based on flanking characteristics such as G-C content , proximity of known SNPs and unique flanking sequence . After scoring , SNPs requiring a single-bead type ( Infinium II ) were preferred and of these , the highest scoring 60 , 000 were passed to the array design regardless of genomic location . Twilight and the 7 SNP discovery horses from the NHGRI equine genome sequencing project ( an Andalusian , Arabian , Akhal-Teke , Icelandic , Standardbred , Thoroughbred and a Quarter Horse ) were selected as controls [3] , and each of these horses was genotyped in duplicate . The remaining 346 genotyped horses were from 14 different breeds ( Table S2 ) . Breeds were selected where possible to represent a geographic distribution from Europe , Asia and North America . 18 mare-stallion-foal trios were genotyped from 12 different breeds ( Table S3 ) . Three of the 6 Thoroughbred trios had the same sire , while two Thoroughbred trios , and two Belgian trios shared the same sire and dam ( i . e . full-sibling pairs ) . The remaining individuals from any given breed were selected to be no more related than second cousins ( i . e . , not sharing grandparents ) based on pedigree analysis . The utility of the EquineSNP50 BeadChip for use in other Perissodactyla was determined by assaying the 54 , 602 SNPs that produced genotypes in Equus caballus in 53 individuals from 18 species evolutionarily related to the domestic horse , including domestic and wild asses , zebras , tapirs and rhinoceroses ( Table S7 ) . Individual genotyping rate was defined as the proportion of loci that produced a genotype in that individual . SNP conversion rate was calculated as the number of SNPs that produced a genotype/number of SNPs included in the assay . Validation rate was calculated as the number of polymorphic SNPs ( at least 1 heterozygous individual ) /number of converted SNPs . Mendelian errors in each of the 18 nuclear trios were calculated using PLINK [33] and results are reported as Mendelian agreement ( 1-[number of Mendelian errors in the trios/total number of loci genotyped] ) . Informative SNPs were defined as those SNPs with a minor allele frequency greater than 0 . 05 . Minor allele frequencies and missingness rates were calculated using PLINK ( –freq , –missing ) [33] . The proportion of validated SNPs from each discovery breed was computed by identifying all SNPs within the assay that were discovered in a single breed ( relative to Twilight's sequence ) and determining the proportion of those SNPs that were polymorphic within each of the 14 breeds included in the sample set ( with the exclusion of the discovery horses ) . Genotyping quality for each call was determined using the GenCall method in Illumina's Genome Studio software [11] . GenCall ( GC ) scores are reported as the 10th percentile of the GC scores ( GC10 scores ) . Additional filtering criteria were applied to the genotyping data in extant Perissodactyla , First , calls with low signal intensity were identified by combining the X raw and Y raw intensity values for both allele A and allele B , and removing genotypes failing to reach the threshold value ( set at 1000 ) . These loci were then removed and re-coded as no calls ( 00 ) in the ped file for further analyses . After intensity filtering , individual genotyping rates were determined . Mean and standard deviations for individual genotyping rates were determined for both the Hippomorpha and the Ceratomorpha . Individuals with genotyping rates below 2 standard deviations from the mean were excluded from further analyses . Markers that genotyped in >90% of the remaining individuals were considered true markers and are reported as loci producing a genotype in the species ( Table S8 ) . Genome-wide LD was estimated by calculating r2 values between all pairs of SNPs with inter-SNP distances of less than 4 Mb both within a given breed ( a minimum of 18 horses per breed ) and across all breeds . Pair-wise LD was calculated for each chromosome within breed using the LD plot function in Haploview [34] exporting the data to text files . These files were computationally processed to produce mean r2 values in 50 Kb distance bins across all chromosomes for individual breeds and for all horses . Inter-SNP distances of greater than 4 Mb were ignored . Extent of LD was regarded as the persistence of LD until falling below two-fold background LD . Background LD within breed is largely affected by sample size and effective population size . Genetic distance ( D ) between pair-wise combinations of individuals was calculated using PLINK where D = 1−[ ( IBS2+0 . 5*IBS1 ) /N]: IBS2 and IBS1 are the number of loci that share either 2 or 1 alleles identical by state ( IBS ) , respectively , and N is the number of loci tested . Metric multidimensional scaling ( MDS ) analysis of pair-wise genetic distance ( 6 dimensions ) was used to identify the relationships between breeds with PLINK ( –mds-plot 6 ) . Individual inbreeding coefficients ( F ) were estimated with PLINK . SNPs were pruned for linkage equilibrium using pair-wise genotypic correlation in 100 SNP windows sliding by 25 SNPs along the genome; SNPs were pruned at r2>0 . 2 ( –indep-pairwise 100 25 0 . 2 ) . The resulting set of 17 , 947 SNP loci was used to calculate F for all individuals within each breed . Genetic distance ( D ) between pair-wise combinations of individuals was calculated and MDS analysis of pair-wise genetic distance ( 6 dimensions ) was used to identify the relationships using PLINK ( as above ) . D and MDS calculations for the domestic horse and Przewalski's Horse group included all domestic horses as well as the control horses . Autosomal genotypes from 344 individuals of the 14 modern breeds , the 9 Przewalski's Horses , and a domestic ass , were pruned in PLINK for a minimum per-SNP genotyping rate of 0 . 9 ( –geno 0 . 1 ) and minor allele frequency of 0 . 05 ( –maf 0 . 05 ) . Alleles of the 46 , 244 remaining SNPs were coded AA = 0 , AB = 1 , and BB = 2 for parsimony analyses in TNT ( Goloboff et al . 2003 ) with a domestic ass designated as the outgroup . Traditional searches were applied using subtree pruning-regrafting ( SPR ) branch swapping for 100 replicates followed by 100 replicates of the tree bisection-reconnection ( TBR ) method . New technology searches were them performed ( random and consensus sectoral searches , 5 rounds of tree fusing , and 30 iterations of tree-drifting ) , at default settings . Bootstrap support was calculated using 500 pseudoreplicates with traditional search methods ( SPR-TBR ) . The resulting tree was visualized in FigTree ( http://tree . bio . ed . ac . uk/software/figtree/ ) . Phylogeny across the Hippomorpha was performed in TNT similarly to the phylogenetic analysis above [35] . The X chromosome was removed and autosomal SNPs were pruned for a per-locus genotyping rate of ≥90% ( –geno 0 . 1 ) and maf >0 . 0001 across species , and an unrooted cladogram was created from parsimony analysis of the remaining in 40 , 697 autosomal markers . Bootstrap support was calculated from 1000 replicates . All horses were genotyped for all known coat color loci including MC1R ( chestnut ) , ASIP ( agouti , black/bay ) , STX17 ( gray ) , SLC36A1 ( champagne ) , MATP ( cream ) , PMEL17 ( silver ) , KIT [exon skipping] ( sabino ) , EDNRB ( overo ) and KIT [inversion] ( tobanio ) [5]–[7] , [36]–[42] . Genotypes were determined using methods routinely employed at the Veterinary Genetics Laboratory , University of California Davis . The base coat color phenotype of each horse was determined either by inference from the genotypes of all 9 coat color loci with consideration of known interactions , or by inference from genotype only at the locus of interest ( MC1R , ASIP , or STX17 ) to model a simple Mendelian trait . To infer coat color phenotype based on the 9 known loci: Coat color association analyses were performed in PLINK [33] , and quality control summary statistics including genotyping rate , MAF , Hardy-Weinberg equilibrium tests and case/control differences in genotype missingness were performed for all analyses . SNPs with MAF<1 . 0% , genotyping rate <90% , and individuals genotyped at a rate of <90% were excluded from further analysis . Additionally , SNPs were excluded if they demonstrated deviation from HWE ( p<0 . 001 ) , or differential missingness between cases and controls ( p<0 . 01 ) . Multiple testing correction , when performed , was accomplished with 10 , 000 label swapping t-max permutations ( –mperm 10 , 000 ) . T-max permuted p-values were considered genome-wide significant at p<0 . 05 . Inflation of p-values due to population structure was assessed by calculating the genomic inflation factor ( λ ) and by assessing quantile-quantile plots . Unstructured genome-wide association analysis was performed using chi-square tests for allelic association ( –assoc ) . Stratified genome-wide association analysis was performed using the Cochran-Mantel-Haenszel ( CMH ) test ( –mh ) . Horses were clustered for the CMH test on the basis of the pair-wise population concordance ( PPC ) test in PLINK , which clusters individuals based on the likelihood of concordant or discordant ancestry . A p-value for merging in the PPC test was set at p = 0 . 01 ( –cluster , –ppc 0 . 01 ) . Manhattan plots of all results were generated using Haploview [34] . Haplotypes containing markers at the MC1R , ASIP and STX17 loci on ECA3 , 22 and 25 , respectively , were determined with fastPHASE [43] . For MC1R , the number of chromosomes in each breed that contained the chestnut allele , the number of SNPs on which the haplotype is based , and the length and coordinates of the shared haplotype are available in Table S15 . Similar analyses resulted in no shared haplotypes at either the ASIP or STX17 loci .
We utilized the previously generated horse genome sequence and a large SNP database to design an ∼54 , 000 SNP assay for use in the domestic horse and related species . The utility of this SNP array was demonstrated through genome-wide linkage disequilibrium , inbreeding and genetic distance measurements within breeds , as well as multidimensional scaling and parsimony analysis . Association mapping confirmed a large conserved segment containing the chestnut coat color locus in domestic horses . We also assess the utility of the SNP array in related species , including the Przewalski's Horse , zebras , asses , tapirs , and rhinoceros . This SNP genotyping tool will facilitate many genetics applications in equids , including identification of genes for health and performance traits , and compelling studies of the origins of the domestic horse , diversity within breeds , and evolutionary relationships among related species .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "animal", "types", "genetics", "biology", "genomics", "population", "biology", "genetics", "and", "genomics", "veterinary", "science", "agriculture" ]
2012
A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies
Several successful pathogens have evolved mechanisms to evade host defense , resulting in the establishment of persistent and chronic infections . One such pathogen , Porphyromonas gingivalis , induces chronic low-grade inflammation associated with local inflammatory bone loss and systemic inflammation manifested as atherosclerosis . P . gingivalis expresses an atypical lipopolysaccharide ( LPS ) structure containing heterogeneous lipid A species , that exhibit Toll-like receptor-4 ( TLR4 ) agonist or antagonist activity , or are non-activating at TLR4 . In this study , we utilized a series of P . gingivalis lipid A mutants to demonstrate that antagonistic lipid A structures enable the pathogen to evade TLR4-mediated bactericidal activity in macrophages resulting in systemic inflammation . Production of antagonistic lipid A was associated with the induction of low levels of TLR4-dependent proinflammatory mediators , failed activation of the inflammasome and increased bacterial survival in macrophages . Oral infection of ApoE−/− mice with the P . gingivalis strain expressing antagonistic lipid A resulted in vascular inflammation , macrophage accumulation and atherosclerosis progression . In contrast , a P . gingivalis strain producing exclusively agonistic lipid A augmented levels of proinflammatory mediators and activated the inflammasome in a caspase-11-dependent manner , resulting in host cell lysis and decreased bacterial survival . ApoE−/− mice infected with this strain exhibited diminished vascular inflammation , macrophage accumulation , and atherosclerosis progression . Notably , the ability of P . gingivalis to induce local inflammatory bone loss was independent of lipid A expression , indicative of distinct mechanisms for induction of local versus systemic inflammation by this pathogen . Collectively , our results point to a pivotal role for activation of the non-canonical inflammasome in P . gingivalis infection and demonstrate that P . gingivalis evades immune detection at TLR4 facilitating chronic inflammation in the vasculature . These studies support the emerging concept that pathogen-mediated chronic inflammatory disorders result from specific pathogen-mediated evasion strategies resulting in low-grade chronic inflammation . Host recognition of Gram-negative bacteria occurs via detection of LPS expressed on the bacterial membrane by the innate immune receptor , TLR4 [1] . This initial recognition is critical for instructing host immunity and promoting an inflammatory response that eradicates the pathogen from the host [1] , [2] . However , a number of Gram-negative organisms have evolved mechanisms to modify their lipid A species , the component of bacterial LPS that directly activates the TLR4 complex , as a strategy to evade immune detection and establish infection [3] . Lipid A is initially synthesized as a β-1′ , 6-linked disaccharide of glucosamine that is phosphorylated and fatty acylated [4] . An unmodified version of this lipid A structure is typically expressed by E . coli and induces a robust inflammatory response [5] . Modifications to this basic lipid A structure are observed in alterations to acyl chains or terminal phosphate groups [6] . Helicobacter pylori [7] , Legionella pneumophila [8] , Yersinia pestis [9] , and Francisella novicida [10] express underacylated lipid A moieties , in comparison to the canonical LPS expressed by E . coli , and are poorly recognized by TLR4 . Yersinia pestis [11] and Francisella tularensis [12] expression of structurally divergent forms of lipid A is highly regulated by local environmental conditions such as temperature , allowing these pathogens to adapt to harsh environmental conditions in the host . It has been postulated that the ability of these pathogens to cause persistent infection and severe disease is partially due to evasion of host immune detection at TLR4 [13] . Recently , it has been revealed that in addition to evasion of TLR4 signaling , lipid A modifications promote evasion of the non-canonical inflammasome by preventing activation of caspase-11 [14] . Activation of the inflammasome is characterized by the production of the proinflammatory mediators IL-1β and IL-18 and is associated with downstream events such as pyroptosis [15] . Due to its role in host innate defense , a number of pathogens have evolved strategies to evade activation of this complex [16] . Pathogen evasion of inflammasome activation has been proposed to serve a dual role: to dampen cytokine production and to prevent host cell death in order to provide an intracellular niche for the pathogen to survive [17] . One pathogen that has successfully adapted to evade the inflammasome is H . pylori , through expression of its tetra-acylated lipid A [14] . The oral pathogen Porphyromonas gingivalis weakly activates TLR4 through expression of a heterogeneous LPS that contains lipid A structures that vary in the number of phosphate groups and the amount and position of lipid A fatty acids [18] , [19] . P . gingivalis expresses underacylated lipid A structures that can be penta-acylated forms , conferring TLR4 agonistic activity , or tetra-acylated forms , functioning as TLR4 antagonists , or are non-activating [20] , [21] . These structures typically express mono- or di-phosphate terminal groups . Expression of divergent structural moieties by P . gingivalis changes depending on growth phase , temperature , and levels of hemin [22]–[24] . Recently , it has been demonstrated that P . gingivalis also expresses a unique non-phosphorylated , tetra-acylated lipid A that is regulated by levels of hemin [23] . During hemin-deplete conditions , P . gingivalis utilizes endogenous lipid A 1- and 4′-phosphatase activities to express a non-phosphorylated , tetra-acylated lipid A that is immunologically inert at the TLR4 complex , as well as a mono-phosphorylated , penta-acylated lipid A that functions as a weak TLR4 agonist [22] , [23] , [25] . Under hemin-replete conditions , the activity of 1-phosphatase is suppressed , resulting in the expression of a mono-phosphorylated , tetra-acylated lipid A species that functions as TLR4 antagonists [23] . Expression of these different structural types is believed to allow P . gingivalis to evade immune detection at TLR4 [26] . A hallmark of chronic infection with P . gingivalis is the induction of a local inflammatory response that results in destruction of supporting tissues of the teeth and resorption of alveolar bone [27]–[29] . In addition to inflammation induced at the initial site of infection , P . gingivalis has been associated with systemic diseases such as diabetes , pre-term birth , pancreatic cancer , and cardiovascular disease [30]–[32] . P . gingivalis has been detected in human atherosclerotic lesions and shown to be viable in atherosclerotic tissue [33]–[35] . Studies from our laboratory have validated human studies by demonstrating that oral infection of atherosclerosis-prone ApoE−/− mice with P . gingivalis results in local oral bone loss and systemic inflammation in atherosclerotic lesions [36] . We have demonstrated that P . gingivalis-induced oral inflammatory bone loss and acceleration of systemic inflammation and atherosclerosis is dependent on TLR2 signaling [37] , [38] . P . gingivalis engages TLR2 through the expression of several outer membrane components that include lipoprotein , major and minor fimbriae , and phosphorylated dihydroceramides [39]–[41] . The unique ability of P . gingivalis to induce TLR2 signaling and to evade TLR4 signaling has been proposed to enable this organism to cause low-grade persistent infection [42]; however , the expression of multiple P . gingivalis lipid A structures simultaneously has complicated the interpretation of how distinct lipid A moieties contribute to chronic inflammation [22] . To define the role of distinct lipid A species in P . gingivalis evasion of TLR4 signaling , innate immune recognition , survival , and the ability of the pathogen to induce local and systemic chronic inflammation , we constructed genetically modified strains of P . gingivalis that lack either 1- or 4′-phosphatase activity [23] . These resulting strains express lipid A species that are not under genetic regulation and function as TLR4 agonists or TLR4 antagonists . Utilizing these strains , we demonstrate that P . gingivalis expression of antagonist lipid A species results in attenuated production of proinflammatory mediators and evasion of non-canonical inflammasome activation , facilitating bacterial survival in the macrophage . Infection of atherosclerosis-prone ApoE−/− mice with this strain resulted in progression of chronic inflammation in the vasculature . Notably , the ability of P . gingivalis to induce local inflammatory bone loss was independent of lipid A modifications , supporting distinct mechanisms for induction of local versus systemic inflammation . Collectively , these results indicate that expression of P . gingivalis lipid A structures that fail to engage TLR4 or function as TLR4 antagonists enables this pathogen to evade host innate immune detection and induce inflammation at sites distant from infection . MALDI analysis of LPS isolated from P . gingivalis strain 381 revealed an ion cluster at m/z 1368 ( Figure 1A and 1D ) . This structure represents the non-phosphorylated and tetra-acylated lipid A species that was predicted to be functionally inert at the TLR4 complex [23] . Additionally , we observed the expression of TLR4 antagonist ( m/z 1448 ) and TLR4 agonist ( m/z 1688 and m/z 1768 ) structures ( Figure 1A and 1E–G ) . In order to examine the role of distinct lipid A species on the induction of inflammation , we constructed P . gingivalis strains lacking lipid A 1- and 4′- phosphatase activities in P . gingivalis 381 . MALDI analysis of P . gingivalis strain PG1587381 , that lacks 4′-phosphatase activity , revealed TLR4 agonist lipid A structures that centered at m/z 1768 and m/z 1688 ( Figure 1B and 1F–G ) . MALDI analysis of P . gingivalis strain PG1773381 , which lacks 1-phosphatase activity , revealed a TLR4 antagonist lipid A mass ion that was predominantly centered at ∼1448 m/z as well as the agonistic lipid A centered at ∼1768 m/z ( Figure 1C , 1E and 1G ) . To confirm the predicted TLR4 activation phenotype of the lipid A expressed by wild-type 381 and the lipid A mutants , we stimulated HEK cells that overexpress mouse TLR4-MD2 with purified LPS from each strain . Notably , the LPS preparations purified from all three strains similarly activated mouse TLR4-MD2 ( Figure 2A ) . In contrast , when live bacteria were used to stimulate the HEK cells only strain PG1587381 resulted in a significant increase in TLR4-dependent NF-κB activation as compared to wild-type 381 and PG1773381 ( Figure 2B ) . These results suggest that the lipid A structures are differentially distributed within the bacterial cell membranes depending upon the strains , and that the relative localization of the specific agonistic and antagonistic lipid A forms to the outer cell membrane determines the respective abilities of the different strains to activate TLR4 . The less potent lipid A forms ( m/z 1368 , 1448 , 1688 ) may be primarily expressed on the bacterial outer membrane whereas the most potent lipid A form ( m/z 1768 ) predominates in the inner membrane where it is initially synthesized prior to processing by phosphatases and deacylase ( s ) . In addition to direct impact on TLR4 activation , modifications in lipid A structure can significantly alter the ability of cationic peptides to kill bacteria . We have previously reported that two different strains of P . gingivalis ( 33277 and A7436 ) deficient in PG1587 exhibit the most pronounced sensitivity to polymyxin B as compared to the wild-type and PG1773 strains , consistent with a critical role of the lipid A 4′-phosphate in rendering bacteria susceptible to this drug [23] , [43] . Assessment of these mutations in the 381 strains revealed a comparable pattern . Strain PG1587381 exhibits a pronounced susceptibility to polymyxin B while the P . gingivalis wild-type strain 381 and strain PG1773381 were relatively more resistant ( Figure 2C ) . These data correlate well with the above TLR4 activation data indicating that lipid A structures localized in the outer membrane of the PG1587381 mutant contain 4′-phosphate ( m/z 1688 ) . In contrast , the PG1773381 strain is the most resistant , indicating the predominance of lipid A lacking 4′-phosphate in the outer membrane ( m/z 1448 ) . Wild-type 381 has an intermediate polymyxin B resistance phenotype consistent with an increased presence of lipid A containing 4′-phosphate as compared to strain PG1773381 . To verify that the mutant 381 strains exhibit phenotypes that are consistent with bacterial surface lipid A modifications rather than modifications of other surface virulence factors , we further assessed the ability of the P . gingivalis wild-type strain and the lipid A mutants to activate TLR2 . All three P . gingivalis strains induced a similarly significant increase in NF-κB activation in HEK293 cells over expressing TLR2; however , we observed a slight decrease in the ability of the P . gingivalis wild-type strain 381 to activate TLR2 at lower MOIs ( Figure 2E and data not shown ) . Stimulation of HEK-TLR2 cells with purified LPS isolated from the P . gingivalis wild-type strain 381 and the lipid A mutants resulted in equivalent activation of TLR2 ( Figure 2D ) . These results were expected since P . gingivalis strongly activates TLR2 via expression of fimbriae and lipoproteins [39] , [40] . To confirm that modification of lipid A structures in P . gingivalis strains PG1587381 and PG1773381 did not alter the expression of other outer membrane components , we examined the major fimbriae protein and activity of the cell-associated cysteine proteases , gingipain R and gingipain K . Similar levels of fimbriae expression were observed in P . gingivalis strains 381 , PG1587381 and PG1773381 ( Figure S1-A-B ) . We observed a slight decrease in gingipain activity ( KGP and RGP ) in P . gingivalis strain PG1587381 as compared to that observed in the wild-type strain ( Figure S1-C ) . We did not observe significant differences in the growth of P . gingivalis strains PG1587381 and PG1773381 as compared to the wild-type strain ( Figure S1-D and data not shown ) . Taken together , these results indicate that deletion of PG1587 or PG1773 alters the ability of the whole bacteria to activate TLR4 but does not alter the expression of other outer membrane components or the ability of the pathogen to activate TLR2 . Therefore , the use of strains PG1587381 and PG1773381 in this study allowed us to assess the immunological consequences of differential lipid A expression by P . gingivalis . We examined the ability of the P . gingivalis strains lacking lipid A 1- and 4′-phosphatase activities to induce NF-κB-dependent proinflammatory cytokines in bone marrow-derived macrophages ( BMDM ) . Stimulation of BMDM with P . gingivalis strain PG1587381 resulted in increased production of KC , IL-6 , IL-1β , and IL-1α compared to P . gingivalis strains 381 and PG1773381 in a dose-dependent manner ( Figure 3B–C; Figure 4A–B ) . In contrast , all three P . gingivalis strains induced significant levels of TNF-α . ( Figure 3A ) . The role of TLR2 and TLR4 in the production of these inflammatory cytokines was assessed in BMDM obtained from TLR2- and TLR4-deficient mice . P . gingivalis-induced TNF-α production required both TLR2 and TLR4 signaling; however , TLR2 signaling was more dominant ( Figure 3D ) . Additionally , we observed that the ability of P . gingivalis to induce IL-1β and IL-1α was dependent on both TLR2 and TLR4 signaling ( Figure S2 ) . In contrast , P . gingivalis-induced expression of KC and IL-6 were primarily dependent on TLR4 signaling ( Figure 3E–F ) . We observed that PG1587381 induced enhanced KC and IL-6 levels in TLR2-deficient macrophages as compared to the P . gingivalis wild-type strain 381 , suggesting the increased cytokine production we observed in wild-type BMDM was mediated via TLR4 signaling . Furthermore , we observed comparable KC and IL-6 levels in BMDM deficient in TLR4 following stimulation with all 3 strains of P . gingivalis , suggesting additional signaling through TLR2 in the absence of TLR4 or an inability of lipid A to antagonize production of these cytokines . Overall , these results indicate that expression of antagonistic or inert lipid A attenuates the production of NFκB-dependent proinflammatory mediators in macrophages . IL-1β is considered an “alarm” cytokine and has been shown to be critical for host defense against infection [16] , [44] . Previous studies have documented that P . gingivalis fails to induce significant levels of IL-1β production in macrophages [45] , [46] . Thus , the increased production of IL-1β observed in macrophages stimulated with P . gingivalis strain PG1587381 was an unexpected finding ( Figure 4A ) . IL-1β is first produced as an inactive zymogen , through activation of TLR signaling [47] . We observed that all three P . gingivalis strains induced expression of the proform of IL-1β ( Figure 4G ) , which was dependent on TLR2 and TLR4 ( data not shown ) . These results indicated that the attenuated production of IL-1β observed with P . gingivalis strains 381 and PG1773381 was not due to an obstruction of TLR-mediated synthesis of pro-IL-1β . These findings led us to investigate the role of P . gingivalis lipid A modifications on inflammasome activation , the second signal required for production of mature and active IL-1β . Stimulation of macrophages with P . gingivalis strain PG1587381 resulted in activation of the inflammasome , as assessed by detection of the active caspase-1 p10 subunit in cell supernatants by Western blot analysis ( Figure 4G ) . We also observed an increase in macrophage cell lysis following stimulation with P . gingivalis strain PG1587381 ( Figure 4C ) , an event that is downstream from inflammasome activation . These results correlated with an inability of PG1587381 to survive in macrophages . We observed a significant decrease in survival of P . gingivalis strain PG1587381 in macrophages compared to P . gingivalis strains 381 and strain PG1773381 ( Figure 4F ) . Caspase-11 has emerged as an important mediator of inflammasome activation in Gram-negative bacterial infections [48] , [49] . We thus examined the role of caspase-11 in P . gingivalis-induced IL-1β production . Interestingly , IL-1β production was completely ablated in macrophages deficient in caspase-11 following stimulation with P . gingivalis strain PG1587381 ( Figure 4D ) , while TNFα levels were not altered ( data not shown ) . In agreement with the requirement for caspase-11 in IL-1α production [50] , we observed decreased production of IL-1α following stimulation of BMDM obtained from caspase-11-deficient mice with P . gingivalis strain PG1587381 . However , we did not observe significant differences in the levels of IL-1α in BMDM obtained from caspase-11-deficient mice when stimulated with wild-type 381 compared to strain PG1587381 ( Figure 4E ) . These results suggest distinct mechanism ( s ) for IL-1α production independent of lipid A modifications . Collectively , these findings indicate that expression of modified lipid A species by P . gingivalis facilitates evasion of non-canonical inflammasome activation through a caspase-11-mediated pathway and obstructs downstream events associated with activation of this complex . To determine if the expression of modified lipid A by P . gingivalis is associated with the ability of the organism to promote chronic inflammation in vivo , we utilized a mouse model that mimics chronic P . gingivalis exposure as seen during human infection [51] , [52] . Atherosclerosis-prone ApoE−/− mice were orally infected with P . gingivalis strains 381 , PG1587381 , and PG1773381 and chronic inflammation at local ( oral bone loss ) and systemic ( atherosclerosis ) sites was evaluated [36] . Plaque accumulation in the innominate artery was examined by magnetic resonance angiogram ( MRA ) throughout the course of the study to assess progression of site-specific inflammatory atherosclerosis . The innominate artery exhibits a high degree of lesion progression and expresses features of human disease including vessel narrowing and perivascular inflammation [53] . MRA at 8 weeks after oral infection resulted in an increase in the change of luminal area for mice infected with all 3 strains , indicating that the mice were still growing at this age ( 14–16 weeks of age ) ( Figure 5A ) . At 16 weeks after oral infection , MRA revealed that oral infection with P . gingivalis strains 381 and strain PG1773381 resulted in significant luminal narrowing compared to sham-infected controls ( Figure 5A ) . In contrast , oral infection with P . gingivalis strain PG1587381 induced minimal luminal narrowing compared to sham-infected controls ( Figure 5A ) . Furthermore , P . gingivalis strains 381 and PG1773381 induced progressive luminal narrowing from 8 to 16wks compared to strain PG1587381 and sham-infected controls ( Figure 5A inset ) . Luminal narrowing was further validated by histological assessment of the innominate artery in postmortem sections . Hematoxylin and eosin staining of the innominate artery corresponding to the region of MRA analysis revealed an occlusion of the lumen in ApoE−/− mice infected with P . gingivalis strain 381 ( Figure S3 ) , in agreement with our previous studies [53] . Oral infection with P . gingivalis strain PG1773381 resulted in plaque accumulation that was comparable to that observed with P . gingivalis strain 381 ( Figure S3 ) . Oral infection with P . gingivalis strain PG1587381 resulted in thickening of the vessel wall without occlusion of the vasculature ( Figure S3 ) . To assess macrophage infiltrate of the atherosclerotic lesions , histological sections of the innominate artery were stained with F4/80 . We found oral infection with P . gingivalis strains 381 and PG1773381 resulted in an increase in macrophage accumulation in the innominate lesions compared to that observed with P . gingivalis strain PG1587381 and sham-infected controls ( Figure 5B ) . Lipid staining of en face aortas revealed that oral infection with P . gingivalis strains 381 and PG1773381 accelerated plaque accumulation compared to that observed in sham-infected mice ( Figure 6 ) . In contrast , oral infection with P . gingivalis strain PG1587381 induced minimal plaque accumulation ( Figure 6C ) . The inability of P . gingivalis strain PG1587381 to elicit inflammatory disease pathology was not due to failed activation of immunity , since we observed an induction of the humoral response by P . gingivalis strain PG1587381 that was comparable to that induced by P . gingivalis strains 381 and strain PG1773381 , as observed by serum levels of IgG1 , IgG2b , IgG2c and IgG3 ( Figure S4 ) . Assessment of alveolar bone loss in infected mice revealed that P . gingivalis strains 381 , PG1587381 , and PG1773381 all induced oral bone loss at similar levels ( Figure 7 ) . These results are consistent with studies demonstrating a predominant role for TLR2 signaling in P . gingivalis-induced oral inflammatory bone loss [54] , [55] . Collectively , these results indicate that expression of P . gingivalis lipid A structures that fail to engage TLR4 or function as TLR4 antagonists enables this pathogen to evade host innate immune detection and contributes to inflammation at sites distant from infection . In this study , we generated genetically defined strains of P . gingivalis expressing TLR4 agonist and antagonist lipid A species to examine the role of TLR4 evasion in P . gingivalis-induced chronic inflammation . Importantly , we determined that expression of TLR4 antagonist lipid A contributes to the ability of P . gingivalis to activate innate immunity and induce inflammation at systemic sites . Notably , induction of local inflammatory bone loss in response to P . gingivalis infection was not dependent on lipid A modifications , indicative of distinct mechanisms for the induction of local versus systemic vascular chronic inflammation . The expression of antagonistic or immunological inert lipid A species was associated with attenuated production of proinflammatory mediators and inflammasome activation , which correlated with increased bacterial survival in macrophages . We conclude that P . gingivalis evades TLR4-mediated bacterial clearance in the host , allowing it to exacerbate vascular inflammation ( Figure 8 ) . We and others have reported that the expression of P . gingivalis lipid A is regulated by growth phase , temperature , and levels of hemin [22]–[24] . The expression of multiple lipid A structures has complicated the interpretation of the host response elicited by P . gingivalis LPS [22] . During growth under hemin-replete conditions , P . gingivalis expresses an antagonistic lipid A , due to the repression of 1-phosphatase activity [23] . The antagonist lipid A expressed by P . gingivalis has been demonstrated to antagonize E . coli LPS binding to TLR4 [56] and to dampen the cytokine response typically induced by other Gram-negative pathogens [45] . The use of P . gingivalis strain PG1773381 in this study allowed us to specifically define the role of the antagonistic lipid A ( typically expressed under hemin-replete conditions ) in the induction of chronic inflammation at both local and distant sites from infection . We observed that P . gingivalis strains 381 and PG1773381 induced comparable levels of inflammatory atherosclerosis suggesting that in vivo P . gingivalis is exposed to a hemin-replete environment and predominantly expresses an antagonistic lipid A that exacerbates chronic systemic inflammation . Evasion of TLR4 signaling through lipid A modifications has been attributed to the ability of a number of highly pathogenic Gram-negative pathogens to cause disease [3] . For example , F . novicida expresses a tetra-acylated lipid A , with one phosphate group and does not induce a TLR4 response [10] . Y . pestis expresses a tetra-acylated lipid A that functions as a TLR4 antagonist at 37°C , which allows this pathogen to remain undetected in the bloodstream during early stages of infection [9] , [11] . Generation of a strain of Y . pestis that expressed a more immunostimulatory LPS conferred a protective immune response against this pathogen [57] . Likewise , Pseudomonas aeruginosa expresses a modified LPS which promotes evasion of TLR4 signaling , favors intracellular survival , and has been postulated to contribute to chronic persistence in Cystic Fibrosis patients [58] . In agreement with these studies , we have shown that P . gingivalis modifies its lipid A structure in order to evade host defenses and establish chronic infection leading to persistent low-grade inflammation in the vasculature . Uniquely , P . gingivalis evasion of host innate immunity at TLR4 results in progression of inflammation at a site that is distant from local infection by gaining access to the vasculature . A number of reports have proposed that P . gingivalis lipid A modifications are a mechanism for evasion of TLR4 signaling [6] , [23] , [26] . However , these studies utilized purified P . gingivalis LPS in an in vitro setting . To date , only this study and our recent study in a rabbit model of periodontitis [43] have begun to shed light on the immunological consequences of differential activation of the TLR4 complex by P . gingivalis LPS through the use of live bacteria that express a “locked” lipid A profile that is not responsive to growth conditions . Furthermore , we assessed the host response in the oral cavity and vasculature , physiologically relevant sites of chronic inflammation observed in humans . Notably , the use of purified LPS in our study resulted in discrepancies in TLR4 activation by isolated LPS versus the whole bacterium . These differences observed in the host response may be a reflection of LPS structure and composition on the cell surface , which leave us with new areas of investigation with regards to LPS translocation . Potentially , the less potent lipid A forms ( m/z 1368 , 1448 , 1688 ) may be primarily expressed on the bacterial outer membrane and , consequently , render wild-type 381 and PG1773381 unable to activate TLR4 . In contrast , strain PG1587381 is expected to exclusively accumulate lipid A TLR4 agonists ( m/z 1688 and possibly m/z 1768 ) in the outer membrane since the presence of a lipid A 4′-phosphate precludes production of the lipid A antagonist ( m/z 1448 ) or non-activating lipid A ( m/z 1368 ) in this strain . Overproduction of proinflammatory mediators and dysregulated inflammasome activation has been reported to contribute to inflammatory pathology in a number of chronic diseases [59] . Paradoxically , we observed that increased stimulation of TLR4 by P . gingivalis enhanced production of proinflammatory mediators and activation of the inflammasome , resulting in attenuated systemic inflammation ( Figure 8 ) . These results indicate that production of inflammatory mediators is protective against pathogen-mediated chronic inflammation , which is in agreement with our recent results that documented a protective role for TLR4 in P . gingivalis-mediated chronic inflammation at systemic sites [42] . This report , along with our current study , is in contrast to other studies elucidating the role of TLR4 in pathogen-mediated atherosclerosis progression . Infection of ApoE−/− TLR4−/− mice , fed a high-fat diet , with C . pneumoniae resulted in diminished atherosclerosis compared to ApoE−/− infected mice [60] . Additionally , a previous study documented that common mechanisms of signaling via TLR2 , TLR4 and MyD88 link stimulation by multiple pathogens and endogenous ligands to atherosclerosis progression [61] , [62] . Therapeutic antagonism has been suggested to be beneficial in the treatment of chronic atherosclerosis [63] . However , we have demonstrated TLR4 antagonism exacerbates atherosclerosis progression . Collectively , our study highlights the complexity of chronic inflammatory pathways in diseases like atherosclerosis that are exacerbated by pathogen infection and further elucidate pathogen-specific mechanisms for chronic disease progression . An important observation from this study was that P . gingivalis failed to activate the inflammasome . It has recently been reported that Gram-negative bacteria utilize a non-canonical pathway for inflammasome activation that is mediated by caspase-11 [48] , [49] . Kayagaki et al . [14] have shown that H . pylori , whose tetra-acylated lipid A poorly activates the TLR4 complex , failed to trigger the non-canonical inflammasome . Although TLR4 signaling correlates with non-canonical inflammasome activity , this group reported that activation of the non-canonical inflammasome is independent of TLR4 signaling , further suggesting an unknown sensor in the cytosol that detects modified lipid A ( Figure 8 ) . We found that caspase-11 expression was essential for IL-1β production elicited by P . gingivalis strain PG1587381 , pointing to a pivotal role for activation of the non-canonical inflammasome in P . gingivalis infection . Pathogen evasion of inflammasome activation has been proposed to serve a dual role: to prevent IL-1β release and to circumvent host cell death in order to provide an intracellular niche for the pathogen to survive [17] . Indeed , we observed that the low levels of IL-1β induced by P . gingivalis strains 381 and PG1773381 correlated with an enhanced ability of these organisms to survive in macrophages . Likewise , the induction of relatively high levels of IL-1β by P . gingivalis strain PG1587381 correlated with decreased survival of this strain in macrophages . The enhanced survival we observed with wild-type 381 and PG1773381 are in agreement with our observation that both strains were relatively resistant to killing in the presence of the cationic antimicrobial peptide polymyxin B . In contrast , strain PG1587381 was unable to survive intracellularly and was rapidly killed . These results suggest that P . gingivalis utilizes multiple mechanisms concurrently to promote its adaptive fitness . The ability of P . gingivalis to survive intracellularly in the macrophage is intriguing when considering the link between periodontal disease and systemic inflammatory conditions . We propose that P . gingivalis entry and survival into macrophages may be a mechanism for dissemination of the bacterium from the oral cavity to other systemic sites , such as the vasculature . We have recently identified P . gingivalis in blood myeloid dendritic cells of humans with chronic periodontitis , suggesting a role for blood myeloid dendritic cells in harboring and disseminating pathogens from the oral mucosa to atherosclerotic plaques [64] . The mechanism utilized by P . gingivalis for survival in myeloid cells remains elusive . Wang et al . [65] have shown that intracellular survival of P . gingivalis within macrophages is dependent upon TLR2-mediated entry into lipid rafts . Pathogens that hijack lipid rafts do not readily fuse with late endosomes and lysosomes and may potentially fuse to autophagosomes [66] , [67] . Whether intracellular trafficking to autophagosomes is the mechanism for P . gingivalis intracellular survival and dissemination to distant sites remains unknown ( Figure 8 ) . An interesting finding from this study was expression of P . gingivalis modified lipid A species did not alter the ability of the organism to induce oral inflammatory bone loss . These results are in agreement with previous studies that show that TLR4 is not needed for the induction of inflammatory bone loss , and it is predominantly mediated via TLR2 signaling [37] , [68] . We also recently identified a TLR2- and TNF-dependent macrophage-specific mechanism for P . gingivalis-induced inflammatory bone loss in vivo [38] . In the current study , we observed comparable levels of TNFα were induced in macrophages stimulated with wild-type 381 and the lipid A mutants . In addition to the role of TNFα , it has been recently reported that P . gingivalis is able to induce oral bone loss at very low colonization levels , which triggers changes to the amount and composition of the oral commensal microbiota [69] . We have recently demonstrated in a rabbit model of periodontitis that lipid A phosphatases are required for both colonization of the rabbit and increases in the oral microbial load [43] . Whether this same mechanism for inflammatory bone loss is at play in our study remains to be determined . It is well established that atherosclerosis progression is due to excessive production of proinflammatory mediators [70] . Although lipid deposition is considered a leading contributor to the inflammation , additional stimuli , such as infectious agents , have been considered as sources for the continuous inflammation [35] . In our study , we observed infection with P . gingivalis induced low levels of proinflammatory mediators but accelerated chronic inflammatory atherosclerosis . Thus , the question arises as to why a pathogen that induces low levels of inflammatory mediators would accelerate chronic inflammatory atherosclerosis . In a recent clinical trial for the inflammasome-mediated disease , Cryopyrin-associated periodic syndrome ( CAPS ) , patients receiving the humanized monoclonal antibody , canakinumab , specific for IL-1β , had a 67% increased risk for infection compared to 25% of patients in the placebo group [71] . This clinical trial supports the results presented in our study that highlight a protective role for activation of innate immunity against low-grade chronic infection . An additional clinical trial was recently launched using canakinumab with the hypothesis that IL-1β inhibition will reduce major cardiovascular events in patients with preexisting coronary artery disease ( CAD ) [72] . Our results demonstrate that the potential benefit of long-term use of a neutralizing antibody to IL-1β in humans at high risk for atherosclerotic vascular disease must be substantial enough to counter the increased risk of infection [71] . Furthermore , future therapies need to be developed to consider the complexity of inflammatory pathways in chronic inflammation and the role of chronic infection in disease pathology . This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by Boston University's Institutional Animal Care and Use Committee ( IACUC ) protocol numbers AN15312 and AN14348 . Boston University is committed to observing federal policies and regulations and Association for Assessment and Accreditation of Laboratory Animal Care ( AAALAC ) International standards and guidelines for humane care and use of animals . Federal guidelines , the Animal Welfare Act ( AWA ) and The Guide were followed when carrying out experiments . Procedures involved euthanasia and harvesting of bone marrow macrophages . All efforts were made to minimize discomfort , pain and distress . Frozen stocks of P . gingivalis wild-type strain 381 and the lipid A mutants ( PG1587381 and PG1773381 ) were grown anaerobically at 37°C on blood agar plates ( Remel ) for 3–5 days [73] . Brain heart infusion broth ( Becton-Dickinson Biosciences ) supplemented with yeast extract ( 0 . 5%; Becton-Dickinson Biosciences ) , hemin ( 10 µg/ml; Sigma-Aldrich ) , and menadione ( 1 mg/ml; Sigma- Aldrich ) was inoculated with plate grown bacteria and cultures grown anaerobically for 16–18 h . P . gingivalis lipid A mutants were grown in the presence of erythromycin ( 5 µg/mL ) . The genomic nucleotide sequences encoding the putative lipid A 1-phosphatase , PG1773 , and the putative lipid A 4′-phosphatase , PG1587 , were obtained from searches of the annotated P . gingivalis W83 genome at The Comprehensive Microbial Resource ( http://cmr . jcvi . org/tigr-scripts/CMR/CmrHomePage . cgi ) . Gene deletions were created by introducing an erythromycin resistance cassette ( ermF/AM ) in place of the coding region for PG1773 and PG1587 . Polymerase chain reaction ( PCR ) amplification of genomic DNA from P . gingivalis 381 was performed using primer sets designed against the W83 sequence to amplify 1000 base-pairs upstream and 1000 base-pairs downstream from the regions adjacent to the PG1773 and PG1587 coding regions , respectively . The amplified 5′ and 3′ flanking regions for PG1773 and PG1587 , respectively , were co-ligated with the ermF/AM cassettes respectively into pcDNA3 . 1 ( − ) to generate the gene disruption plasmids , p1773 5′flank:erm:3′flank and p1587 5′flank:erm:3′flank . P . gingivalis 381 deficient in either PG1587 ( PG1587381 ) or PG1773 ( PG1773381 ) was generated by introducing either p1587 5′flank:erm:3′flank or p1773 5′flank:erm:3′flank into P . gingivalis 381 by electroporation in a GenePulser Xcell ( BioRad , Hercules , CA ) . Bacteria were plated on TYHK/agar plates containing the appropriate selective medium , which included erythromycin ( 5 µg/ml ) , and incubated anaerobically . One week later , colonies were selected for characterization . Loss of the PG1587 and PG1773 coding sequences were confirmed in all clones by PCR analyses using primers designed to detect the coding sequences in wild-type 381 bacteria . LPS and Lipid A from P . gingivalis 381 and the lipid A mutant strains ( PG1587381 and PG1773381 ) were isolated as previously described [23] . For MALDI-TOF MS analyses , lipid A were analyzed in the negative ion mode on an AutoFlex Analyzer ( Bruker Daltonics ) . Data were acquired and processed using Flex Analysis software ( Bruker Daltonics ) [6] , [23] . HEK293 cells were plated in 96-well plates at a density of 4×104 cells per well , and transfected the following day with plasmids bearing firefly luciferase , Renilla luciferase , recombinant murine TLR4 and MD-2 or recombinant murine TLR2 and TLR1 by standard calcium phosphate precipitation . After overnight transfection , the test wells were stimulated in triplicate for 4 hours at 37°C with the indicated doses of LPS isolates or live bacteria . Following stimulation , the transfected HEK293 cells were rinsed with phosphate-buffered saline and lysed with 50 µl of passive lysis buffer ( Promega , Madison , WI ) . Luciferase activity was measured using the Dual Luciferase Assay Reporter System ( Promega , Madison , WI ) . Data are expressed as fold increase of NF-κB-activity which represents the ratio of NF-κB-dependent fire-fly luciferase activity to β-Actin promoter-dependent Renilla luciferase activity . BHI broth cultures of wild-type 381 and the lipid A mutant strains were started at an optical density of . 1 at 660 nm in the presence or absence of increasing concentrations ( 1 , 5 , 10 , 25 , 50 µg/mL ) of polymxin B ( InvivoGen ) . After overnight growth under anaerobic conditions , growth was assessed spectrophotometrically at 660 nm [74] . Male ApoE−/− and C57BL/6 mice were obtained from The Jackson Laboratory ( Bar Harbor , ME ) . C57BL/6 mice deficient in TLR2 and TLR4 were provided by Dr . S . Akira ( Osaka University , Osaka , Japan ) and bred in house . Mice were maintained under specific-pathogen free conditions and cared for in accordance with the Boston University Institutional Animal Care and Use Committee . Bone marrow derived macrophages ( BMDM ) from wild-type and knockout mice were cultured in RPMI with 10% fetal bovine serum ( Thermo Scientific HyClone Fetal Bovine Serum ( U . S . ) , Defined SH3007003HI Heat inactivated ) and 20% L929 supernatants [49] and were allowed to mature into macrophages over 7 days . Cells were seeded into 24-well plates at 2×105 cells/well ( ELISA assays ) or 6-well plates at 1×106 cells/well ( Western blot analysis ) and stimulated with bacteria at indicated MOI overnight . Cells stimulated with LPS from E . coli OIII:B4 ( InvivoGen ) or Pam3CysSk4 ( InvivoGen ) served as controls . Levels of IL-1β , TNFα , IL-6 ( BD Bioscience ) , IL-1α ( eBioscience ) and KC ( R&D Systems ) in cell culture supernatants were analyzed by ELISA . Proteins from cell culture supernatants were precipitated with ethanol at −20°C overnight and resuspended in Laemmli sample buffer . Cellular lysates were collected in RIPA buffer ( Thermo Scientific ) and samples were prepared in Laemmli sample buffer . Samples were separated by SDS-PAGE , transferred to polyvinyldifluoride membranes , blocked in 5% milk and target proteins were detected using antibodies to IL-1β ( H-153 ) and caspase-1 p10 ( M-20 ) ( Santa Cruz Biotechnology ) . An antibody to β-actin ( A1978 Sigma ) was used as the loading control . BMDM were stimulated with P . gingivalis or lipid A mutants for 2 h and 6 h . Extracellular nonadherent bacteria were removed by washing with PBS . Adherent bacteria were killed by addition of gentamicin ( 300 µg/mL ) and metronidazole ( 200 µg/mL ) for 1 hr . After PBS wash , BMDM were lysed with HyClone water ( Thermo Scientific ) for 10 min . Serial dilutions of the lysate were plated on blood agar plates and cultured anaerobically for CFU enumeration [65] . Mice were fed a normal chow diet ( Global 2018; Harlan Teklad , Madison , WI ) . Six-week old male mice were treated with a 10-day regimen of oral antibiotics to allow for P . gingivalis colonization . Mice were challenged by oral application of vehicle ( 2% carboxymethylcellulose in PBS ) or the P . gingivalis strains ( 1×109 CFU ) at the buccal surface of the maxilla 5 times a week for 3 weeks [36] , [37] . In vivo imaging of the innominate artery was performed using a vertical-bore Bruker 11 . 7 T Avance spectrometer ( Bruker; Billerica , MA ) as previously described [53] . Mice were anesthetized with 0 . 5–2% inhaled isoflurane and placed in a vertical 30 mm probe ( Micro 2 . 5 ) . Respiration was monitored using a small animal monitoring and gating system ( SA Instruments , Waukesha , WI ) . The angiography data was acquired with a fast low-angle shot ( FLASH ) sequence using the following parameters: slab thickness = 1 . 5 cm; flip angle = 45°; repetition time = 20 ms; echo time = 2 . 2 ms; field of view = 1 . 5×1 . 5×1 . 5 cm; matrix = 128×128×128; number of average = 4 . The total scan time was ∼25 min . Visualization of the vasculature was achieved by 3D maximum intensity projections ( MIP ) of angiographic images reconstructed using Paravision . The target cross section of the innominate artery was chosen at 0 . 3- to 0 . 5-mm distance below the subclavian bifurcation . Lumen area of the chosen cross section was manually defined and calculated with ImageJ ( National Institutes of Health ) by two independent observers . The intra-reader reliability was excellent with interclass correlation coefficient values of 0 . 91 . Mice were euthanized ( n = 3–4/group ) , perfused with PBS ( 5 mL ) and the aortic arch with heart tissue was embedded in OCT freezing compound . Seven-micrometer serial cryosections were collected every 70 µm in the innominate artery . Immunohistochemistry was performed on cryosections corresponding to greatest plaque accumulation in the innominate artery as previously described [42] , [53] using rat anti-mouse F4/80 ( no . MCA497R; Serotec , Oxford , U . K . ) or isotype controls ( no . MCA1125; Serotec ) . Biotinylated anti-rat ( mouse absorbed ) IgG was used as secondary Ab ( Vector Laboratories , Burlin- game , CA ) . Nuclei were counter-stained with hematoxylin . Digital micrographs were captured at 10× and 40× . Aortas were harvested and stained with Oil Red O as described [42] . Digital micrographs were taken , and total area of atherosclerotic plaque was determined using ImageJ ( NIH ) by a blinded observer . Three-dimensional analysis of alveolar bone loss was assessed as previously described [38] . Briefly , cephalons were fixed for 24–48 h in 4% buffered paraformaldehyde and stored at 4°C in 70% ethanol until evaluation by microcomputed tomography ( micro-CT ) . Quantitative three-dimensional analysis of alveolar bone loss in hemi-maxillae was performed using a desktop micro-CT system ( μCT 40; Scanco Medical AG , Bassersdorf , Switzerland ) . Maxillary block biopsies were scanned at a resolution of 12 µm in all three spatial dimensions . Raw images were converted into high-quality dicoms and analyzed using computer software ( Amira 5 . 2 . 2; Visage Imaging ) . Residual supporting bone volume was determined for the buccal roots . The apical basis of the measured volume was set mesio-distally parallel to the cemento-enamel junction and bucco-palatinally parallel to the occlusal plane . Results represent residual bone volume ( mm3 ) above the reference plane ( 180 µm from the cemento-enamel junction ) . Data were analyzed by two-tailed unpaired Student's t test or ANOVA with Bonferroni's posttest where indicated . A p value of . 05 was considered indicative of statistical significance .
Several human pathogens express structurally divergent forms of lipid A , the endotoxic portion of lipopolysaccharide ( LPS ) , as a strategy to evade host innate immune detection and establish persistent infection . Expression of modified lipid A species promotes pathogen evasion of host recognition by Toll-like receptor-4 ( TLR4 ) and the non-canonical inflammasome . The Gram-negative oral anaerobe , Porphyromonas gingivalis , expresses lipid A structures that function as TLR4 agonists or antagonists , or are immunologically inert . It is currently unclear how modulation of P . gingivalis lipid A expression contributes to innate immune recognition , survival , and the ability of the pathogen to induce local and systemic inflammation . In this study , we demonstrate that P . gingivalis expression of antagonist lipid A species results in attenuated production of proinflammatory mediators and evasion of non-canonical inflammasome activation , facilitating bacterial survival in the macrophage . Infection of atherosclerosis-prone ApoE−/− mice with this strain resulted in progression of chronic inflammation in the vasculature . Notably , the ability of P . gingivalis to induce local inflammatory bone loss was independent of lipid A modifications , supporting distinct mechanisms for induction of local versus systemic inflammation . Our work demonstrates that evasion of immune detection at TLR4 contributes to pathogen persistence and facilitates low-grade chronic inflammation .
[ "Abstract", "Introduction", "Results", "Materials", "and", "Methods" ]
[ "biology", "and", "life", "sciences", "immunology", "microbiology" ]
2014
Distinct Lipid A Moieties Contribute to Pathogen-Induced Site-Specific Vascular Inflammation
The tripeptide glutathione is the most abundant cellular antioxidant with high medical relevance , and it is also required as a co-factor for various enzymes involved in the detoxification of reactive oxygen species and toxic compounds . However , its cell-type specific functions and its interaction with other cytoprotective molecules are largely unknown . Using a combination of mouse genetics , functional cell biology and pharmacology , we unraveled the function of glutathione in keratinocytes and its cross-talk with other antioxidant defense systems . Mice with keratinocyte-specific deficiency in glutamate cysteine ligase , which catalyzes the rate-limiting step in glutathione biosynthesis , showed a strong reduction in keratinocyte viability in vitro and in the skin in vivo . The cells died predominantly by apoptosis , but also showed features of ferroptosis and necroptosis . The increased cell death was associated with increased levels of reactive oxygen and nitrogen species , which caused DNA and mitochondrial damage . However , epidermal architecture , and even healing of excisional skin wounds were only mildly affected in the mutant mice . The cytoprotective transcription factor Nrf2 was strongly activated in glutathione-deficient keratinocytes , but additional loss of Nrf2 did not aggravate the phenotype , demonstrating that the cytoprotective effect of Nrf2 is glutathione dependent . However , we show that deficiency in glutathione biosynthesis is efficiently compensated in keratinocytes by the cysteine/cystine and thioredoxin systems . Therefore , our study highlights a remarkable antioxidant capacity of the epidermis that ensures skin integrity and efficient wound healing . Maintenance of the cellular redox balance is essential for appropriate cellular function . This balance is frequently challenged , particularly in response to infections or tissue damage inflicted by mechanical , chemical or physical insults . Under these conditions cells produce an excess of reactive oxygen and nitrogen species ( ROS and RNS ) . While low levels of these molecules are required for cellular signaling [1] , high levels can damage all types of cellular macromolecules [2] . Therefore , cells strongly depend on efficient ROS/RNS detoxification systems . This is achieved by various ROS/RNS-detoxifying enzymes , but also by low molecular weight antioxidants , such as vitamins C and E . Of particular importance is reduced glutathione ( GSH ) , a tripeptide composed of glutamate , cysteine , and glycine . It is highly abundant in all cell types ( ≈ 1–10 mM ) , serves as a cellular redox buffer , and protects against the toxicity of electrophilic compounds . It also reacts with nitric oxide ( NO ) to yield nitrosoglutathione , thereby reducing the amount of free NO . Furthermore , it is used as a co-factor for glutathione peroxidases and by glutathione S-transferases for the glutathionylation of selected proteins and for conjugation of toxic substances , and it is required for the maturation of cytosolic iron-sulfur proteins [3–5] . Due to these vital functions , GSH deficiency plays a key role in the pathogenesis of major human diseases , including neurodegenerative diseases and diabetes , whereas increased GSH levels reduce the susceptibility of cancer cells to oxidative stress and therefore promote cancer progression and resistance to chemo- and radiotherapy [6 , 7] . Since the skin forms the outermost barrier to the environment and is therefore frequently exposed to ultraviolet ( UV ) irradiation , toxic chemicals , or mechanical insults , the cytoprotective functions of GSH are likely to be of particular importance in this tissue . Indeed , esterified GSH prevented apoptosis of cultured keratinocytes under hyperglycemic conditions [8] . Upon UVA or UVB irradiation of cultured fibroblasts or keratinocytes , depletion of GSH occurred [9 , 10] , resulting in oxidative stress and cell death [11] . A role for GSH in wound repair has been suggested , since GSH depletion occurred in skin wounds , especially in situations of impaired healing , such as in immunocompromised rats , in diabetic mice and in human diabetic foot ulcers [12 , 13] . Furthermore , GSH levels were reduced in wounds of aged compared to young rats [14] , and chemical depletion of GSH in rat wounds reduced wound bursting strength [15] . On the other hand , topical treatment of poorly healing wounds in diabetic mice with esterified GSH accelerated the repair process [13] . Hence , all these studies strongly suggest that normal GSH levels are crucial for efficient wound healing . So far GSH functions have mainly been studied with chemical agents that deplete the tripeptide , in particular buthionine sulfoximine ( BSO ) . However , this approach does not allow long-term GSH depletion and analysis of cell-type specific activities in vivo . The generation of animals deficient in the rate-limiting enzyme in GSH biosynthesis—glutamate cysteine ligase ( Gcl ) —now allows addressing the role of GSH in tissue homeostasis , repair and disease . Gcl is a heterodimer consisting of a catalytic ( Gclc ) and a “regulatory” modifier ( Gclm ) subunit , and catalyzes the formation of γ-glutamylcysteine . Whereas Gclc possesses catalytic activity , Gclm cannot synthesize the dipeptide , but serves to change the kinetic characteristics of Gclc [4] . Mice lacking Gclm in all cells are viable and fertile , in spite of a strong reduction in GSH levels [16] . By contrast , Gclc knockout mice die in utero from enhanced apoptotic cell death [17 , 18] . However , the affected cell types and the underlying mechanisms have not been characterized in detail . Here , we analyzed the consequences of Gclc deficiency in keratinocytes , a cell type that continuously proliferates under steady state conditions and is frequently exposed to various external challenges . We demonstrate that GSH protects from DNA and mitochondrial damage and consequently ensures survival of keratinocytes in normal and wounded skin . Loss of GSH was partially compensated by the thioredoxin system , but not by activation of the cytoprotective transcription factor nuclear factor ( erythroid-derived 2 ) -like 2 ( Nrf2 ) . Thus , keratinocytes have developed a remarkable combination of protective strategies that contribute to the efficient barrier function of the epidermis and help to maintain skin integrity even under stress conditions . We generated mice lacking Gclc in all keratinocytes ( designated koG mice ) by deleting the Gclc gene in the epidermal basal layer and in the outer root sheath keratinocytes of hair follicles using mice expressing Cre recombinase under control of the keratin 5 ( K5 ) promoter ( Fig 1A ) . The mutant mice were designated koG mice . Loss of Gclc expression was verified by qRT-PCR using epidermal RNA from mice at the age of 3 weeks ( 3W ) or two months ( 2M ) and from cultured primary keratinocytes ( 1°KC—Fig 1B ) . The residual levels of Gclc transcripts in the epidermis most likely result from expression in epidermal cells other than keratinocytes , which are not targeted by the keratin 5 promoter . A similar result was obtained for total GSH/GSSG levels ( Fig 1C ) . Loss of Gclc protein in the epidermis and reduced Gclc levels in total skin were confirmed by Western blot analysis ( Fig 1D ) . Since Gclc expression was still almost undetectable at 2M , it seems unlikely that cells , which had escaped recombination , predominantly contribute to epidermal regeneration . The loss of Gclc in keratinocytes did not affect the expression of the glutathione-dependent enzymes peroxiredoxin 6 ( Prdx6 ) and glutathione peroxidase 4 ( Gpx4 ) , while expression levels of glutaredoxin 2 ( Glrx2 ) were slightly increased ( S1A and S1B Fig ) . At 3W of age Gclc-deficient mice were first distinguishable from littermate controls by the rough appearance of their fur ( Fig 1E ) . Patchy hair loss was observed in some knockout mice ( Fig 1E right panel; see head region , and S1C Fig ) and the skin appeared less elastic ( S1D Fig ) . In addition , the hairs of koG mice were thinner and showed malformation ( S1E Fig ) . The hair loss was not due to loss of hair follicles , which showed the same or even a mildly increased density in koG mice ( S1F Fig ) . Rather , it is most likely the consequence of severe hyperkeratosis in the hair follicle infundibulum ( S1G Fig ) , which affects the anchorage of the hairs and may also cause the observed hair malformation due to narrowing of the hair canal . KoG mice failed to gain weight after weaning ( Fig 1F ) and approximately 25% of them died or had to be sacrificed according to animal welfare regulations because of their general weakness ( Fig 1G ) . The lack of weight gain was most likely due to malnutrition that resulted from hyperkeratosis in the forestomach ( Fig 1H ) , where the K5 promoter is also active [19] . Stomach abnormalities were also reflected by the severe bloating of the stomach ( Fig 1I ) . Blood glucose levels of koG mice were significantly lower compared to control mice at 3W and 2M ( S2A Fig ) , further suggesting malnutrition as the cause of cachexia . By contrast , it is not the consequence of tooth abnormalities ( S2B Fig ) or of abnormal activity of the K5 promoter in tissues lacking K5 expression , such as the liver or the kidney ( S2C Fig ) , which would result in GSH deficiency in other organs relevant for whole body metabolism . Furthermore , systemic inflammation as a reason for the lack of weight gain seems unlikely , since serum levels of the pro-inflammatory cytokine interleukin-6 ( Il-6 ) , a marker for systemic inflammation , were below the detection levels of the ELISA ( 0 . 05 ng/ml ) . Cutaneous abnormalities were not detected prior to P18 ( S3A Fig ) . From 3W onwards , progressive hyperkeratosis was observed as reflected by hematoxylin/eosin ( H&E ) staining and immunofluorescence analysis of the late differentiation marker loricrin , which had a broader and more diffuse distribution in the knockout mice ( Fig 2A ) . Furthermore , a more intense staining for filaggrin , a structural protein of the stratum corneum ( Fig 2B ) , was observed in the 3W koG epidermis , followed by patchy expression of filaggrin in the mutant mice at 2M ( Fig 2A ) . The thickness of the viable epidermis was not affected by the loss of Gclc ( Fig 2C ) , and keratin 14 ( K14 ) and K10 were appropriately expressed in the basal or suprabasal layers , respectively ( Fig 2A and 2B ) . However , the K10 positive area was extended ( Fig 2A ) . In addition , some patches of interfollicular K6 positive areas were detected ( Fig 2A ) , demonstrating mild abnormalities in keratinocyte differentiation . qRT-PCR and Western blot analysis of epidermal RNAs/lysates confirmed the mild increase in loricrin expression and the stronger increase in filaggrin expression in young mice ( Fig 2D–2F ) . Processing of filaggrin was not affected ( S3B Fig ) . Hyperkeratosis in koG mice was also detected by electron microscopy , which revealed reduced attachment of the corneocytes ( Fig 2G ) . These stratum corneum abnormalities correlate with a mild increase in transepidermal water loss ( TEWL ) , which reflects a defect in the epidermal barrier ( Fig 2H ) . This was already seen in some mice at the age of 3W , and the difference was statistically significant at the age of 2M . The rate of keratinocyte proliferation was not reduced in koG mice at 3W . On the contrary , keratinocytes became hyperproliferative at the age of 2M ( Fig 3A and 3B ) . The late onset suggests that keratinocyte hyperproliferation is a non-cell autonomous effect , and may result from an increase in cutaneous immune cells , which are known producers of keratinocyte mitogens [20] . Consistent with this assumption , toluidine blue staining revealed an increase in the number of dermal mast cells , and immunofluorescence staining showed that the number of epidermal γδ T cells was significantly increased at 2M ( Fig 3C–3E ) . A more detailed analysis of the epidermal immune cells by flow cytometry confirmed the increase in epidermal γδ T cells , although the number of γδ T cells expressing the activation marker CD69 was not significantly increased ( Figs 3F–3K and S4A ) . This accumulation started at the age of 3W and became more obvious at 2M . Analysis of dermal cells by flow cytometry showed no increase in immune cells in koG mice at the age of 3W , a significant increase in the number of all immune cells at the age of 2 months , but no differences in the number of macrophages and neutrophils at any time point ( S4B and S4C Fig ) . The mild inflammation , however , was not associated with a significant increase in the expression of the pro-inflammatory cytokines tumor necrosis factor alpha ( Tnfα ) and Il6 , and of thymic stromal lymphopoietin ( Tslp ) in the skin of koG mice ( Fig 3L–3N ) . Expression of S100A8 was increased in the epidermis of young koG mice , but returned to basal levels at the age of 2M ( Fig 3O ) . Finally , there was no increase in the expression of prostaglandin-endoperoxide synthase 2 ( Ptgs2 , also known as cyclooxygenase-2 ) , suggesting that prostaglandin production is not enhanced ( Fig 3P ) . These findings demonstrate that there is only a mild cutaneous inflammation in koG mice and that the lack of weight gain is most likely not a consequence of systemic abnormalities that result from enhanced production and release of pro-inflammatory cytokines in the skin . Since chemical Gcl inhibitors strongly affected the healing of rat incisional wounds [15] , we analyzed the healing of full-thickness excisional wounds in koG and control mice . These experiments were performed prior to the development of health deficits and severe skin abnormalities ( P19-24 ) to exclude that any healing abnormalities are secondary to the malnutrition or to pre-existing histological abnormalities in the skin . Histomorphometric analysis of stained wound sections using the parameters shown in Fig 4A revealed no difference in wound closure and length of the migrating epithelium at days 2 , 3 and 5 after wounding ( Fig 4B–4D ) . There was a mild , but significant reduction in the area of the wound epithelium in koG mice compared to controls at day 5 after wounding ( Fig 4E ) , which , however , did not result from reduced keratinocyte proliferation ( Fig 4F and 4G ) . The unexpectedly weak epidermal phenotype of Gclc-deficient mice , even in response to wounding , suggested that other proteins or low molecular weight antioxidants might compensate at least in part for the loss of Gclc in keratinocytes . A likely candidate is the Nrf2 transcription factor , which controls the expression of a battery of cytoprotective genes [21] and which was shown to be activated upon chemical GSH depletion [22 , 23] . Furthermore , activation of Nrf2 in the skin either pharmacologically or through expression of a constitutively active Nrf2 mutant ( caNrf2 ) in keratinocytes of transgenic mice caused acanthosis and hyperkeratosis in the epidermis and in the hair follicle infundibuli combined with patchy hair loss—a similar phenotype as seen in koG mice [24] . Indeed , a strong increase in the expression of the well-established Nrf2 target genes NAD ( P ) H dehydrogenase quinone 1 ( Nqo1 ) and sulfiredoxin-1 ( Srxn1 ) was observed in the epidermis of koG mice at 3W and 2M , together with upregulation of secretory leukocyte peptidase inhibitor ( Slpi ) and small proline-rich protein 2D ( Figs 5A and S5A ) . The overexpression of these recently identified Nrf2 target genes had been shown to be responsible for the epidermal and the hair follicle phenotype of mice expressing caNrf2 in keratinocytes [24 , 25] . Upregulation was confirmed for additional Nrf2 target genes at 3W ( S5B Fig ) and for the gene encoding “Elongation of very long chain fatty acids protein 3” ( Elovl3 ) ( S5C Fig ) . This enzyme is involved in the production of long chain fatty acids , and it is indirectly regulated by caNrf2 in keratinocytes [25] . Its abnormal expression may contribute to the barrier function defect of caNrf2-transgenic and of koG mice due to alterations in the lipid barrier . Other Elovls , however , where not dysregulated in the Gclc knockout epidermis ( S5C Fig ) , which might explain the milder barrier defect of koG mice compared to caNrf2-transgenic mice . Activation of Nrf2 in the absence of Gclc is a cell autonomous effect , since expression of Nrf2 target genes was also upregulated in cultured Gclc-deficient keratinocytes ( Fig 5B ) . By contrast , expression of superoxide dismutase 1 and catalase was neither affected in vitro nor in vivo ( S5D Fig ) . Furthermore , expression of L-gulonolactonoxidase , an enzyme essential for the production of the antioxidant ascorbate ( Vitamin C ) , could not be detected in epidermal and total skin samples of ctrl and koG mice , whereas it was readily detectable in liver samples ( S5D Fig ) . To determine if the activation of Nrf2 has a compensatory function , we generated mice lacking both Gclc and Nrf2 in keratinocytes ( designated koG/N mice ) ( Fig 5C and 5D ) . The enhanced expression of Nrf2 target genes that occurred in Gclc-deficient epidermis was indeed completely ( Nqo1 and Srxn1 ) or partially ( Slpi and Sprr2d ) rescued ( Fig 5E ) . This was confirmed for some of the genes in primary keratinocytes ( Fig 5F ) . In contrast to our expectations , koG/N mice did not exhibit a more severe macroscopic or histological phenotype compared to koG mice at 3W ( Fig 5G and 5H ) , and the expression of keratinocyte differentiation markers was also not obviously affected by the loss of Nrf2 ( Fig 5H ) . There was also no reduction of the hyperkeratosis , and the squames were even more detached ( Fig 5H ) . The additional loss of Nrf2 had also no effect on keratinocyte proliferation , TEWL , and body weight ( Fig 5I–5K ) . The only additional abnormalities were misalignment and malformation of hair follicles combined with cyst formation ( Fig 5H and 5L ) . Even at 2M of age , when the phenotype in single Gclc knockout mice becomes more severe , we did not observe additional abnormalities in skin morphology , body weight or TEWL in koG/N mice ( S5E–S5G Fig ) . We next determined if the epidermal abnormalities in koG mice and the reduced area of the wound epidermis result from enhanced cell death . Indeed , a significant increase in the number of cleaved caspase-3 positive ( apoptotic ) keratinocytes was observed in the epidermis of koG mice with an early onset already at P2 . 5 and prior to the development of macroscopic or histological abnormalities ( Figs 6A and S6A ) , but there was no further increase by concomitant loss of Nrf2 ( Fig 6A ) . Consistent with the initiation of apoptosis by stress-induced activation/stabilization of p53 [26] , more epidermal keratinocytes were positive for nuclear p53 in the absence of Gclc , while expression of the cell cycle inhibitor p21 , a p53 target , was only mildly increased ( S6B and S6C Fig ) . Since p53 is activated in response to DNA damage , we performed immunofluorescence staining with an antibody against phosphorylated histone 2A ( γH2AX ) , which recognizes DNA double strand breaks . Indeed , koG mice had significantly elevated levels of γH2AX positive cells in the epidermis . A mild increase was also seen in koN mice , but the loss of Nrf2 did not further aggravate the DNA damage that occurred in the absence of Gclc ( Fig 6B ) . Ultrastructural analysis of the epidermis from koG mice revealed that most of the apoptotic cells were located in the basal layer ( Fig 6C ) . In addition , mitochondria , which depend on cytosolic GSH production for their integrity , were severely condensed , reflecting their damage ( Fig 6D ) . This abnormality was particularly obvious in apoptotic keratinocytes ( Fig 6D , middle panel ) , but even detectable in pre-apoptotic cells with features resembling ferroptosis , an iron-dependent form of non-apoptotic cell death [27] ( Fig 6D , right panel ) . This likely results from oxidative stress as suggested by enhanced protein carbonylation , which reflects their oxidation state ( Fig 6E ) . Within the first 2–3 days after skin injury , the number of cleaved caspase-3 positive cells in the wound tongue was not significantly different between mice of both genotypes , but a strong increase was observed at day 5 post-injury in the wound epidermis of koG mice ( Fig 7A ) . This finding provides a likely explanation for the reduced area of the wound epidermis that we detected at this time point ( Fig 4E ) . Gclc-deficient wound keratinocytes also exhibited enhanced DNA double strand breaks ( Fig 7B ) , concomitant with increased levels of carbonylated proteins in 3-day wounds ( Fig 7C ) . Combined loss of Nrf2 and Gclc had no further effect on the wound healing process , and the percentage of wound closure as well as length and area of the wound epithelium were not affected in the double knockout mice at day 3 after wounding compared to control mice ( Fig 7D–7G ) . Similar to the situation in non-wounded skin , loss of Nrf2 did not affect proliferation and did not further increase the number of cleaved caspase-3 and γH2AX positive cells in the hyperproliferative wound epidermis ( Fig 7H–7J ) . To determine if DNA damage and apoptosis are direct consequences of GSH deficiency in keratinocytes , we analyzed primary keratinocytes during the first days after plating . Levels of ROS and RNS were significantly increased in Gclc-deficient keratinocytes ( Fig 8A and 8B ) , and additional loss of Nrf2 did not further enhance the intracellular ROS levels ( Fig 8C ) . Oxidative stress in these cells was further reflected by enhanced lipid peroxidation , which was detected with the lipid peroxidation sensor C11-BODIPY581/591 ( Fig 8D ) . The lack of Gclc caused a mild , but non-significant reduction in keratinocyte proliferation . The reduction was statistically significant for keratinocytes from the double knockout mice ( Fig 8E ) , further confirming that the keratinocyte hyperproliferation observed in vivo at 2M is not a cell autonomous effect , but rather a consequence of increased inflammation . The number of cleaved caspase-3 and γH2AX positive cells was significantly increased in cultures from koG mice compared to controls , but—like in the in vivo situation—there was no further increase in cells from double mutant mice ( Fig 8F and 8G ) . Therefore , DNA damage and the subsequent initiation of apoptosis are cell autonomous effects , which are directly triggered by the loss of GSH synthesis in keratinocytes and not amplified by loss of Nrf2 . Since we found a rapid decline in the number of Gclc-deficient keratinocytes upon culturing ( Fig 8H and 8I ) , we determined if these cells die exclusively from apoptosis , or if non-apoptotic forms of cell death are also involved as suggested by the ferroptosis features that we detected in the Gclc-deficient epidermis by ultrastructural analysis ( Fig 6D , right panel ) . For this purpose , Gclc-deficient primary keratinocytes and cells from control mice were incubated for 24 h with the pan-caspase inhibitor Z-VAD-FML ( Z-VAD ) , the necroptosis inhibitor necrostatin-1 ( Nec-1 ) , the ferroptosis inhibitor ferrostatin-1 ( Fer-1 ) or the autophagy inhibitor 3-methyladenine ( 3MA ) ( Fig 8H and 8J ) . None of these inhibitors affected the viability of cells from control mice ( Fig 8J , left panel ) . However , the progressive cell death of keratinocytes from Gclc-deficient mice was partially rescued by low concentrations of Z-VAD , confirming that the cells die at least in part via apoptosis . Moreover , there was an increase in cell viability in the presence of necrostatin-1 or ferrostatin-1 ( Fig 8J , right panel ) , indicating a contribution of necroptosis and ferroptosis to the cell death of koG primary keratinocytes . A more detailed ultrastructural analysis of the epidermis at 3W confirmed the presence of cells with signs of ferroptosis and also revealed cells with necroptosis-like features . This included dysmorphic mitochondria , as well as small mitochondria with increased membrane density and/or membrane accumulation , characteristic for ferroptosis ( Fig 8K left and middle panel; Fig 6D , right panel ) and nuclear condensation , severe vacuolization and autophagosome formation , characteristic for necroptosis ( Fig 8K , right panel ) . These findings demonstrate the in vivo relevance of the functional cell culture studies and further suggest that Gclc-deficiency initiates different cell death pathways . We next tested if other thiols can compensate at least in part for the loss of GSH in keratinocytes . An important candidate is free cysteine , which is mainly provided by the uptake of cystine through the cystine-glutamate exchange protein ( Slc7a11; xCT ) [28] and concomitant intracellular reduction to cysteine or by direct uptake through the Slc1a4 ( Asc ) transporter . Interestingly , a strong increase in Slc7a11 expression was observed in the epidermis and in cultured keratinocytes of koG mice ( Fig 9A ) , and a mild , but non-significant increase in Slc1a4 expression was seen in the epidermis ( S7A Fig ) . Slc7a11 is a known Nrf2 target gene [29] , and the increase in expression of this gene that occurred in the absence of Gclc was indeed partially rescued by loss of Nrf2 . Nevertheless , expression levels of Slc7a11 were still significantly elevated in koG/N mice compared to controls ( Fig 9A ) . Expression levels of Slc1a4 , which has not been described as an Nrf2 target , were not affected by the loss of Nrf2 only , but significantly reduced in the double knockout mice compared to koG mice ( S7A Fig ) . The intracellular reduction of cystine to cysteine requires GSH or potentially thioredoxin reductase ( Txnrd ) dependent systems [30–32] , and the GSH and Txn/Txnrd systems were shown to be partially redundant in embryonic stem cells , cancer cells and also in mouse liver [23 , 31 , 33] . Txn1 mRNA levels in the epidermis of young mice or in primary keratinocytes were not affected by the loss of Gclc ( Fig 9B ) , but a mild increase was seen in the epidermis of mice at the age of 2M ( S7B Fig ) . Txnrd1 expression was mildly reduced in koG mice , and the reduction was statistically significant in koG/N mice ( Fig 9C ) . However , the levels of this protein were similar in epidermal lysates from control and koG mice ( S7C and S7D Fig ) . The difference in Txnrd1 expression was no longer detectable at the age of 2M ( S7E Fig ) . Txnrd2 expression was not affected by the loss of Gclc , but a mild increase in Txn2 protein levels was observed at the age of 3W ( S7C and S7D Fig ) . To determine if the Slc7a11/Txn/Txnrd system compensates for the loss of Gclc , we treated primary keratinocytes from Gclc-deficient and control mice with chemical inhibitors of Slc7a11 ( sulfasalazine—SSZ ) or Txnrd ( auranofin—AUR ) for 24 h ( Fig 9D and 9E ) . While the viability of control cells was not or only mildly affected by these compounds , they caused a significant reduction in the number of viable Gclc-deficient keratinocytes ( Fig 9F ) . The same tendency was seen upon staining for cleaved caspase-3 ( S7F Fig ) . The detrimental effect of AUR on Gclc-deficient cells was verified in an alamarBlue survival assay ( S7G Fig ) . To exclude a general susceptibility of Gclc knockout keratinocytes to chemical inhibitors , we analyzed inhibitor-treated keratinocytes from wild-type mice . While neither inhibition of Txnrd1 by AUR nor GSH depletion by BSO alone affected survival of these cells , a combination of both inhibitors severely affected their viability ( Fig 9G ) , demonstrating that both systems have complementary protective functions in keratinocytes . These results provide insight into the roles of different antioxidant defense systems in keratinocytes and their orchestrated interplay in vitro and in vivo ( Fig 9H ) and led us to propose the following scenario: Loss of Gclc and subsequent glutathione deficiency in keratinocytes results in activation of the Nrf2 transcription factor as shown by the genetic approach in this study and by pharmacological GSH depletion [22] . However , in the absence of Gclc , Nrf2 can no longer activate GSH production , and various GSH-dependent Nrf2 targets are increased , but remain non-functional . The upregulation of Nrf2 target genes does not compensate for the loss of Gclc in koG mice as demonstrated by the lack of additional abnormalities in koG/N mice . By contrast , cystine , which is imported via the xCT transporter and intracellularly reduced to cysteine can partially compensate for the lack of GSH . Cysteine is incorporated into TXN , which can compensate for the lack of GSH in the reduction of cystine and as a ROS/RNS scavenger . Therefore , inhibition of the TXNRD pathway in Gclc-deficient keratinocytes causes massive cell death as shown in this study , whereas inhibition of either the GSH or the TXN pathway can be tolerated by keratinocytes in vitro and in vivo . The most obvious phenotype of the Gclc-deficient mice was the failure to gain weight after weaning . This is likely to result from impaired food uptake due to the severe hyperkeratosis in the forestomach . The deficit in weight gain may be further promoted by the progressive increase in TEWL . Malnutrition as the cause of cachexia and premature death in koG mice is further supported by their low blood glucose levels . By contrast , systemic effects are unlikely to contribute to the lack of weight gain and the reduced life expectancy since: ( i ) serum levels of Il-6 were below detection levels , ( ii ) expression of important cytokines , which could cause cachexia or other systemic abnormalities was not increased in the skin of the mutant mice , and ( iii ) Gclc expression was not affected in tissues where the K5 promoter is not active , such as liver and kidney . The epidermis of Gclc-deficient mice showed hyperkeratosis and reduced adhesiveness of the corneocytes , providing a likely explanation for the mildly enhanced TEWL . This increase was followed by an elevation in the number of dermal mast cells and epidermal γδ T cells , suggesting that the accumulation of these immune cells is a consequence of the barrier defect . Consistent with this assumption , an increase in mast cells and epidermal γδ T cells is frequently observed in mice with impaired barrier function [35] . The mild inflammation may be further promoted by the early onset of apoptotic and also non-apoptotic cell death in the epidermis . The latter had previously been demonstrated to result in cutaneous inflammation [36] . Mast cells and epidermal γδ T cells produce a variety of growth factors and cytokines [37 , 38] , providing a possible explanation for the keratinocyte hyperproliferation that we observed in Gclc-deficient mice upon aging . The cutaneous abnormalities in koG mice showed some similarities with the phenotype of mice lacking Gpx4 in keratinocytes , including cutaneous inflammation [39] . However , the inflammatory response was much milder , and the increase in dermal macrophages and neutrophils as well as the enhanced expression of various pro-inflammatory cytokines and of Ptgs2/Cox2 observed in Gpx4-mutant mice was not seen in koG mice . Furthermore , there was no increase in the viable part of the epidermis in koG mice . The milder phenotype may be explained by the fact that Gpx4 can also use cysteine or other thiols as substrates [40] . Gpx4-deficient mice exhibit major hair follicle abnormalities and they develop transient baldness [39] . Hair loss was also seen in Gclc-deficient mice , but it was restricted to a few areas . In addition , abnormal hair follicles developed in mice lacking both Gclc and Nrf2 , which were highly reminiscent to those observed in Gpx4-mutant mice . These findings suggest that loss of Nrf2 reduces the availability of other thiol substrates of Gpx4 , which may then become rate limiting in the rapidly growing hair follicle keratinocytes . Ultrastructural and molecular analysis of the epidermis from Gclc-deficient mice revealed a strong increase in the number of apoptotic and pre-apoptotic cells . This is likely to result from the severe ROS- and RNS-induced DNA and mitochondrial damage . In addition , it is possible that certain proteins involved in the control of apoptosis are glutathionylated in wild-type mice and that the loss of such posttranslational modifications in koG mice affects their functions . This should be determined in the future using proteomics and follow-up functional approaches . Our ultrastructural data combined with the functional in vitro studies strongly suggest that Gclc-deficient keratinocytes not only die from apoptosis , but that different forms of regulated necrosis are also involved , such as necroptosis and ferroptosis . The latter is consistent with an at least partial functional inhibition of Gpx4 in the absence of GSH , since Gpx4 was previously identified as a crucial regulator of ferroptotic cell death in tumor cells and kidney tubular cells [41 , 42] . Gclc-deficient keratinocytes proliferated normally in vivo , suggesting remarkable compensatory mechanisms in this cell type that are even sufficient in response to skin injury . We did not even observe an increase in apoptosis in Gclc-deficient mice during the early phase of wound healing , possibly due to the upregulation of various growth and survival factors in healing skin wounds [20] . This is different to the severe wound healing defect in rats after BSO-mediated depletion of GSH in the wound tissue [15] . It may well be that cells of the dermis/granulation tissue are more dependent on GSH than keratinocytes and/or that the cell death induced by the lack of GSH in the epidermis is compensated for by the high regenerative capacity of the epidermis . An important role of GSH in granulation tissue formation is supported by the early onset of senescence in fibroblasts lacking the Gcl modifier subunit [43] . Alternatively , long-term GSH deficiency may allow upregulation of compensatory mechanisms that cannot come in place upon acute depletion . Several lines of evidence suggested a key role of Nrf2 in the compensation of GSH deficiency: ( i ) Nrf2 target genes were upregulated in Gclc-deficient keratinocytes . This is in line with the induction of Nrf2 activity by GSH deficiency and the identification of Nrf2 as a functional adaptive response to GSH depletion in neuroblastoma cells and fibroblasts [22 , 44]; ( ii ) Nrf2 induces the expression of Slc7a11 [29] , the cystine transporter , which had rescued the death of Gclc-deficient embryonic stem cells upon forced overexpression [31]; ( iii ) hyperkeratosis was also observed in the epidermis and the hair follicle infundibulum of mice expressing a caNrf2 mutant in keratinocytes [25]; ( iv ) caNrf2-transgenic as well as koG mice had a defect in the epidermal barrier , most likely as a result of abnormal expression of Sprr2d , a major component of the cornified envelope [25] , and subsequent alterations in the expression of lipid biosynthesis enzymes such as Elovl3 [25]; and ( v ) activation of Nrf2 rescued the barrier defect in loricrin knockout mice and thus prevented postnatal lethality [45] . However , our genetic data revealed that Nrf2 is not acting as a back-up system to compensate for the lack of Gclc in keratinocytes . The most likely explanation is that any cytoprotective effect of Nrf2 is mediated via its strong induction of enzymes involved in GSH synthesis and recycling . In the absence of Gclc , this protective effect is no longer in place , and the upregulation of Nrf2 in Gclc-deficient cells can therefore not result in a functional rescue . However , activation of Nrf2 is likely to have a protective effect when GSH depletion is not the consequence of a loss of its biosynthesis enzymes . In this case , Nrf2 will promote their expression , resulting in restoration of normal GSH levels . While activation of Nrf2 is obviously not responsible for the relatively mild phenotype of koG mice , the upregulation of Slc7a11 that occurred at least in part in an Nrf2-independent manner , was more important , and pharmacological inhibition of this transporter induced death of Gclc-deficient keratinocytes . An even more striking result was obtained with a Txnrd inhibitor , which strongly reduced the viability of cultured Gclc-deficient keratinocytes and also promoted death of wild-type keratinocytes when applied together with a Gclc inhibitor . Therefore , the Txn/Txnrd system indeed compensates at least in part for the loss of GSH , most likely through the capacity to reduce the imported cystine . These results are consistent with findings obtained with embryonic stem cells or cancer cells , which demonstrated that loss of GSH can be compensated for by the Txn/Txnrd system and vice versa [23 , 31 , 46] . Importantly , we show here that this compensatory activity is relevant in a normal tissue in vivo without the need of forced overexpression of one component . Our results also highlight the remarkably diverse antioxidant capacity of keratinocytes , which allows them to survive in response to various insults and to maintain the epidermal barrier function , which guarantees whole body homeostasis even under stress conditions . The compensatory function of thioredoxin also provides an explanation for the resistance of epidermal keratinocytes to various anti-cancer drugs , of which many affect GSH metabolism [47] . This allows maintenance of skin integrity in the treated cancer patients . Finally , our results provide important insight into the interplay between different cellular antioxidant defense systems . Mice expressing Cre recombinase under control of the keratin 5 promoter ( K5Cre mice ) [19] were mated with mice harboring floxed alleles of the Gclc gene [34] and/or floxed alleles of the Nrf2 gene [48] . All mice were in C57Bl/6 genetic background . They were housed under optimal hygiene conditions and maintained according to Swiss animal protection guidelines . All experiments with animals were approved by the “Kantonales Veterinäramt Zürich” ( CH 32/2011 and ZH 247/2013 ) . The work was performed in strict accordance with the Schweizerisches Tierschutzgesetz ( Animal Welfare Act ) and the subordinate Tierschutzordnung ( Animal Welfare Ordinance ) and Tierversuchsverordnung ( Animal Experimentation Ordinance ) . Mice between P19 and P24 were anaesthetized by inhalation of 2% isoflurane . One full-thickness excisional wound , 4 mm in diameter , was made on each side of the dorsal midline by excising skin and panniculus carnosus . Mice were sacrificed at different time points after injury . For histological analysis , the complete wounds were excised and either fixed overnight in 95% ethanol/1% acetic acid or in 4% paraformaldehyde / phosphate buffered saline ( PBS ) followed by paraffin embedding , or directly frozen in tissue freezing medium ( Leica Microsystems , Heerbrugg , Switzerland ) . Sections ( 7 μm ) from the middle of the wounds were stained with H&E or used for immunofluorescence analysis . Morphometric analysis of different parameters of the wound healing process was performed using H&E- or immunofluorescence-stained sections as shown schematically in Fig 4A . Blood glucose levels were determined using a commercial blood glucose meter . Separation of epidermis from dermis was achieved either by heat shock treatment ( 30 s at 55–60°C followed by 1 min at 4°C , both in PBS ) , by incubation for 50–60 min at 37°C in 0 . 143% dispase/DMEM or by incubation in 0 . 8% trypsin/DMEM for 15–30 min at 37°C . For dispase and trypsin treatment the subcutaneous fat was gently scraped off with a scalpel prior to incubation . Isolated epidermis was either directly snap frozen and stored at -80°C , or homogenized and further processed . TEWL was determined using a Tewameter ( Courage and Khazaka Electronic GmbH , Cologne , Germany ) . The probe was placed on the dorsal back skin of shaved mice and measurements were performed for 30–50 consecutive counts on two different spots . Total RNA from tissue was isolated with Trizol followed by purification with the RNeasy Mini Kit , including on-column DNase treatment ( Qiagen , Hilden , Germany ) . Total RNA from cells was extracted directly with the RNeasy Mini Kit . cDNA was synthesized using the iScript kit ( Bio-Rad Laboratories , Hercules , CA ) . Relative gene expression was determined using the Roche LightCycler 480 SYBR Green system ( Roche , Rotkreuz , Switzerland ) . Primers used for qRT-PCR are shown in S1 Table . Keratinocytes were isolated from single mice as described previously [35] and cultured in a 7:5 mixture of keratinocyte serum-free medium ( Invitrogen/Life Technologies , Carlsbad , CA ) supplemented with 10 ng/ml EGF , 10−10 M cholera toxin and 100 U/ml penicillin/100 μg/ml streptomycin ( Sigma ) and of keratinocyte medium [49] . Plates were coated with collagen IV prior to seeding of the cells . For treatment with chemical inhibitors , primary keratinocytes were isolated from individual mice , cultured for 2 days , and incubated with the solvent DMSO ( equal amount as in inhibitor samples ) , 15 mM BSO ( Sigma ) , 250 μM SSZ ( Sigma ) , 75 nM AUR ( Sigma ) , 10 μM Z-VAD ( Enzo Life Sciences , Lausen , Switzerland ) , 1 μM Fer-1 ( Xcessbio , San Diego , CA ) , 20 μM Nec-1 ( Enzo ) , or 10 μM 3MA ( Sigma ) for 24 h . Viable cells were either counted or analyzed using the alamarBlue cell viability reagent as described by the manufacturer ( Invitrogen/Life Technologies ) . Frozen tissue was homogenized in T-PER tissue protein extraction reagent ( Pierce , Rockford , IL ) containing Complete Protease Inhibitor Cocktail ( Roche ) . Lysates were cleared by sonication and centrifugation ( 13 , 000 rpm , 30 min , 4°C ) , snap frozen , and stored at -80°C . The protein concentration was determined using the BCA Protein assay ( Pierce ) . Proteins were separated by SDS-PAGE and transferred onto nitrocellulose membranes . Antibodies used for Western blotting are listed in S2 Table . Oxidized proteins were detected using the OxyBlot assay kit ( Chemicon , Temecula , CA ) according to the manufacturer’s instructions . The method is based on the detection of protein carbonyl groups derivatized with 2 , 4-dinitrophenylhydrazine to convert carbonyl groups to dinitrophenylhydrazone derivatives . Derivatized protein samples were subjected to SDS-PAGE and subsequent Western blot analysis using an antibody against dinitrophenylhydrazone . After deparaffinization and rehydration or fixation with cold methanol ( in case of frozen sections ) , unspecific binding sites were blocked with PBS containing 3–12% BSA and 0 . 025% NP-40 for 1 h at room temperature , and then incubated overnight at 4°C with the primary antibodies ( see S3 Table ) diluted in the same buffer . If needed , antigen retrieval was performed prior to the blocking procedure by cooking in citrate buffer ( 1 h at 95°C ) . For immunohistochemistry , endogenous peroxidase activity was quenched with 3% H2O2 for 10 min prior to blocking . After three washes with PBST ( 1 x PBS/0 . 1% Tween 20 ) , slides were incubated at room temperature for 1 h with secondary antibodies and Hoechst ( 1 μg/ml ) as counter-stain , washed with PBST again and mounted with Mowiol ( Hoechst , Frankfurt , Germany ) . Sections were photographed using a Zeiss Imager . A1 microscope equipped with an Axiocam MRm camera and EC Plan-Neofluar objectives ( 10x/0 . 3 , 20x/0 . 5 ) . For data acquisition the Axiovision 4 . 6 software was used ( all from Carl Zeiss , GmbH , Oberkochen , Germany ) . Antibodies used for immunostaining are listed in S3 Table . After deparaffinization and rehydration , skin sections were stained with 0 . 5% toluidine blue , 0 . 5 N HCl , pH 2 . 3 for 30 min . After washing with distilled water , sections were dehydrated and mounted with Eukitt mounting medium ( Sigma ) . Stained mast cells appear violet or purple . Dermis and epidermis were separated as described above , further processed into single cell suspensions and stained as described previously [50] . Dyes and antibodies used for flow cytometry are listed in S4 Table . Fluorescence was directly measured by flow cytometry using the BD LSRFortessa ( BD Biosciences , San Jose , CA ) . Mice were lethally anesthetized with pentobarbital ( 700 mg/kg ) and perfused with 4% PFA in PBS . Skin samples were kept overnight in fixation solution , rinsed , and stored in PBS . After washing in 0 . 1 M cacodylate buffer pH 7 . 2 at 4°C , the specimens were treated with 2% OsO4 for 2 h . After washing , they were stained in 1% uranyl acetate , dehydrated and embedded in araldite resin . Ultra-thin sections ( 30–60 nm ) were processed with a diamond knife and placed on copper grids . Transmission electron microscopy was performed using a 902A electron microscope ( Zeiss , Oberkochen , Germany ) . Cells or heat shock isolated epidermis were lysed in 0 . 6% sulfosalicylic acid/0 . 1% Triton-X100 in phosphate buffer containing 5 mM EDTA . After centrifugation , total GSH/GSSG levels in the supernatant were determined using the enzymatic recycling method [51] . Levels of intracellular ROS and NO and extent of lipid peroxidation in primary murine keratinocytes were determined using H2DCF-DA ( Invitrogen/Life Technologies ) , DAF-FM-DA ( Sigma ) , or C11-BODIPY581/591 assays ( Invitrogen/Life Technologies ) , respectively . H2DCF-DA allows detection of intracellular H2O2 , but it also detects oxygen radicals [52] . DAF-FM-DA is a probe to detect NO , but it only works under aerobic conditions and it is likely to react with an oxidative product of NO , rather than with NO itself [53] . Cells were incubated for 30 min with 50 μM H2DCF-DA or 5 μM DAF-FM-DA , or for 2 h with 2 μM C11-BODIPY581/591 in cell culture medium at 37°C prior to detachment by trypsin . Fluorescence was directly measured by flow cytometry using the BD Accuri C6 ( BD Biosciences , San Jose , CA ) . Statistical analysis was performed using the Prism4 software ( GraphPad Software Inc , San Diego , CA ) . Significance was calculated with the Mann–Whitney U test for Non-Gaussian distribution or the Wilcoxon signed rank test . Log-rank test was used for the survival data .
The skin is frequently exposed to various challenges that cause oxidative stress , such as UV irradiation , exposure to toxic chemicals or mechanical injury . Therefore , keratinocytes -the major cell type of the outermost layer of our skin—need sophisticated antioxidant defense systems . However , the relevance of individual defense systems and their interaction in the cell are largely unknown . Here we studied the role of glutathione , the most abundant cellular antioxidant , in keratinocytes . We show that in the absence of the enzyme that catalyzes the rate-limiting step in glutathione biosynthesis , keratinocytes initiate a complex cell death program , resulting in reduced survival of these cells in culture and in mouse skin . Despite this , the epidermal structure was only mildly affected and the mutant mice were even able to heal full-thickness excisional skin wounds . We found that this is ensured by compensatory functions of another antioxidant defense system , allowing survival of keratinocytes in the absence of glutathione . These results therefore demonstrate a remarkable antioxidant defense capacity of keratinocytes that guarantees maintenance of the essential barrier of the skin and efficient wound repair .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "skin", "flow", "cytometry", "cell", "death", "keratinocytes", "medicine", "and", "health", "sciences", "integumentary", "system", "immunofluorescence", "staining", "cell", "processes", "epithelial", "cells", "dna", "damage", "epidermis", "dna", "research", "and", "analysis", "methods", "specimen", "preparation", "and", "treatment", "staining", "animal", "cells", "glutathione", "biological", "tissue", "spectrophotometry", "cytophotometry", "biochemistry", "peptides", "cell", "biology", "anatomy", "nucleic", "acids", "apoptosis", "genetics", "epithelium", "biology", "and", "life", "sciences", "cellular", "types", "antioxidants", "spectrum", "analysis", "techniques" ]
2016
A Glutathione-Nrf2-Thioredoxin Cross-Talk Ensures Keratinocyte Survival and Efficient Wound Repair
Hedgehog ( Hh ) signaling in vertebrates depends on primary cilia . Upon stimulation , Hh pathway components , including Gli transcription factors , accumulate at primary cilia to transduce the Hh signal , but the mechanisms underlying their ciliary targeting remains largely unknown . Here , we show that the PY-type nuclear localization signal ( PY-NLS ) /karyopherinβ2 ( Kapβ2 ) nuclear import system regulates Gli ciliary localization and Hh pathway activation . Mutating the PY-NLS in Gli or knockdown of Kapβ2 diminished Gli ciliary localization . Kapβ2 is required for the formation of Gli activator ( GliA ) in wild-type but not in Sufu mutant cells . Knockdown of Kapβ2 affected Hh signaling in zebrafish embryos , as well as in vitro cultured cerebellum granule neuron progenitors ( CGNPs ) and SmoM2-driven medulloblastoma cells . Furthermore , Kapβ2 depletion impaired the growth of cultured medulloblastoma cells , which was rescued by Gli overexpression . Interestingly , Kapβ2 is a transcriptional target of the Hh pathway , thus forming a positive feedback loop for Gli activation . Our study unravels the molecular mechanism and cellular machinery regulating Gli ciliary localization and identifies Kapβ2 as a critical regulator of the Hh pathway and a potential drug target for Hh-driven cancers . Cell–cell signaling often occurs in specialized subcellular compartments . One such cell signaling center is the primary cilium , which is a microtubule-based plasma membrane protrusion [1] . Primary cilia regulate many essential cellular processes , and their malfunction is attributed to numerous human disorders collectively called “ciliopathy” [2] . Recently , the primary cilium has been implicated in transducing extracellular signals , most notably , the Hedgehog ( Hh ) signal [1 , 3] . The Hh family of secreted proteins plays pivotal roles in both embryonic development and adult tissue homeostasis [4–6] . Deregulation of Hh signaling activity has been linked to numerous human diseases , including birth defects and cancer [5 , 7–9] . The Hh signal is transduced by the seven-transmembrane G-protein-coupled receptor ( GPCR ) -like protein Smoothened ( Smo ) , leading to activation of the latent Gli family of Zn-finger transcription factors . Both Smo and Gli are localized to primary cilia in response to Hh stimulation [10–14]; however , the mechanisms that target Hh pathway components to the primary cilia have remained poorly understood . Although ciliary localization of Smo and Gli proteins correlates with Hh pathway activation , definitive proof that ciliary localization of these and other pathway components is required for Hh signal transduction is still lacking . Indeed , a recent study revealed that Smo could activate the Hh signaling pathway in the absence of ciliary accumulation under certain conditions [15] . A ciliary localization signal has been identified in Smo; however , similar ciliary localization signals were not found in the Gli proteins [10] . A previous study suggested that nuclear localization signal ( NLS ) can function as a ciliary targeting signal for the kinesin-2 motor kinesin family member ( KIF ) 17 [16]; however , a recent study showed that deletion of the canonical NLS in Gli2 did not affect its ciliary localization [17] . In a previous study , we identified a noncanonical NLS called PY-type nuclear localization signal ( PY-NLS ) that matches the consensus: basic/hydrophobic motif-X7~12-R/K/H-X2~5-PY/L[18] , which is localized in the N-terminal region of the Gli family of transcription factors , including the Drosophila Gli homolog Cubitus interruptus ( Ci ) and vertebrate Gli1 , Gli2 , and Gli3 ( S1 Fig ) [19] . We found that the PY-NLS acts in conjunction with the canonical NLS ( a bipartite NLS ) localized in the Zn-finger domain to promote efficient Ci nuclear localization in Drosophila [19] . In the process of dissecting the function of PY-NLS and canonical NLS in regulating Gli proteins , we found that the canonical NLS in Gli plays a major role , whereas the PY-NLS a minor role in targeting Gli to the nucleus . Interestingly , mutating the PY-NLS but not the canonical NLS impaired Gli ciliary localization . The PY family of NLSs interacts with the karyopherin-β family member karyopherin-β2 ( Kap-β2; also known as Transportin 1 or importin β2 ) that transports PY-NLS-containing proteins to the nucleus [18] . Kapβ2 is required for the ciliary localization of retinitis pigmentosa 2 ( RP2 ) [20] . Here , we show that Kap-β2 is essential for Gli ciliary localization and activation . Inactivation of Kap-β2 inhibited Hh signal transduction in cultured mammalian cells , as well as in zebrafish embryos . Furthermore , Kap-β2 is essential for the growth of cultured cerebellum granule neuron precursors ( CGNPs ) as well as medulloblastoma cells driven by a smo oncogenic mutation ( SmoM2 ) . Interestingly , we find that Kap-β2 itself is a target of the Hh–Gli signaling pathway , suggesting that Kap-β2 and Hh–Gli forms a positive feedback loop to promote Gli ciliary localization and activation . To study the function of the PY-NLS in the Gli proteins , we generated full-length Gli2 and Gli3 lacking the PY-NLS ( Gli2mPY and Gli3mPY ) , as well as full-length Gli2 lacking the canonical NLS ( Gli2mNLS ) or lacking both the PY and canonical NLS ( Gli2m ( PY+NLS ) ) ( Fig 1A and 1B ) . When transfected into NIH3T3 cells , Myc-tagged wild type Gli2 ( Myc-Gli2WT ) localized predominantly to the nucleus ( Fig 1C and 1H ) and the majority of transfected cells ( > 80% ) contained ciliary Myc-Gli2WT signal ( Fig 1C and 1I ) . Mutating the canonical NLS ( Gli2mNLS ) greatly reduced Gli2 nuclear localization but did not affect its ciliary localization ( Fig 1D and 1H ) . By contrast , mutating the PY-NLS ( Myc-Gli2mPY ) only slightly reduced Gli2 nuclear localization but greatly impaired ciliary localization of Gli2 , as only about 20% of transfected cells contained weak Myc-Gli2mPY signal in primary cilia ( Fig 1E , 1F , 1H and 1I ) . Although Gli2m ( PY+NLS ) exhibited a more profound defect in its nuclear localization , its ciliary localization defect was similar to that of Myc-Gli2mPY ( Fig 1G–1I ) . Furthermore , Gli3mPY exhibited diminished ciliary localization similarly to Gli2mPY ( Fig 1J–1M ) . These observations suggest that the PY-NLS in Gli proteins has acquired a new function , i . e . , ciliary targeting of Gli , beyond its traditional role as a NLS . It has been proposed that ciliary translocation of Hh pathway components , including Gli proteins , is essential for Hh signal transduction leading to Gli activation [1 , 3] . However , many studies addressing the importance of ciliary localization of Gli in Hh signal transduction involved disruption of cilia structure or components involved in ciliary protein transport [21] [12 , 13 , 22]; as such , alternative explanation cannot be excluded . The ciliary localization defect associated with Gli2mPY provided us an opportunity to directly test whether ciliary localization of Gli2 is essential for its activation . To this end , we established NIH3T3 cell lines with endogenous Gli2 depleted by RNA interference ( RNAi ) targeting its 3′ untranslated region ( NIH3T3mGli2-shRNA ) and supplemented with or without the expression of exogenous Myc-Gli2WT or Myc-Gli2mPY at low levels using the lentiviral transfection system . Western blot analysis indicated that Myc-Gli2WT and Myc-Gli2mPY were expressed at levels slightly higher than that of the endogenous Gli2 ( Fig 2A ) . We found that Gli2 depletion diminished the expression of both Ptch1 and Gli1 , two sonic hedgehog ( Shh ) target genes , in response to SAG ( Fig 2B and 2C ) . SAG-stimulated expression of Ptch1 and Gli1 in NIH3T3mGli2-shRNA cells was fully restored by the expression of Myc-Gli2WT ( Fig 2B and 2C ) . By contrast , Myc-Gli2mPY only marginally restored the expression Shh target genes in NIH3T3mGli2-shRNA cells and exhibited approximately 20-fold less activity compared to Myc-Gli2WT ( Fig 2B and 2C ) . Fractionation experiments indicated that Myc-Gli2mPY only exhibited a slight reduction in its nuclear localization compared with Myc-Gli2WT ( Fig 2D ) , which cannot account for the large drop in Myc-Gli2mPY activity . On the other hand , ciliary localization of Myc-Gli2mPY was greatly diminished under both unstimulated and Hh-stimulated conditions compared to Myc-Gli2WT ( Fig 2E and 2F ) , which correlated with its diminished activity . In transient transfection experiments where both Myc-Gli2WT and Myc-Gli2mPY were overexpressed , Myc-Gli2mPY activated a Gli-luciferase ( Gli-luc ) reporter gene similar to Myc-Gli2WT ( Fig 2G ) , consistent with a previous finding that an excessive amount of Gli2 can activate Hh pathway independent of the primary cilia [13] . On the other hand , both Myc-Gli2mNLS and Myc-Gli2m ( PY+NLS ) exhibited much-reduced ability in activating the Gli-luc reporter gene ( Fig 2G ) , consistent with their intrinsic nuclear localization defect ( Fig 1H ) . These observations suggest that the defect in Hh signaling activity associated with Myc-Gli2mPY is most likely due to its ciliary localization defect . Hence , the PY-NLS–mediated ciliary localization of Gli2 is required for its activation in response to the upstream signal . These results are consistent with a recent study showing that a nonciliary Gli2 deletion mutant failed to respond to Hh when knocked into the endogenous locus [23] . We have previously shown that the PY-NLS motif from Gli2 , Gli3 , or Ci , when fused to a heterologous protein such as LacZ , is sufficient to confer nuclear translocation of the heterologous protein ( S1A and S1B Fig ) [19] . However , the PY-NLS was unable to confer ciliary localization when fused to LacZ ( S1B Fig ) . Consistent with the notion that the PY-NLS is insufficient for ciliary targeting , Ci was not localized to the primary cilium when expressed in NIH3T3 cells . To determine additional domain ( s ) in Gli2 required for its ciliary localization , we generated several Ci-Gli2 chimeric proteins ( Fig 3A ) . Replacing the Gli2 sequence C-terminal to the PY-NLS motif with that of Ci ( GliNCiC ) nearly abolished the ciliary localization of the chimeric protein ( Fig 3B and 3C ) . On the other hand , replacing the Ci sequence C-terminal to the PY-NLS motif with that of Gli2 ( CiNGliC ) conferred ciliary localization of the chimeric protein , and mutating the PY-NLS in CiNGliC ( CiNGliCmPY ) diminished its ciliary localization ( Fig 3A–3C ) . These results suggest that the PY-NLS in Ci is a functional ciliary targeting signal but the Gli sequence C-terminal to its PY-NLS is also required for Gli ciliary localization . To narrow down the C-terminal domain required for Gli ciliary localization , we generated a set of C-terminally deleted CiNGliC variants ( Fig 3D ) . Deletion to amino acid ( aa ) 1080 ( CiN-GliC1080 ) reduced , whereas deletion to aa 874 ( CiN-GliC874 ) or aa 735 ( CiN-GliC735 ) abolished ciliary localization ( Fig 3E and 3F ) , suggesting the sequence between aa 874 and aa 1080 of Gli2 is critical for its ciliary localization . Consistent with this , 2 recent studies also identified sequence overlapping with this region as critical for Gli2 ciliary localization [17 , 23] . The PY family of NLSs physically interacts with Kapβ2 , which carries the PY-NLS–containing cargoes into the nucleus [18] . Indeed , an N-terminal fragment of Ci , Ci1-440 ( CiN ) , interacted with the Drosophila Kapβ2 , Trn , in a manner depending on the PY-NLS , and depletion of Trn diminished CiN nuclear localization in S2 cells [19] . To determine whether Kapβ2 is required for ciliary localization of Gli proteins , we depleted mouse karyopherinβ2 ( mKapβ2 ) from NIH3T3 by establishing cell lines stably expressing 2 independent short hairpin RNAs ( shRNAs ) ( mKapβ2-shRNA1 and mKapβ2-shRNA2 ) that targeted different regions of mKapβ2 . We found that both mKapβ2-shRNA1 and mKapβ2-shRNA2 effectively knocked down endogenous mKapβ2 and diminished ciliary localization of endogenous Gli2 , both in the absence and in the presence of Hh stimulation ( Fig 4A and 4B; S2A and S2B Fig ) . Because mKapβ2-shRNA2 knocked down mKapβ2 with a higher efficiency than mKapβ2-shRNA1 ( S3A Fig ) , we focused on this RNAi line for the rest of the study and simply referred it to as mKapβ2-shRNA unless mentioned otherwise . The ciliary localization defect of Gli2 in mKapβ2-shRNA–expressing cells was completely rescued by transfection with a human karyopherinβ2 ( hKapβ2 ) that is resistant to mKapβ2-shRNA ( Fig 4A and 4B ) . mKapβ2-shRNA also diminished ciliary-localized Myc-Gli3 and Flag-Gli1 , and this defect was completely rescued by coexpressing hKapβ2 ( S2C–S2F Fig ) . The observations that 2 independent mKapβ2-shRNAs can both inhibit Gli ciliary localization and that such defect can be rescued by hKapβ2 rule out off-target effect and demonstrate that Kapβ2 is essential for ciliary localization of Gli proteins . To determine whether Kapβ2 is required for Smo ciliary translocation , NIH3T3 cells expressing mKapβ2-shRNA or green fluorescent protein ( GFP ) -shRNA were infected with lentivirus expressing a Myc-tagged form of Smo ( Myc-Smo ) and treated with or without Hh . We found that Hh stimulated ciliary accumulation of Myc-Smo in both control and mKapβ2 depleted cells ( S3A and S3B Fig ) , suggesting that Kapβ2 is not required for Smo ciliary localization . In addition , ciliary localization of a yellow fluorescent protein ( YFP ) -tagged KIF7 , a Hh pathway component that is also required for cilium tip organization [24–27] , was not affected by Kapβ2 knockdown ( S3C Fig ) . Taken together , these observations suggest that the ciliary localization defect of Gli proteins caused by Kapβ2 knockdown is not likely due to a general defect in ciliary structure and/or transport but rather to a specific role of Kapβ2 in the regulation of Gli ciliary localization . The observation that Kapβ2 is required for Gli ciliary localization prompted us to examine whether depletion of Kapβ2 affects Hh target gene expression . We found that Kapβ2 RNAi diminished the Gli-luc reporter activity , as well as the expression of endogenous Gli1 and Ptch1 induced by Hh , and that this defect was fully rescued by the expression of hKapβ2 ( Fig 4C–4E ) . In addition , introducing Myc-Gli2 into mKapβ2-shRNA cells by lentiviral infection restored the expression of Hh target genes ( Fig 4C–4E ) , suggesting that down-regulation of Hh target genes in Kapβ2-depleted cells is due to diminished Gli activator activity . We then examined the relationship between Kapβ2 and Sufu , a major negative regulator of the mammalian Hh pathway that binds and inhibits Gli proteins [13 , 28] . Previous studies suggest that the constitutive Gli activity in Sufu mutant cells is cilium-independent [13 , 29] . We reasoned that if Kapβ2 promotes Hh pathway activity by targeting Gli proteins to primary cilia , then removing Sufu should bypass the requirement of Kapβ2 for Hh pathway activation . To test this , we depleted mKapβ2 from Sufu-/- mouse embryonic fibroblast ( MEF ) cells by viral infection of mKapβ2-shRNA . As a control , we reintroduced mSufu into Sufu-/- MEF cells to generate Sufu+ MEFs ( Sufu-/- + mSufu ) . We found that Kapβ2 RNAi diminished Hh-induced Gli-luc activity in Sufu+ MEF cells ( Fig 4F ) ; however , the high basal as well as Hh-induced Gli-luc activity was not affected by Kapβ2 depletion in Sufu-/- MEFs ( Fig 4F ) , suggesting that Kapβ2 is not required for the ectopic Gli activity in the Sufu mutant background . Of note , Hh-induced Gli-luc activity was relatively low in Sufu-/- MEFs compared with Sufu+ MEFs because Gli proteins are unstable in the absence of Sufu[13] . The observation that the Hh signaling defect caused by Kapβ2 depletion was fully rescued by overexpression of Gli2 or removal of Sufu strongly implies that the signaling defect is mainly due to lack of Gli activation rather than a general defect caused by Kapβ2 inactivation . To determine whether Kapβ2 regulates Hh pathway in vivo , we turned to zebrafish and inactivated Kapβ2 during embryonic development by injecting morpholinos ( MOs ) into 1-cell stage embryos ( see Materials and methods ) . We found that Kapβ2 MO resulted in reduced expression of the Hh target gene Eng and “U-shaped” somites similar to Smo MO ( Fig 5A–5F ) , phenotypes indicative of Hh signaling defects[30] . In addition , Kapβ2 MO led to reduced expression of multiple Hh target genes , including Ptch2 , Hhip , Nkx2 . 2b , and Gli1 as determined by in situ hybridization and/or real-time PCR ( Fig 5G–5J ) . Under these circumstances , Kapβ2 MO did not affect the expression of the Wnt target gene Axin2 ( Fig 3J ) , consistent with a previous report that the primary cilium is not required for Wnt signaling in zebrafish [31] . During cerebellum development from the late embryonic stage to the early postnatal stage , Hh signaling is required for the proliferation and expansion of the CGNPs in the external granule layer ( EGL ) [32–34] . To determine whether Kapβ2 regulates Shh signaling in CGNPs that are essential for their proliferation , we inactivated Kapβ2 using RNAi ( mKapβ2 shRNA1 or mKapβ2 shRNAi2 ) in Shh-treated mouse CGNP cultures . We also depleted both mouse Gli1 and Gli2 by RNAi ( mGli1/2 shRNA ) in Shh-treated CGNP cultures in parallel experiments . We found that knockdown of Kapβ2 in CGNPs significantly impaired the expression of Shh target genes such as Gli1 , Ptch1 , Cyclin D1 ( CycD1 ) , and N-Myc and inhibited the proliferation of CGNPs as determined by bromodeoxyuridine ( BrdU ) incorporation in a manner similar to Gli1/2 depletion ( Fig 6A–6C ) [35] . Introducing exogenous mGli2 into Kapβ2-depleted CGNPs restored Shh target gene expression above the basal levels and rescued the proliferation defect of Kapβ2 depleted CGNPs ( Fig 6A–6C ) . Consistent with Kapβ2 regulating Shh pathway activity through Gli ciliary localization , ciliary localization of endogenous Gli2 was diminished in Kapβ2-depleted mouse CGNPs ( Fig 6D–6E ) . Mutations leading to constitutively active Shh signaling cause Shh-subtype medulloblastoma , whose progression requires the active pathway activity [36–39] . Therefore , we determined whether Kapβ2 is required for the growth of medulloblastoma driven by SmoM2 , which resulted in constitutive activation of Smo [37 , 40] . SmoM2-induced medulloblastoma cells were cultured in vitro for a short period of time and infected with lentiviruses expressing shRNAs for Kapβ2 or Gli1/2 [35] . Similar to Gli1/2 RNAi , Kapβ2 knockdown in SmoM2-induced medulloblastoma cells diminished the expression of Shh target genes , including Gli1 , Ptch1 , CycD1 , and N-Myc ( Fig 6F ) , leading to growth inhibition of the medulloblastoma cells as indicated by a cell survival assay ( Fig 6G ) . Moreover , inhibition of Shh target gene expression and medulloblastoma growth were rescued by lentiviral infection of mGli2 into Kapβ2-depleted medulloblastoma cells ( Fig 6F–6G ) . Taken together , these results suggest that Kapβ2-meidated Gli activation is required for Shh-stimulated CGNP proliferation and SmoM2-driven medulloblastoma cell growth . We noticed that Kapβ2 was up-regulated in the mouse model of medulloblastoma driven by SmoM2 ( S4A Fig ) . In addition , Kapβ2 expression level is significantly higher in the Shh subgroup of medulloblastoma compared with the Wnt subgroup of medulloblastoma from clinical samples ( S4B Fig ) . We found that depletion of Gli1/2 from Shh-stimulated CGNPs or SmoM2-driven medulloblastoma cells ( Smo MO ) in zebrafish embryos down-regulated the expression of Kapβ2 ( Fig 6A and 6F , S4C Fig ) , suggesting that Kapβ2 is a Shh-responsive gene . As a further support to this notion , NIH3T3 cells treated with SAG exhibited elevated Kapβ2 mRNA levels and protein abundance ( Fig 7A and 7B ) . Depletion of mGli2 from NIH3T3 cells abolished SAG-stimulated Kapβ2 up-regulation , which was rescued by lentiviral infection of exogenous mGli2 ( Fig 7C ) , suggesting that Smo activation induces Kapβ2 expression through Gli . Inspection of the mKapβ2 gene locus identified 3 Gli protein binding consensus sites within a 2 . 5-kb sequence upstream from the transcription start site ( Fig 7D ) . Furthermore , DNA fragments containing these sites were enriched in Myc-Gli2 chromatin immunoprecipitation ( CHIP ) in response to SAG stimulation ( Fig 7D ) , suggesting that mKapβ2 is a Gli target gene . The primary cilium is required for the formation of both GliR and GliA [12 , 21]; however , we found that Kapβ2 depletion in NIH3T3 cells did not significantly affect the proteolytic processing of either Gli2 or Gli3 to generate GliR ( Fig 7E and 7E′ ) . Furthermore , the ability of SAG to inhibit GliR formation was not affected by Kapβ2 depletion ( Fig 7E and 7E′ ) . These results imply that ciliary localization of Gli2/3 might not be absolutely required for their processing . Therefore , the Shh signaling deficiency caused by Kapβ2 depletion is most likely due to a defect in the conversion of GliFL to GliA . Previous studies suggested that Shh stimulates nuclear translocation of Gli2FL [21] and that nuclear Gli2FL exhibited increased phosphorylation and decreased association with Sufu [41–43] , all of which may contribute to Gli2 activation . Consistent with Kapβ2 regulating Gli2 activation , we found that Kapβ2 depletion in NIH3T3 cells attenuated SAG-induced nuclear translocation of endogenous Gli2FL ( Fig 7F ) abolished SAG-stimulated phosphorylation of nuclear Gli2FL as indicated by the mobility shift on SDS-PAGE ( Fig 7G ) . In control cells , SAG induced dissociation of Gli2FL from Sufu in the nuclear fraction as measured by co-immunoprecipitation assay ( Fig 7H , lanes 3–4 ) [42]; however , such dissociation was diminished in Kapβ2-depleted cells ( Fig 7H , lanes 7–8 ) . The sustained binding of Sufu to Gli2FL in Kapβ2-depleted cells may explain why Gli2 cannot be activated in response to Shh in these cells . Although it has been long thought that ciliary localization of Gli is essential for its activation and subsequent translocation into the nucleus , how Gli proteins are targeted to the primary cilia has remained a mystery . In this study , we identified the PY-NLS located in the N-terminal region of Gli proteins as a ciliary localization signal ( CLS ) whose mutation diminished Gli ciliary localization . We found that Kapβ2 , which normally brings PY–NLS-containing cargoes into the nucleus , is essential for Gli ciliary localization and activation . Interestingly , Kapβ2 itself is a Gli target gene , suggesting a positive feedback regulation of Gli activation ( Fig 8 ) . We provided further evidence that Kapβ2-mediated ciliary localization of Gli is essential for Hh pathway activity in multiple physiologically relevant contexts and depletion of Kapβ2 affected the growth of SmoM2-driven medulloblastoma cells cultured in vitro , suggesting that blockage of Kapβ2-mediated Gli ciliary localization may serve as a new strategy to treat Hh-driven cancers such as basal cell carcinoma ( BCC ) and medulloblastoma . Members of the Gli family of transcription factors , including Drosophila Ci , contain a conserved PY-NLS in their N-terminal region and a canonical bipartite NLS in their Zn-finger DNA-binding domains . Whereas both NLSs contribute to the regulation of Ci nuclear localization [19] , the PY-NLS has only a minor role in Gli nuclear targeting but instead plays a critical role in Gli ciliary localization ( Fig 1 ) . Hence , the PY-NLS has been co-opted by the Gli transcription factors for their ciliary targeting . Consistent with our findings that the PY-NLS/ Kapβ2 nuclear transport system regulates Gli ciliary localization and Hh pathway activity , a recent study revealed that blocking Kapβ2/Imp-β2 activity using a blocking peptide , M9M , also attenuated Gli2 ciliary localization without apparently affecting cilia length [44] . However , these authors failed to reveal a role of the PY-NLS in Gli2 ciliary localization , likely because the PY-NLS motif was insufficiently mutated in their study [44] . Several other studies attempted to map the ciliary localization signals for Gli proteins [17 , 45] . Consistent with the PY-NLS in Gli ciliary targeting , several N-terminal deletion mutants with the PY-NLS motif removed exhibited significantly reduced ciliary localization . In addition , these studies also revealed that the C-terminal region of Gli proteins is important for their ciliary localization [17 , 45] . The PY-NLS/Kapβ2 nuclear import system has been implicated in the ciliary targeting of several other proteins , including Kif17 and RP2 protein [16 , 20] . In addition , depletion of importinβ2/Kapβ2 inhibited ciliary localization of RP2 [20] . Hence , the PY-NLS/Kapβ2 system is likely to play a broad role in the ciliary targeting of nonmembrane proteins . By contrast , Kapβ2 depletion did not affect ciliary localization of Smo ( S3 Fig ) , suggesting that Smo ciliary localization is regulated by a distinct mechanism . Indeed , Smo ciliary localization is regulated by a CLS that is different from the PY-NLS [10] , as well as by a Septin family protein , Septin2 , localized at the base of the ciliary membrane [46] . In addition , Smo ciliary localization is regulated by phosphorylation and sumoylation of its C-terminal intracellular tail [14 , 47] , as well as by its association with β-arrestin and BBSome [48 , 49] . The observations that a nuclear transport system is involved in ciliary targeting and many nucleoporins ( Nups ) are localized at ciliary base and that the ciliary base has a diffusion barrier similar to that of nuclear pores led to the proposal that the ciliary base may contain a nuclear pore-like structure [50–52] . However , other studies revealed that the ciliary diffusion barrier is mechanistically distinct from those of the nuclear pore complex [53 , 54] . Furthermore , a recent study using super-resolution imaging revealed that Nup188 forms 2 barrel-like structures with dimensions and organization incompatible with a nuclear pore complex ( NPC ) -like ring , arguing against Nups forming a ciliary pore complex at ciliary bases [55 , 56] . Therefore , it is possible that Nubs form a different type of diffusion barrier at ciliary bases , which could explain why canonical NLS does not function as a ciliary targeting signal . It is also possible that the ciliary bases may contain additional diffusion barriers that need to be overcome through other mechanisms . In this regard , it is important to note that the C-terminal half of Gli2 also contains a sequence essential for its ciliary localization ( Fig 3 ) [17 , 23] . It is possible that this sequence may bind a factor or factors that assist Gli proteins in crossing the diffusion barrier at the ciliary base . Alternatively , it may bind a motor protein that actively transports Gli proteins to the ciliary base . Indeed , a previous study revealed that a cytoplasmic microtubule network is required for ciliary targeting of Gli2 [21] . Furthermore , fusing the CLS from Kif17 to a nonciliary kinesin , the Kinesin-1 subunit kinesin heavy chain ( KHC ) , resulted in the ciliary localization of KHC , whereas deletion of the motor domain from Kif17 resulted in the nuclear localization of the truncated Kif17 , suggesting that motor domain may act in conjunction with CLS to target Kif17 for ciliary localization [16] . A recent study revealed that the heterotrimeric kinesin-2 complex containing Kif3A/Kif3B/KAP3 interacts with and regulates Gli protein function; however , this motor complex binds Gli2 and Gli3 through the N-terminal but not the C-terminal region of the Gli proteins [57] . Identification and characterization of protein ( s ) interacting with the C-terminal region of Gli2 will provide further insight into the ciliary targeting mechanism for Gli proteins . Our study also provides new insight into the role of ciliary localization of Gli in the regulation of Gli activity . Disrupting primary cilia affected the formation of both GliR and GliA , leading to ectopic but low levels of Hh signaling activity [12 , 22] . It has been shown that protein kinase A ( PKA ) holoenzyme , as well as proteasome , are enriched at the ciliary base [58 , 59] . In the resting state , a cilium-localized GPCR , Gpr161 , increases the local production of cAMP and thus PKA catalytic activity at the ciliary base , which is essential for Gli processing [60] . Upon Hh stimulation , Gpr161 moves out of the cilia , leading to reduced local production of cAMP and PKA activity , and subsequent inhibition of Gli processing [60] . Similarly , disrupting the primary cilia may abolish the local production of cAMP and PKA catalytic activity , resulting in inhibition of Gli processing . Furthermore , inhibition of PKA activity within cilia using a cilium-tethered PKA inhibitor also impaired Gli processing , leading to the proposal that Gli proteins need to enter the cilia in order to be phosphorylated and processed [61] . Here , we showed that compromised ciliary localization of Gli2 and Gli3 due to Kapβ2 knockdown did not significantly affect their proteolytic processing into GliR ( Fig 7E and 7E′ ) . It is possible that residual ciliary localization of Gli2/3 may account for their normal processing . Alternatively , Gli2/3 can be phosphorylated and processed at the ciliary base in response to a local gradient of PKA activity . By contrast , ciliary localization of Gli proteins is critical for GliA formation in response to Hh . In Kapβ2-depleted cells , both phosphorylation and nuclear import of Gli2FL were compromised , and more Gli2 FL was bound by Sufu in the nucleus ( Fig 7F–7H ) , which could explain the diminished GliA activity ( Fig 4C–4E ) . We propose that ciliary localization of Gli2 in the presence of Hh allows it to be modified ( phosphorylated , for example ) and converted into GliA that can escape the inhibition imposed by Sufu . In Sufu-/- cells , however , Gli2 is constitutively active and its ciliary localization is no longer required for its activation , which explains why Kapβ2 depletion has no effect on GliA in Sufu-/- MEFs ( Fig 4F ) . Aberrant Hh pathway activity has been implicated in many types of cancer , including BCC and medulloblastoma , and small molecule Smo inhibitors have been used to treat Hh-driven cancers [62] . However , patients treated with Smo inhibitors often acquired resistance due to mutations that block drug binding [63 , 64] . Our finding that Kapβ2 depletion affects Hh signaling downstream of Smo makes it a potential therapeutic target for the treatment of Smo-inhibitor–resistant cancers . Wild-type mouse Gli2/3 and their mutants ( mPY , mNLS , and mPY+mNLS ) , as well as mGli2-Ci chimera proteins ( GliNCiC , CiNGliC and CiNGliCmPY ) , are tagged with 6 copies of Myc epitope at their N-termini and subcloned into the pcDNA3 . 1 ( + ) vector , digested with EcoRI and XhoI . For lentiviral protein-expressing constructs , N-terminally 6XMyc-tagged mouse Gli2 ( wild type [WT] and mPY ) and mouse Smo; C-terminally Flag-tagged mouse Sufu; and human Kapβ2 were cloned into the FUXW vector digested with XbaI and BamHI . Flag-lacZ ( FZ ) and FZ-Gli2PY were described previously [19] . Flag-Gli1 construct was described previously [13] . All the constructs were made by using Gibson Assembly Master Mix ( NEB E2611S ) . NIH3T3 cells were cultured in DMEM containing 10% Bovine Calf Serum ( ATCC ) . HEK 393T and Sufu -/- MEF cells were cultured in DMEM with 10% Fetal Bovine Serum ( FBS ) ( Sigma Aldrich ) . Shh treatment was done by serum starvation for 24 hours ( 0 . 5% Bovine Calf Serum ) , then adding a recombinant mouse Shh N-terminal fragment ( R&D Systems #464-SH ) at 1 ug/ml overnight . Smoothened agonist SAG ( Sigma Aldrich ) treatment was done at 200 ng/ml for 8–12 hours . Cell transfections were performed using PolyJet in vitro DNA Transfection Reagent ( SignaGen ) following manufacturer’s instruction . Immunoprecipitation , immunostaining , and western blot analyses were carried out as described previously [47] . The antibodies used in this study are listed as follows: anti-Myc ( 9E10 , Santa Cruz Biotechnology ) , anti-β-galactosidase ( A11132 , Life Technologies ) , anti-acetylated tubulin ( T7451 , Sigma Aldrich ) , anti-mGli2 ( AF3635 , R&D Systems ) , anti-mGli3 ( AF3690 , R&D Systems ) , anti-mKapβ2 ( Ab10303 , Abcam ) , anti-α-tubulin ( T9026 , Sigma Aldrich ) , anti-Histone3 ( Ab1791 , Abcam ) , and anti-BrdU ( B8434 , Sigma Aldrich ) . 8XGliBS luciferase ( Gli-luc ) assay was performed using Dual Luciferase Reporter Assay System ( Promega ) and FLUOstar OPTIMA ( BMGLABTCH ) . Cells were seeded in 6-well plates and transfected with 8XGliBS reporter and pRL-TK at a 4:1 ratio ( as well as other plasmids , if necessary ) . The day after transfection , cells were treated with Shh or SAG , subjective to lysis and determined for luciferase activity . For quantitative reverse transcription PCR ( RT-qPCR ) with cell samples , total RNA was extracted from cell using RNeasy Plus Mini Kit ( Qiagen ) , cDNA was synthesized with iScript cDNA synthesis kit ( Bio-rad ) , and qPCR was performed using iQ SYBR Green System ( Bio-rad ) and a Bio-rad CFX96 real-time PCR system . Glyceraldehyde 3-phosphate dehydrogenase ( GADPH ) expression level was used a normalization control . The primer pairs used were as follows: GAPDH , GTGGTGAAGCAGGCATCTGA ( F ) and GCCATGTAGGCCATGAGGTC ( R ) Gli1 , GTGCACGTTTGAAGGCTGTC ( F ) and GAGTGGGTCCGATTCTGGTG ( R ) Gli2 , AGCTCCACACACCCGCAACA ( F ) and TGCAGCTGGCTCAGCATCGT ( R ) mKapβ2 , ATCTTGGTCTTGGGTTCTCTG ( F ) and CCTTCAGCATGTTCCATTTCTG ( R ) Ptch1 , GAAGCCACAGAAAACCCTGTC ( F ) and GCCGCAAGCCTTCTCTAGG ( R ) CyclinD1 , AGACCTGTGCGCCCTCCGTA ( F ) and CAGCTGCAGGCGGCTCTTCT ( R ) N-Myc , GTCTTCCCCTTCCCGGTGAAC ( F ) and CAAGGTATCCTCTCCGGAGGTGC ( R ) For RT-qPCR with zebrafish samples , about 50 zebrafish embryos at 24 hours post-fixation ( hpf ) were lysed to extract the RNA by TRIzol ( Invitrogen ) following the standard protocol . 1 μg of RNA was used for reverse transcription by ReverTra Ace qPCR RT Master Mix with gDNA Remover ( TOYOBO ) . Real-time PCR was performed on ABI Fast7500 with Maxima SYBR Green qPCR Master Mix ( Thermo Fisher Scientific ) . The primer pairs used were as follows: mKapβ2 , GAACGCAAGCCCTAATGCTG ( F ) and GCATATGTGGAAGGAGACGG ( R ) fkd4 , GCTTCACTGAACCATTTCGCA ( F ) and CTGAGCCATAATACATCTCGCTG ( R ) hhip , CTTACGAGCCAAGTGTGAACTG ( F ) and TGCTGTCTTTCTCACCGTCC ( R ) Gli1 , TTCTTGGTTTACTTGAAGGCAGAG ( F ) and GCTCATTATTGATGTGATGCACC ( R ) nkx2 . 2b , CAAATATCCAGTGCCGTCAGC ( F ) and CGCTCTAACTCAAAGGTTTGAGTC ( R ) ptch2 , TCCTCCTTATGAGTCCCAAACAG ( F ) and CATGAACAACCTCAACAAACTTCC ( R ) axin2 , CTTAAACCTGCCACTAAGACCT ( F ) and CATTCTCCTCCATAGCCGTC ( R ) GAPDH , CATCACAGCAACACAGAAGACC ( F ) and ACCAGTAAGCTTGCCATTGAG ( R ) HEK293T cells were seeded and transfected with psPAX2 and VSVG , along with pLKO . 1-puro ( for shRNA lentivirus ) or FUXW ( for protein expressing lentivirus ) . After 48 hours , virus-containing culture media was collected , filtered , and centrifuged at 20 , 000 g for 2 hours; the resultant precipitant was resuspended in a small volume of culture medium and stored at −80°C for future use . Mission shRNA plasmids against eGFP ( control ) , mGli2 ( TRCN0000219066 ) , and mKapβ2 ( TRCN0000295632 and TRCN0000295586 ) were purchased from Sigma Aldrich . The mGli1 shRNA plasmid was a kind gift from Dr . Jiang Wu’s lab . Myc-tagged WT and PY mutant mGli2 , mSmo , Flag tagged human Kapβ2 were subcloned into FUXW vector under the control of a ubiquitin promoter . NIH3T3 cells treated with vehicle or SAG were crosslinked with paraformaldehyde for 15 minutes at room temperature with agitation . After quenching , cells were lysed , sonicated , centrifuged , and immunoprecipitated with anti-Myc antibody . Precipitated DNA was purified and subjective to real-time PCR . The primer pairs used were as follows: S1 , CTTCCAAGACCCGGGTTTCTC ( F ) and AATAATGGTAATGAAGAGAG ( R ) S2 , CCCTCTGAACCATTTTCCCAG ( F ) and AGCTTTCATTGTAGAGTAGAG ( R ) S3 , CGAGACAGGATTTCTCTGTGT ( F ) and TTTAGGCAGGGCATGGTGGCG ( R ) C1 , GAGGAAGGTTTACATTAAATTG ( F ) and GAGAAACTTTGTCTCTATCA ( R ) Primary CGNP cells were dissociated from P3–P4 mice and cultured in DMEM/F12 medium containing 25 mM KCl , N2 supplement ( Invitrogen ) , and 10% FBS ( Sigma Aldrich ) . Shh-conditioned media derived from Shh-CM 293T cells was added in the above culture medium at a 1:20 ratio [35] . For primary medulloblastoma cell culture , tumor cells from SmoM2 , CAG-creER mice [37 , 40] with spontaneously occurring medulloblastoma were dissociated and cultured in the same medium as above except for Shh-conditioned media . Corresponding lentiviruses were added to the culture medium for the above 2 primary cells immediately after seeding and were maintained for 3 days . BrdU was applied 2 hours before immunostaining , and viable cell number was determined by CellTiter-Glo Luminescent Cell Viability Assay Kit ( Promega ) . All experimental procedures were approved by the local IACUC animal research committee ( University of Texas Southwestern Medical Center , protocol: APN2009-0018 ) and complied with NIH guidelines ( PHS Animal Welfare Assurance D16-00296 [A3472-01] ) . Extra care was taken of animals that suffered from medulloblastoma . Antisense MOs ( Gene Tools ) were microinjected into 1-cell stage embryos according to the standard protocols . A 4-nl volume of mixed MOs was injected at the concentration of 0 . 075 mM Kapβ2-MO1 and either 0 . 15 mM Kapβ2-MO2 or 0 . 15 mM Smo MO . MO sequences used were Kapβ2-MO1 ( 5′-CCATGCTGTATCGGGCTTCTCTTAC-3′ ) , Kapβ2-MO2 ( 5′-TCGGGTTTCCACTGGCACTCCATC-3′ ) , Smo-MO ( 5′-CTGGGCAGATGAGACTGGATGATTA-3′ ) , and standard control MO . Zebrafish embryos of the AB strain were obtained from the Zebrafish Core Facility at the Shanghai Institute of Biochemistry and Cell Biology . Whole mount in situ hybridization of zebrafish embryos was performed according to standard protocols [65] . Immunostaining of zebrafish embryos was performed as previously described [66] . In brief , Zebrafish embryos were fixed for 3 hours at room temperature in 4% formaldehyde and stored in methanol at −20°C overnight . Staining was performed in PBStwA ( PBStw + 1% BSA ) using anti-Engrailed ( Developmental Studies Hybridoma Bank ) and F59 anti-Myosin heavy chain antibodies ( Santa Cruz ) . Images of zebrafish embryos were acquired under a confocal microscope ( LAS SP5 ) using a 20×/0 . 7 NA objective ( Leica ) at room temperature .
The secreted Hedgehog ( Hh ) protein plays an evolutionarily conserved role in both embryonic development and adult tissue homeostasis . Malfunction of Hh signaling activity contributes to a wide range of human diseases , including birth defects and cancer . Hh signaling in vertebrates critically depends on the primary cilium , a microtubule-based plasma membrane protrusion present on the surface of most mammalian cells . Upon ligand stimulation , Hh pathway components , including the seven-transmembrane protein Smoothened ( Smo ) and Gli transcription factors , accumulate at primary cilia to transduce the Hh signal , but the mechanisms underlying their ciliary targeting are still poorly understood . Here , we discover that the PY-type nuclear localization signal ( PY-NLS ) and the nuclear import factor karyopherinβ2 ( Kapβ2 ) regulate Gli ciliary localization and Hh pathway activity . Mutating the PY-NLS in Gli or knockdown of Kapβ2 diminished Gli ciliary localization without affecting Smo ciliary accumulation in response to Hh . Kapβ2 regulates the formation of the active form of Gli , which is required for proper Hh signaling in zebrafish embryos and cultured cerebellum granule neuron progenitors ( CGNPs ) . Kapβ2 depletion impaired the growth of medulloblastoma cells driven by an oncogenic form of Smo . Finally , Kapβ2 is a transcriptional target of the Hh pathway , forming a positive feedback loop to promote Gli activation . Our study reveals the molecular mechanism underlying the regulation of Gli ciliary targeting and identifies Kapβ2 as a potential cancer drug target .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "medicine", "and", "health", "sciences", "gene", "regulation", "regulatory", "proteins", "blastomas", "cancers", "and", "neoplasms", "vertebrates", "dna-binding", "proteins", "animals", "oncology", "animal", "models", "osteichthyes", "developmental", "biology", "model", "organisms", "experimental", "organism", "systems", "transcription", "factors", "embryos", "cellular", "structures", "and", "organelles", "research", "and", "analysis", "methods", "specimen", "preparation", "and", "treatment", "embryology", "medulloblastoma", "staining", "fishes", "proteins", "gene", "expression", "hedgehog", "signaling", "biochemistry", "signal", "transduction", "zebrafish", "immunostaining", "cell", "biology", "cilia", "genetics", "biology", "and", "life", "sciences", "cell", "signaling", "organisms" ]
2017
Regulation of Gli ciliary localization and Hedgehog signaling by the PY-NLS/karyopherin-β2 nuclear import system
Complications of scabies and impetigo such as glomerulonephritis and invasive bacterial infection in Australian Aboriginal children remain significant problems and the overall global burden of disease attributable to these skin infections remains high despite the availability of effective treatment . We hypothesised that one factor contributing to this high burden is that skin infection is under-recognised and hence under-treated , in settings where prevalence is high . We conducted a prospective , cross-sectional study to assess the burden of scabies , impetigo , tinea and pediculosis in children admitted to two regional Australian hospitals from October 2015 to January 2016 . A retrospective chart review of patients admitted in November 2014 ( mid-point of the prospective data collection in the preceding year ) was performed . Prevalence of documented skin infection was compared in the prospective and retrospective population to assess clinician recognition and treatment of skin infections . 158 patients with median age 3 . 6 years , 74% Aboriginal , were prospectively recruited . 77 patient records were retrospectively reviewed . Scabies ( 8 . 2% vs 0 . 0% , OR N/A , p = 0 . 006 ) and impetigo ( 49 . 4% vs 19 . 5% , OR 4 . 0 ( 95% confidence interval [CI 2 . 1–7 . 7 ) were more prevalent in the prospective analysis . Skin examination was only documented in 45 . 5% of cases in the retrospective review . Patients in the prospective analysis were more likely to be prescribed specific treatment for skin infection compared with those in the retrospective review ( 31 . 6% vs 5 . 2% , OR 8 . 5 ( 95% CI 2 . 9–24 . 4 ) . Scabies and impetigo infections are under-recognised and hence under-treated by clinicians . Improving the recognition and treatment of skin infections by clinicians is a priority to reduce the high burden of skin infection and subsequent sequelae in paediatric populations where scabies and impetigo are endemic . Skin infections including scabies , impetigo , tinea and pediculosis are common in children , with high prevalence in developing countries and marginalised populations within developed countries[1–4] . It is estimated that 162 million children in low and low-middle income countries have active impetigo at any one time[1] . Similarly , scabies is very common in tropical environments particularly amongst children with population prevalence in excess of 10% in many Asian , Pacific Island and Central and South American countries[2] . Community based skin infection prevalence studies from Aboriginal populations in northern Australia demonstrate some of the highest prevalence rates of scabies and impetigo in the world[5 , 6] . The high burden of skin infections is challenging in the primary health care setting , whilst the serious sequelae of skin infections predominantly affect hospitalised patients . The burden of these sequelae of skin infections is greatest where the prevalence is high[7–9] . Impetigo and secondarily infected scabies lesions may be complicated by invasive bacterial infections including cellulitis , skeletal infection and bacteraemia[10–13] . Immune complications of impetigo are important in tropical regions where Streptococcus pyogenes ( Group A Streptococcus or GAS ) is the predominant pathogen[4 , 7 , 14] . In endemic settings most cases of acute post streptococcal glomerulonephritis ( APSGN ) are preceded by impetigo[15] and scabies infestation has been shown to be associated with renal disease[16] . There is also a plausible link between S . pyogenes skin infection and acute rheumatic fever ( ARF ) and rheumatic heart disease[17] . There are effective and relatively well tolerated treatments for skin infections , yet the burden of disease appears to be increasing or at least stable in endemic settings[18–20] . Translation of these evidence-based treatments depends on the successful recognition and diagnosis of skin infection by clinicians . We hypothesised that under-recognition due to the ‘normalisation’ of skin infection by clinicians contributes to under-treatment and the perpetuation of skin infection and subsequent sequelae in endemic settings . Normalisation is a term to describe that in contexts of high burden , but not life-threatening disease , clinicians may not specifically diagnose or treat scabies , impetigo , pediculosis or tinea when a patient presents to a health care provider for a reason other than skin infection because these infections are so common they are regarded as normal and are thus ignored or forgotten . The term normalisation has been used previously in the Australian[21–23] and international[24] literature to describe this hypothesized phenomenon in regions with endemic skin infection . Clinician under-recognition of scabies was suggested in the findings of one previous study in a population with high prevalence of scabies[25] but thus far normalisation of impetigo has not been demonstrated in the clinical setting . To test our hypothesis , we designed this study to prospectively assess prevalence of skin infection and to assess recognition by comparing this with the documented prevalence in a retrospective case note review . Participation in the study was voluntary and verbal and written informed consent was sought from each participant’s parent or appropriate guardian and where appropriate , ( i . e . in children >7yo ) assent was obtained . Ethics approval was granted by the Western Australian Country Health Service Research Ethics Committee ( project number 2015:11 ) and the Western Australian Aboriginal Health Ethics Committee ( project number 635 ) . The study protocol was finalised only after consultation with the Kimberley Aboriginal Health Planning Forum Environmental Health and Research subcommittees as well as local Aboriginal Medical Services . We performed a prospective , cross-sectional study to ascertain prevalence of skin infection and compared this with a retrospective , cross-sectional study to assess recognition of skin infection by health professionals . In the prospective arm , patients were opportunistically recruited from two regional hospitals during the period from October 2015 to January 2016 . Data for the retrospective review were obtained from the medical records of all patients admitted to the two paediatric wards in November 2014 at both centers . The retrospective data collection was limited to a one-month period that was the mid-point in the prospective data collection period for feasibility . This retrospective data capture provided the same season and likely admission profile as the prospective study . All children and adolescents ( aged <16 years ) admitted to Broome Hospital ( a 36 bed facility with 8 paediatric inpatient beds ) and Hedland Health Campus ( a 55 bed facility with 8 paediatric inpatient beds ) during the study period were eligible for participation in the prospective study . These two hospitals provide the regional paediatric services for the Kimberley and Pilbara regions respectively , covering a total catchment of greater than 900 000 km2 in the north of the state of Western Australia . In combination , these units admit around 1500 paediatric patients annually[26] servicing a total paediatric population of over 20 000 [27] . The study was conducted during the tropical “wet season” when temperatures are on average 33–36°C respectively and rainfall and humidity are high[27] . The population of the Kimberley region is 37 , 000 of whom 40% are Aboriginal[27] The population of the Pilbara is 62 , 000 of whom 12% are Aboriginal[27] . Patients were recruited by the site coordinator ( DY , AA ) at the two sites . An attempt to approach all admitted patients was made by the respective site coordinators and individuals were approached to participate regardless of the reason for admission , co-morbidities , ethnicity , language spoken , address or gender . Individuals were excluded if the individual or the parent / carer did not assent or consent to participation or if there was no parent / carer available to provide consent . All participants in the prospective arm of the project underwent assessment including: All purulent or crusted skin lesions were swabbed and sent for microscopy , culture and antibiotic susceptibility testing according to standardized methods . All samples were delivered to the local microbiology laboratory and subsequently sent to a tertiary laboratory ( over 2500km away ) for processing . In the retrospective review of medical records age , ethnicity , locality of residence , number of household members , primary reason for admission , history of skin infection ( including complications and comorbidities ) , documentation of skin infection on physical examination and treatment recommendations were recorded . Pathology records were reviewed for each patient and microbiology of skin lesions was recorded where applicable . All data were initially recorded onto standard case report forms and subsequently entered onto a secure online database ( REDCap Software–Version 6 . 10 . 12 ) . Ethnicity was self-reported or as recorded in the medical record as Aboriginal and/or Torres Strait Islander ( ATSI ) , Pacific Islander / Maori , Caucasian or other . Locality was assessed and classified for each participant as a local town ( resident in Broome or Port Hedland ) , another regional town ( within the region but outside of Broome and Port Hedland ) or a remote Aboriginal community . By the Australian Standard Geographical Classification ( ASGC ) for remoteness , Broome , Port Hedland and Karratha are considered remote and the remainder of the Kimberley and Pilbara are considered very remote[28] . Remote Aboriginal communities are defined areas inhabited by Aboriginal people with housing and infrastructure that is managed on a community basis[29] . Whilst nearly all are connected to essential services , disruptions are commonplace with 38% , 85% and 49% of communities reporting disruptions to water supply , electricity and sewage disposal respectively in 2001[29] . Access to health services is often limited with 74% of communities 100km or further from the nearest hospital and only 12% with a local doctor resident in the community[29] . Skin infection was defined as scabies , impetigo , tinea corporis , tinea capitis and/or pediculosis . A standard diagnostic guideline with clinical and photographic definitions of each condition was used as a reference tool in the prospective assessment of skin infection[30] . Scabies , a parasitic infection of the skin was diagnosed in the presence of pruritic papules in a typical distribution; classically in the web spaces , hands , feet and other moist areas . Impetigo is a bacterial infection of the superficial skin . Clinical detection ranges from active purulent or crusted lesions to resolving flat , dry lesions . Tinea infections were diagnosed based on well-demarcated areas of scale with a raised edge and itch . Pediculosis was diagnosed if either the live lice or nits attached to strands of hair were visualized . Secondary bacterial infection of parasitic or fungal lesions was diagnosed in the presence of pus or a crust . Cellulitis and abscess were not included in this assessment . Each condition was diagnosed clinically by the site’s study coordinator ( a paediatric clinician ) and treatment was prescribed according to local guidelines[31] . The primary objective was to compare the prevalence of skin infection in the prospective study with the documented prevalence in the retrospective review . Secondary objectives were to compare the frequency of treatment prescribed for skin infections between the prospective and the retrospective groups , to assess the local microbiology of impetigo in the prospective group and to assess age , admission reason , remoteness , overcrowding and ethnicity as potential risk factors for skin infection in the prospective study . The demographic details of patients and microbiology of impetigo lesions were reported for each group using descriptive statistics . Prevalence of each of the skin infections ( scabies , impetigo , tinea , and pediculosis ) in the prospective and retrospective cohort was determined . Odds ratios comparing frequency of each skin infection and frequency of treatment prescribed in the prospective and retrospective cohorts were calculated using logistic regression . Univariate analysis of associations between skin infection and age , admission reason , remoteness , overcrowding and ethnicity respectively was performed using logistic regression . Comparison of categorical data was conducted using logistic regression , Pearson’s Chi-square test or Fisher’s exact test ( where 0 events occurred in one or more groups ) . P-values of <0 . 05 were considered to indicate statistical significance . All statistical analysis was performed using SPSS statistics version 23 . 0 . 0 . 0 ( Armonk , NY: IBM Corp . ) . One hundred and fifty-eight patients were included in the prospective assessment; 102 from Broome and 56 from Port Hedland . This was 43 . 8% of those admitted during the period ( Fig 1 ) . No patients who were approached to participate refused to consent . Seventy-seven patient records were reviewed in the retrospective arm; 46 from Broome and 31 from Port Hedland . The demographic characteristics including age , gender , ethnicity and area of residence along with the primary reason for admission were similar between the prospective and retrospective cohorts ( Table 1 ) . In the prospectively assessed group median age was 3 . 6 years ( interquartile range [IQR] 0 . 9–7 . 4 ) , 74 . 1% were of Aboriginal ethnicity and 25 . 3% were from a remote Aboriginal community . The most common reason for admission was respiratory illness ( 34 . 2% prospective , 28 . 6% retrospective ) . Conditions that may complicate skin infection including APSGN , ARF , skeletal infections and soft-tissue infections accounted for almost one-quarter of admissions ( 24 . 1% prospective , 20 . 8% retrospective ) . Less than 20% of patients in the prospective analysis reported receiving specific treatment for skin infection in the twelve months prior to admission; 13 . 9% of patients had received treatment for scabies , 18 . 4% for impetigo and 13 . 9% for pediculosis . Prevalence of skin infection was high in the prospectively assessed group with 53 . 2% of patients diagnosed with one or more skin infections . Scabies was diagnosed in 8 . 2% ( 95% confidence interval [CI] 3 . 9–12 . 6 ) . Impetigo was present in 49 . 4% ( 95%CI 41 . 5–57 . 3% ) of participants , with crusted or purulent lesions identified in 27 . 8% ( 95% CI 20 . 8–34 . 9% ) tinea was identified in in 8 . 2% ( 95% CI 3 . 9–12 . 6% ) and pediculosis in 14 . 6% ( 95% CI 9 . 0–20 . 1% ) . The recognition of skin infection was four-fold greater in the prospective assessment compared with the retrospective review; odds ratio ( OR ) 4 . 0 ( 95% CI 2 . 2–7 . 5 ) ( Table 2 ) . Skin infection was diagnosed in 22 . 1% of patients in the retrospective review and notably 54 . 5% did not have any skin examination findings documented anywhere in the case notes . The prevalence of scabies ( 8 . 2% vs 0 . 0%; OR N/A ( p = 0 . 006 ) ) , impetigo ( 49 . 4% vs 19 . 5%; OR 4 . 0 ( 2 . 1–7 . 7 ) ) and pediculosis ( 14 . 6% vs 1 . 3%; OR 13 . 0 ( 1 . 7–97 . 8 ) ) respectively were significantly higher in the prospective assessment compared with the retrospective review . Prevalence of tinea was not significantly higher in the prospective assessment ( 8 . 2% vs 2 . 6%; OR 3 . 4 ( 0 . 7–15 . 3 ) ) Specific treatments for scabies , impetigo , tinea and/or pediculosis were prescribed eight times more frequently in the prospective assessment ( 31 . 6% vs 5 . 2%; OR 8 . 5 ( 95% CI 2 . 9–24 . 4 ) ) ( Table 3 ) . Antibiotics were the most commonly prescribed treatment and significantly more patients in the prospective analysis received antibiotics for skin infection ( 27 . 8% vs 14 . 3%; OR 2 . 3 ( 1 . 1–4 . 8 ) ) . No patients received treatment for scabies or tinea in the retrospective group while all patients diagnosed in the prospective assessment received treatment . Environmental health measures were implemented in 8 . 2% of the prospective cases compared with none in the retrospective review ( p = 0 . 006 ) . Although skin infection recognition was higher in the prospective arm , the communication of this finding was poor . In a subsequent review , only 64 . 6% ( 31 of 48 ) of children who received treatment for skin infection in Broome in the prospective study had this documented in the discharge letter . Household overcrowding , Aboriginal ethnicity , older age ( >5yo ) and residence in a remote community were all associated with an increased odds of skin infection in the prospectively assessed group ( Table 4 ) . Scabies , impetigo and pediculosis were all significantly associated with Aboriginal ethnicity and household overcrowding . Increased age was associated with increased prevalence of impetigo and pediculosis whilst prevalence of scabies and tinea was similar between age groups ( Table 5 ) . Children aged >5y were 3 times more likely to have a condition complicating skin infection ( APSGN , ARF , bone and joint infection and soft tissue infection ) as the primary admission diagnosis compared with those <5y age; OR 3 . 2 ( 95%CI 1 . 5–6 . 9 ) . Where the reason for admission was a condition associated with or complicating skin infection the prevalence of impetigo was significantly higher compared with admission for other reasons ( Table 6 ) . Despite this difference , skin infection was still common amongst those admitted for reasons not directly associated with or complicating skin infection with 40 . 5% ( 95% CI 31 . 6–49 . 4% ) of these patients having any skin infection: scabies in 6 . 6% ( 95% CI 2 . 1–11 . 1% ) , impetigo in 35 . 5% ( 95% CI 26 . 9–44 . 2% ) , crusted/purulent impetigo in 13 . 2% ( 95% CI 7 . 1–19 . 4% ) , tinea capitis / corporis in 5 . 8% ( 95% CI 1 . 6–10 . 0% ) and pediculosis in 9 . 9% ( 95% CI 4 . 5–15 . 3% ) . Bacterial swabs were collected from 41/ 44 ( 93 . 2% ) participants with crusted and purulent impetigo lesions in the prospective assessment . An organism was isolated in 37/41 ( 91% ) . Staphylococcus aureus ( 30/37 , 81% of swabs ) and Streptococcus pyogenes ( 18/41 , 44% ) were the predominant pathogens and co-infection ( 15/41 , 37% ) was common ( Fig 2 ) . Of the S . aureus isolates 13 ( 39% ) were methicillin resistant ( MRSA ) . All S . aureus isolates were susceptible to co-trimoxazole ( SXT ) . 90% of methicillin susceptible S . aureus ( MSSA ) and 77% of MRSA isolates were susceptible to clindamycin . All S . pyogenes were susceptible to penicillin . Susceptibility of S . pyogenes to SXT is not routinely tested in our laboratory . Our findings demonstrate that under-recognition of skin infections is clearly an important problem; consequentially specific treatment for skin infections is not offered by clinicians . Previous studies have confirmed that under-recognition of scabies occurs in industrialised [32] and resource limited settings [25] due to the absence of diagnostic tests . In a cross-sectional study of a population dwelling in a slum in Brazil , Heukelbach et al found that despite an estimated community prevalence of scabies of 8 . 8% , doctors at the health care centre failed to diagnose any cases of scabies amongst the 260 patients who presented for other reasons during the study period[25] . Hong et al demonstrated that time constraints and Emergency Department ( ED ) overcrowding were potential factors contributing to the missed diagnosis of scabies in patients admitted to a tertiary hospital in Taiwan where the diagnosis was missed by the ED physician in 65% ( 72 of 111 ) of cases[32] . Although under-recognition of scabies has been previously described , this is the first comparative study to demonstrate the under-recognition by clinicians of impetigo along with scabies and pediculosis in a region of high skin infection prevalence . It is plausible that under-recognition and normalisation of skin infection contribute to the ongoing burden of skin infection in many endemic settings around the world and the findings of this study have significant implications in the context of the global burden of skin infections . The implications of under-recognition of skin infection are manifold . The significant individual complications of scabies , pediculosis and impetigo are well documented[3 , 4 , 7–9 , 17 , 18] . Scabies , impetigo and pediculosis are highly transmissible and the assessment and treatment of household members is recommended as important public health control measures to prevent onward transmission and re-infection[33 , 34] . In failing to treat children and their family members for skin infections during a hospital admission , clinicians may miss the opportunity to prevent serious individual complications , perpetuate the cycle of ongoing transmission within communities and possibly render other patients at risk by failing to implement appropriate infection control measures . The prevalence of skin infection is high in this region as demonstrated in our prospective assessment with over half of all children having at least one form of skin infection . Limited data exists regarding prevalence of skin infection in the Kimberley and Pilbara region although other studies in regional Western and Northern Australia have found similarly high rates[5 , 6 , 35] . This high prevalence in our study supports our hypothesis that the under-recognition of skin infection is not a product of lack of familiarity with skin infection but rather that clinicians may ‘normalise’ skin infection because it is pervasive . S . aureus was the most common pathogen in impetigo lesions in our study with S . pyogenes implicated in less than half of cases . In previous studies S . pyogenes has been demonstrated as the predominant pathogen in impetigo in tropical regions where co-infection with S . aureus is also common[14] . The yield of S . pyogenes culture may have been reduced in our study due to the processing of samples which were sent to a tertiary laboratory over 2500km away for plating . S . pyogenes requires rigorous temperature and humidity controls to prevent deterioration[36] . Our results also reflect the increasing importance of community acquired MRSA as a pathogen in the Australian setting with almost 50% of S . aureus demonstrating methicillin resistance , as has been apparent in recent times[11] . Clearly other broad factors including the social determinants of health and patient access to health services significantly contribute to the persistent high burden of skin infection and complications in this setting . Overcrowding , poor access to water and poverty have been associated with scabies and impetigo[1 , 2 , 9 , 37] , and indeed in our prospective analysis those patients from overcrowded households and remote Aboriginal communities had significantly increased odds of skin infection . As evidenced in the industrialisation of tropical countries such as Singapore , improvements in housing along with better access to quality healthcare can significantly impact on the burden of skin infection complications such as post-streptococcal glomerulonephritis[38] . It is reasonable to conceive that skin infection is also under-recognised outside of the hospital setting . This is compounded by the poor communication of diagnosis and treatment of skin infections documented by hospital staff on discharge back to primary care providers . Despite the high prevalence of skin infection in our population , few children had received specific treatment for impetigo in the preceding twelve months . This speaks to the likely ‘normalisation’ of skin sores amongst patients and families as well as under-treatment of skin infection in primary health care and community clinics . Strategies to improve recognition of and awareness of the complications of skin infection and the importance of treatment should consider primary health care workers , community workers , teachers , environmental health providers as well as children and their families . This study has several limitations . Firstly , we were not able to recruit all of the eligible patients during the study period due to the availability of study staff and clinical commitments at other sites . Although recruitment was opportunistic , all children admitted to the ward were approached to participate when the study site doctor was present in order to achieve a representative sample . Secondly , in the prospective assessment , the diagnosis of skin infection was made clinically . In order to limit possible bias due to the reliance on clinical judgement , a diagnostic guide with clear clinical definitions was used as a reference tool in all cases[30] . Thirdly , although there were no major changes to public health policy in the region during the study period , the period encompassing the retrospective and prospective data collection was concurrent with an ongoing APSGN outbreak in the Kimberley region dating from the end of 2013[39] with an ongoing public health response from mid-2014 including the formation of the Kimberley Skin Health Regional Partnership in September 2014[40] and the revision of the Kimberley Aboriginal Medical Services Council’s skin infection treatment protocol in December 2014[31] . The heightened awareness of the importance of skin health at a regional level during late 2014 , as evident in the public health response , could potentially have increased the recognition of skin infection during the retrospective data collection period and the coordinated public health response led to a documented decrease in the community prevalence of scabies between December 2014 and May 2015[41] . Despite these potential influences our study still found that skin infection was less likely to be diagnosed and treated in the retrospective period ( November 2014 ) compared with the prospective data collection period . Finally , by virtue of the study design the assessment of clinician recognition of skin infection was performed retrospectively . Although it is plausible that clinicians did in fact recognise skin infection but did not document this , specific treatment for skin infection was prescribed far less frequently in the retrospective analysis supporting the finding of clinician under-recognition . Notwithstanding the limitations of this study the findings have significant implications for policy and future research . As the diagnosis of skin infections in endemic settings remains predominantly clinical , the training of health care providers is vital in improving recognition . Strategies which potentially overcome the difficulties associated with the diagnosis and treatment of individual patients such as community dermatology[42–44] and mass drug administration[45] should be considered . Specific training of health workers has been shown to improve recognition and treatment of skin infection in resource-poor settings[46] . The use of integrated algorithms for the management of skin infection in health clinics has also demonstrated promise as a strategy to improve diagnosis of skin infection[47 , 48] . Improvements in the accessibility to and availability of appropriate existing diagnostic tools such as dermatoscopy in resource limited settings should occur in parallel with further research exploring novel , practical diagnostic techniques[49 , 50] . Community dermatology has demonstrated promise as an effective and affordable strategy in addressing common skin conditions including infections in low resource settings by addressing skin disease at a community level[42–44] . This approach encompasses several strategies including the training of community health care workers to recognize and treat skin disease , public health measures to address the determinants of skin disease , the education of community members and the prioritization of conditions to tackle based on accurate epidemiological data and simplifying their treatment[51] . Furthermore , the use of mass drug administration to target scabies has shown promise in populations with endemic disease; this strategy may allow circumvention of some of the challenges around clinical under-recognition and normalization of skin infection in selected settings[45] . Other factors outside of lack of skills and training likely contribute to the under-recognition of skin infection and warrant further investigation and intervention . Identifying barriers to clinician diagnosis and treatment of skin infection and exploring reasons for the ‘normalisation’ of skin infection through well-designed qualitative research is vital . Measuring potential under-recognition of skin infection at a patient and community level and exploring factors that contribute should be a focus of future studies . Certainly the phenomenon of normalisation has been described at the community level[21 , 24] and may present a major barrier to health seeking and access to appropriate treatment in resource limited settings with endemic disease[25 , 52] . It follows that any strategies to improve recognition and treatment of skin infection must consider and partner with the members of the communities which are affected[21] . Moreover , ongoing efforts to address the social determinants which lead to the disproportionate load borne by people of Aboriginal ethnicity , particularly those living in remote communities , remain of great importance[8 , 21] . On a broader scale , skin infections are neglected at a global level with regard to prioritizing funding and policy development despite causing significant morbidity and mortality in resource-limited settings[53] . Our findings of under-recognition and under-treatment of skin infection in the clinical setting highlight some of the difficulties with addressing these conditions in disadvantaged populations and affirms the ongoing need for advocacy and a coordinated global approach to tackle common skin infections such as scabies and impetigo[1 , 9] . Skin infections are under-recognised by clinicians and this leads to suboptimal treatment and likely contributes to the significant ongoing burden of sequelae . There are many factors which contribute to the challenge of addressing the problem of skin infections and improving clinician recognition and treatment of skin infections is a priority .
Scabies and impetigo are common skin infections in children across the developing world as well as in disadvantaged populations living in developed countries . In previous studies including Australian Aboriginal and Pacific Islander children the rates of impetigo and scabies were amongst the highest described worldwide . The complications of these skin conditions include invasive bacterial infection , chronic kidney disease and potentially chronic heart disease and thus the burden of sequelae is significant . There are simple therapies which are efficacious in treating scabies and impetigo yet there has been little progress in reducing the burden of complications in endemic settings . We demonstrate in this study that scabies and impetigo , in a region with high prevalence of these conditions , are often not recognised by clinicians and appropriate treatment is not prescribed as a result of this . This is likely because clinicians ‘normalise’ skin infection where it is highly prevalent and therefore do not offer therapy unless specifically asked . The findings of this study have significant implication for health policy in regions with high prevalence of scabies and impetigo where focus should be put on improving health care worker recognition and awareness as well as exploring alternative strategies to individual case management of skin infection . Moreover future research should be directed at exploring the barriers to clinician recognition and treatment of these conditions and assessing specific strategies to ameliorate these .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion", "Conclusion" ]
[ "dermatology", "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "pathogens", "tropical", "diseases", "microbiology", "parasitic", "diseases", "streptococcus", "pyogenes", "skin", "infections", "signs", "and", "symptoms", "ectoparasitic", "infections", "sexually", "transmitted", "diseases", "neglected", "tropical", "diseases", "fungal", "diseases", "bacteria", "bacterial", "pathogens", "infectious", "diseases", "pediculosis", "medical", "microbiology", "streptococcus", "scabies", "lesions", "microbial", "pathogens", "tinea", "diagnostic", "medicine", "group", "a", "streptococci", "biology", "and", "life", "sciences", "soft", "tissue", "infections", "organisms" ]
2017
Are scabies and impetigo “normalised”? A cross-sectional comparative study of hospitalised children in northern Australia assessing clinical recognition and treatment of skin infections
Separase is best known for its function in sister chromatid separation at the metaphase-anaphase transition . It also has a role in centriole disengagement in late mitosis/G1 . To gain insight into the activity of separase at centrosomes , we developed two separase activity sensors: mCherry-Scc1 ( 142-467 ) -ΔNLS-eGFP-PACT and mCherry-kendrin ( 2059-2398 ) -eGFP-PACT . Both localize to the centrosomes and enabled us to monitor local separase activity at the centrosome in real time . Both centrosomal sensors were cleaved by separase before anaphase onset , earlier than the corresponding H2B-mCherry-Scc1 ( 142-467 ) -eGFP sensor at chromosomes . This indicates that substrate cleavage by separase is not synchronous in the cells . Depletion of the proteins astrin or Aki1 , which have been described as inhibitors of centrosomal separase , did not led to a significant activation of separase at centrosomes , emphasizing the importance of direct separase activity measurements at the centrosomes . Inhibition of polo-like kinase Plk1 , on the other hand , decreased the separase activity towards the Scc1 but not the kendrin reporter . Together these findings indicate that Plk1 regulates separase activity at the level of substrate affinity at centrosomes and may explain in part the role of Plk1 in centriole disengagement . Centrosomes are the main microtubule organizing centers of animal cells that consist of the organizing centrioles and pericentriolar material . Centrosomes , like DNA , duplicate exactly once per cell cycle . From S phase to the end of mitosis centrosomes are composed of a pair of centrioles , the mother and the daughter centrioles , which lie perpendicular to one another [1] . Separation of the mother and daughter centrioles , also referred to as “centriole disengagement” , takes place in telophase/G1 and is the licensing step for centriole duplication in the next S phase [2]–[4] . Following the centriole disengagement , a flexible linker containing the proteins C-Nap1 and rootletin assembles between the separated centrioles [5] . The C-Nap1/rootletin linker connects the two centrosomes ( also named centrosome cohesion ) until G2 or the beginning of mitosis when the linker is disassembled by the activity of the kinase Nek2 [6]–[9] . The disjoined centrosomes each containing two orthogonally engaged centrioles then become the poles of the mitotic spindle [9] . Thus , centriole engagement and centrosome cohesion are two distinct processes that are regulated by different mechanisms . Separase ( Espl1 ) , a cysteine protease , is best known for its role in relieving sister chromatid cohesin during the metaphase-anaphase transition by cleaving the cohesin subunit Scc1/Rad21 [10] , [11] . The function of separase in centriole disengagement has been established in Xenopus egg extracts [3] . Consistently , centriole disengagement was partially inhibited in human separase knockout cells . However , centriole disengagement was only blocked completely when the activities of both separase and the polo-like kinase Plk1 were simultaneously repressed [12] . Both cyclin B1 and securin have been shown to inhibit separase at chromosome until the end of anaphase [11] , [13] . On the other hand , the regulation of separase at centrosomes is poorly understood . The proteins astrin and Aki1 have been proposed to act as inhibitors of centrosomal separase activity [14] , [15] . Depletion of either astrin or Aki1 induces multipolar spindles in mitosis with disengaged centrioles , which would be consistent with premature separase activation [14] , [15] . Furthermore , shugoshin ( Sgo1 ) is the “guardian” of the chromosomes and prevents the prophase-dependent removal of cohesin from centromeres by recruiting PP2A-B56 to the centromere to counteract Plk1 kinase activity [16] , [17] . Interestingly , a smaller version of Sgo1 , called sSgo1 , associates with the centrosomes . Depletion of Sgo1 promotes centriole disengagement in human cells in a manner that requires Plk1 activity [18] . Kendrin , a splice variant of pericentrin , is a coiled-coil motif containing protein which localizes to the centrosomes , where it recruits the γ-tubulin ring complex and modulates centrosome cohesion through the regulation of Nek2A kinase activity [19]–[21] . Localization studies identified also the subunits of cohesin at the centrosomes [22] . Moreover , siRNA depletion experiments showed that not only kendrin , but also cohesin is important for the integrity of the centrosome [23] . Strikingly , the cohesin subunit Scc1/Rad21 and kendrin/pericentrin B , here referred to as Scc1 and kendrin , respectively , are both cleaved by separase at the centrosome [24] , [25] . Subsequent biochemical analyses support the notion that cohesin is the “glue” that connects the mother to the daughter centrioles , and that cleavage of this pool of cohesin by separase promotes centriole disengagement [24] . Furthermore , expression of a non-cleavable version of kendrin blocks centriole disengagement [25] . A fluorescence-based method was used to measure the separase activity on chromosomes [26] , [27] . This separase activity sensor comprises the separase cleavage sites of Scc1142-467 flanked by N-terminal mCherry and C-terminal eGFP fluorescent molecules . Cleavage of the sensor releases the eGFP moiety to diffuse throughout the cytoplasm while the mCherry remains anchored at chromosomes because it is fused to C-terminus of H2B . As a result , the color of the sensor at chromosomes switches from yellow to red [26] . Here we investigated the regulation of separase activity at the centrosomes using Scc1- and kendrin-based separase sensors , which were targeted to centrosomes via the PACT domain of AKAP450 [28] , [29] . Both sensors changed their fluorescent signal in a manner that required separase activation and the integrity of the separase cleavage site . Centrosomal separase activity strongly increased midway through metaphase ahead of chromatin-associated separase activity . We also tested whether astrin , Aki1 and sSgo1 regulate centrosomal separase activity and show that morphological criteria are insufficient indicators for separase activation at centrosomes . Separase localizes to centrosomes during mitosis where it regulates the centriole disengagement [12] , [30] . However , it remains to be established how this centrosomal separase activity is regulated . To address this important question , we have developed two distinct “separase sensors” that measure separase activity at the centrosomes of individual cells in real time . The sensors contained the separase cleavage sites ( SCS ) of either Scc1 ( 142–467 aa; cleavage sites at R172 - cleavage site 1 , R450 and R460 - cleavage site 2 ) or kendrin ( 2059–2398 aa; cleavage site at R2231 ) , the two known centrosomal separase substrates [26] , [31] . mCherry was fused to the N-terminus and eGFP to the C-terminus of each SCS element . Each mCherry-SCS-eGFP module was joined to the N-terminus of the PACT domain of AKAP450 ( aa 3643–3808 ) ( Figure 1A , Figure S1A ) . The PACT domain is a high affinity centrosomal targeting domain , and so will target each of these two reporters to the centrosome [28] . To control for separase cleavage dependent changes in fluorescent signal , we also used reporters in which critical residues within the separase cleavage sites ( ExxR ) were mutated ( RxxE ) . These mutations inhibit the ability of separase to cleave the fusion protein ( separase sensorNC ) ( Figure S1A ) and so this modified reporter serves as an important internal control for separase dependent cleavage [10] , [26] . The reporters were stably integrated into the FRT sites of HeLa T-REx cells to render their expression dependent upon the addition of doxycycline [32] . The first version of the Scc1-derived sensor accumulated in the nucleus during interphase and failed to bind to the centrosomes even after nuclear envelope breakdown in mitosis ( Figure S1B . However , inactivation of the first nuclear localization sequence ( ΔNLS-1 , 319–323 aa of Scc1 ) in the mCherry-Scc1 ( 142-467 ) -ΔNLS-eGFP-PACT reporter ( named Scc1 ( 142-467 ) -ΔNLS ) ) promoted its binding to the centrosomes ( Figure S1C ) . Nonetheless a fraction of the sensor was still detected in the cytoplasm and nucleus . Most likely the number of centrosomal binding sites for the PACT based reporter is limited as this has been observed for other PACT fusion proteins [29] . Fluorescence recovery after photobleaching ( FRAP ) revealed that the mCherry-Scc1 ( 142-467 ) -ΔNLS-eGFP-PACT reporter stably associated with centrosomes ( Figure S1D ) . The kendrin-based sensor was also enriched at the centrosome ( Figure S1C , right panel ) with additional signal in the cytoplasm . Thus , both reporters are targeted to centrosomes via their PACT domain . At chromosomes , separase becomes active just before anaphase onset [26] . In contrast , the exact timing of separase activation at centrosomes is unknown . Real time fluorescence analysis showed that the yellow mCherry-SCS-GFP-PACT signal at centrosomes switched to green GFP-PACT before cells entered anaphase ( Figures 1B , C and Figure S1E ) . This was indicative of reporter cleavage to release the mCherry moiety into the cytoplasm , while eGFP-PACT was retained at centrosomes . The yellow fluorescent signal from the corresponding non-cleavable separase sensorNC persisted at centrosomes throughout the cell cycle ( Figures 1B , D and Figures S1E , F ) . It has been shown that both Scc1 and kendrin are substrates of separase , and they are not cleaved upon Espl1 siRNA [10] , [25]–[27] , [33] , [34] . For proof of principle analyses , we interfered with separase activity via Espl1 siRNA and showed that reporter activation was prevented even when cells passed into G1 phase ( Figures S2A–E ) . Thus , the cleavage of the separase reporters at the centrosome was indeed dependent on separase activity and occurred before anaphase onset . We next addressed whether the timing of separase activation on chromosomes coincided with its activation on centrosomes . For this , we compared cleavage of the centrosomal mCherry-Scc1 ( 142-467 ) -ΔNLS-eGFP-PACT and mCherry-Kendrin ( 2059-2398 ) -eGFP-PACT reporters with the chromatin-associated sensor . Anaphase onset was used as the internal reference point ( t = 0 ) for both reporters . In line with published data , separase became active at chromosomes between −6 and 0 min before anaphase onset [26] . Both centrosomal reporters , however , were activated between −12 and −6 min , clearly before separase activation on chromatin ( Figure 1B , Figure S3 ) . The delayed activation of separase at chromatin might reflect a preferred spatial activation of separase at centrosomes , as has been reported for Cdk1-cyclin B1 [35] . The degradation of cyclin B1 in Drosophila also starts at spindle poles and from there spreads to the metaphase plate [36] . This behavior of the separase inhibitor cyclin B is consistent with the earlier activation of separase at centrosomes . In such a model , separase activity spreads from centrosomes to the cytoplasm . However , it is also possible that separase is activated with the same timing at both locations but cleaves cohesin and kendrin at the centrosomes faster than the chromatin bound cohesin because of topological restrains . A number of proteins are transported to the centrosomes along microtubules [37] , [38] . We used the Scc1-based reporter to ask whether activation of separase at the centrosomes requires microtubules or the activity of the minus-end directed , microtubule-based motor protein dynein . Cells were first synchronized in prometaphase with the drugs STLC ( ( + ) -S-trityl-L-cysteine ) or nocodazole that arrest the cells due to spindle checkpoint activation ( Figure 2A ) [39] . In STLC-treated cells , dynein was subsequently inhibited by the Ciliobrevin D [40] . Cells were then driven from prometaphase to G1 by Cdk1 inhibition with RO-3306 , and as previously reported this treatment does not interfere with the activation of separase during mitotic exit ( Figure 2A ) [41] , [42] . Moreover , in vivo experiments revealed that centrioles still disengage in response to Cdk1 inhibition [12] . Upon dynein inhibition or microtubule depolymerization the Scc1-based reporter was cleaved with similar efficiency as in the control ( Figure 2B , C ) or during a normal mitotic exit ( Figure 1B , 24 min ) . Thus , separase activity at centrosomes is independent of polymerized microtubules or dynein activity . Consistently , the level of Espl1 at the centrosome did not decrease by nocodazole-induced microtubule depolymerization when compared with STLC treated control cells ( Figure 2D ) . Instead , nocodazole slightly increased the centrosomal Espl1 signal ( Figure 2D ) . Scc1/Rad21 is also a substrate of caspase-3 during apoptosis [43] . We analyzed the level of PARP cleavage in order to eliminate the involvement of caspase-3 in sensor cleavage in our experimental approaches ( Figure S4A ) . Although there was no significant change in apoptotic cleavage of PARP , in order to be completely sure that the apoptotic cleavage of Scc1-based sensors did not interfere with the experimental setup , the experiments were repeated with either a non-cleavable version of the separase sensor ( Figure S4B ) or with the wild-type sensor in the presence of the apoptosis inhibitor Z-VAD-FMK ( Figure S4C ) . As expected , the non-cleavable sensor was not subject to cleavage and the wild-type sensor was still cleaved in the presence of apoptosis inhibitor . In conclusion , centrosomal activation of separase is independent of microtubule integrity and reporter cleavage is a direct consequence of separase activity at centrosomes . Activation of separase midway through metaphase prompted us to analyze the localization of separase to discriminate between two possibilities: First , separase is targeted to the centrosomes after initial activation at the centrosome . Alternatively , binding to the centrosome and local activation are two distinct steps . Although we detected a cytoplasmic separase signal during interphase as previously reported [44] , no centrosomal signal was seen . From pro-metaphase onwards until telophase/G1 separase was detected at centrosomes ( Figure 2E ) . Furthermore the localization of separase-GFP , expressed in HeLa BAC cells , confirmed the timing of separase recruitment to centrosomes ( Figure S5 ) . Thus , separase localizes to centrosomes from prometaphase to G1 but is only active at this location 6–12 min before anaphase onset . This means that separase targeting to centrosomes and separase activation are two independent processes . The proteins astrin ( Spag5 ) and Aki1 have been implicated in the regulation of separase activity at centrosomes [14] , [15] . Depletion of astrin causes premature separase activation and sister chromatid disjunction [14] . Moreover , depletion of either astrin or Aki1 promotes premature centriole disengagement in mitosis [14] , [15] . To test whether astrin and Aki1 directly regulate separase activity at centrosomes , each protein was depleted from HeLa cells carrying either the Scc1- or the kendrin-based separase sensors by siRNA ( Figure 3A , Figure S6A ) . Consistent with published data , astrin or Aki1 depletion gave rise to cells with separated sister chromatids ( Figure 3B ) [14] . However , the Scc1 and kendrin sensors indicated that separase was either not or only very weakly activated at centrosomes ( Figure 3C ) . Furthermore , there was no increase in the number of separated centriole pairs upon astrin depletion since always a mother and daughter centriole pair closely associated with one mitotic spindle pole ( Figures S6B , C ) . It is therefore unlikely that astrin regulates centrosomal separase activity . Similarly , Aki1 depletion did not activate separase ( Figure 3C ) . Disengaged centrioles remain connected by centrosomal linker proteins including rootletin until onset of mitosis [4] . To eliminate the possibility that in our depletion experiments mitotic centrioles are joined together by the C-Nap1/rootletin linker , we asked whether the protein rootletin was associated with centrosomes [45] . Rootletin was absent from the mitotic centrosomes upon astrin and Aki1 depletion while it was associated with interphase centrioles ( Figure S6B ) . This provides further evidence that mitotic centrioles remain together when astrin and Aki1 are depleted . Thus , how does astrin or Aki1 depletion cause sister chromatid disjunction without separase activation ? Recent reports have implicated the role of astrin in kinetochore-microtubule attachments [46] . Aki1 or astrin depletion probably causes mitotic arrest through activation of the spindle assembly checkpoint that eventually leads to loss of sister chromatid cohesion without separase activation through a mechanism called “cohesion fatigue” [47] . A smaller splice variant of Sgo1 , named sSgo1 , associates with centrosomes [18] . It has been reported that Sgo1/sSgo1 depletion leads to both the premature disjunction of sister chromatids and centriole disengagement . sSgo1 might counteract Plk1 activity through the recruitment of PP2A-B56 , as demonstrated for centromeric Sgo1 [16] , [48] , [49] . Alternatively , sSgo1 may regulate centrosomal separase activity . To discriminate between these two possibilities , Sgo1 and sSgo1 were co-depleted from our reporter cell line by siRNA ( Figure 3A ) . Depletion of sSgo1 co-depletes Sgo1 because the coding region of this splice variant overlaps with Sgo1 . Chromosome spreads revealed that Sgo1/sSgo1 depletion arrested mitotic progression at metaphase with disjoined sister chromatids ( Figure 3B ) . However , Sgo1/sSgo1 depleted cells did not separate the closely associated centrioles prematurely as judged by the persistence of paired centrin signals ( Figures S6B , C ) . Measurements of the distance of the distal centriole marker GFP-centrin also confirmed the tightly association of mother and daughter centrioles in Sgo1/sSgo1 depleted cells ( Figure S6D ) . The centriole pairs in siRNA Sgo1/sSgo1 depleted cells had the same close distance as wild type cells arrested at prometaphase by STLC . In contrast , STLC treated cells that were driven into G1 by Cdk1 inhibition and therefore had disengaged centrioles showed much larger GFP-centrin distances ( Figure S6D ) [3] . Moreover , we failed to see a significant increase in the percentage of multipolar spindles during mitosis , which is normally caused by premature centriole disengagement ( Figure 3D ) [50] . Sgo1/sSgo1 depletion did not activate separase at centrosomes or chromosomes as indicated by the co-localization of eGFP and mCherry at centrosomes and chromosomes ( Figure 3C , Figure S6E ) . However , in ∼20% of Sgo1/sSgo1 siRNA cells , we observed unfocused γ-tubulin signals at centrosomes that sometimes contained extra γ-tubulin foci ( Figure S6F ) . The majority of these additional γ-tubulin signals did not contain GFP-centrin suggesting that they arose from disruption of centrosome structure rather than from centriole disengagement . Indeed , loss of tension at kinetochores provokes centrosome fragmentation [51] . Thus , Sgo1/sSgo1 depleted cells fragment the centrosomes due to the loss of kinetochore tension . Plk1 has been suggested to promote centriole disengagement in a pathway overlapping with separase [12] . This function of Plk1 directed us to test whether Plk1 regulates centrosomal separase activity . We first arrested cells with the kinesin-5 ( Eg5 ) inhibitor STLC in prometaphase . Subsequently , Plk1 activity was inhibited using the specific , small molecule inhibitor BI2536 . Cdk1 inhibition ( RO-3306 ) then drove cells out of mitosis ( Figure S7A ) . Plk1 inhibition reduced cleavage of the Scc1 based separase sensor at centrosomes to ∼50% even when cells were incubated for 3 h with the Cdk1 inhibitor ( Figure 4A , B ) . After Cdk1 inhibition the nuclear envelope reformed in 100% of the cells and a fraction of the Scc1 sensor was targeted to the nucleus due to its nuclear localization signal indicating that cells exited mitosis ( Figure 4C and Figure S1C ) . Moreover , inhibition of Plk1 decreased the activity of separase not only at the centrosome but also at the chromatin ( Figure S7B ) . The impact of Plk1 towards the activity of separase at the centrosome could be due to the decrease in the phosphorylation of the anaphase promoting complex APC/C . Plk1 phosphorylation of APC/C complex in G2 cells maintains the APC/C in an inactive state , such that inhibition of Plk1 induces premature APC/C activation in G2 [52] . In order to test , whether we see a similar effect during mitosis , we analyzed the steady state levels of the APC/C substrate cyclin B1 . Cyclin B1 levels of prometaphase arrested cells ( nocodazole ) did not increase in repeated experiments following Plk1 inhibition ( Figure 5A , lines 1 and 2 ) . However , kendrin was still efficiently cleaved when cells were driven out of mitosis by the Cdk1 inhibitor RO-3336 as indicated by Plk1/Cyclin B1 degradation and H3S10 dephosphorylation ( Figure 5A , lanes 3 and 4 ) . These findings argue against the possibility that Plk1 inhibition during mitosis activates the APC/C that then would degrade the separase inhibitors securin and cyclin B1 to promote separase activation . Alternatively , Plk1 phosphorylation of Scc1 might increase its cleavage . Such a model has been proposed for the chromosomal Scc1 [49] . Scc1 has two separase cleavage sites ( R172 and R450/R460 ) with neighboring Plk1 phosphorylation sites ( e . g . S175 and S454 ) . At chromosomes Plk1 mainly regulates the Scc1 cleavage site at R450/R460 . Cleavage at R172 , moreover , is only moderately stimulated by Plk1 [49] . To test whether Plk1 stimulates Scc1 cleavage at centrosomes through substrate phosphorylation , we first inactivated the separase cleavage at R172 ( mutation from “ExxR” to “RxxE” ) . Additionally , we mutated the Plk1 phosphorylation site Ser454 to Ala to prevent phosphorylation near the second separase cleavage site . Inactivation of the first separase cleavage site by the R172E mutation strongly reduced cleavage of the Scc1 reporter indicating that the first separase cleavage site around R172 is preferentially cleaved over the second site at R450/R460 ( Figure S8A , B ) . We next asked whether the R450/R460 site is regulated through Plk1 phosphorylation at S454 . The R172E/S454A double mutation completely abolished separase cleavage of the Scc1 reporter ( Figure S8A , C ) . Cleavage of the first site at R172 was independent of the Plk1 phosphorylation site S175 as the double phospho-dead mutant ( S175A/S454A ) was still cleaved by separase ( Figures S8A , D ) as reported before [49] . However , Plk1 inhibition by BI2536 in S175A/S454A mutant cells prevented the complete cleavage of this mutant sensor ( Figure S8E ) . This implies that additional Plk1 sites in Scc1 might be important for the separase activity at the centrosome . Additional Plk1 phosphorylation sites close to the fist separase cleavage site of Scc1 have been reported [49] . Mutating these sites ( T144A , S153A , S175A , S185A , T186A , T187A , T188A , S189A ) together with inactivating the second separase cut site ( R450E and R460E , Scc1 ( 142-467 ) -8A-ΔNLS-ERRE ) strongly reduced cleavage efficiency of the Scc1 separase reported at centrosomes ( Figures S9A , B ) . Thus , separase cleavage of both cut sites of Scc1 at centrosomes is promoted by Plk1 phosphorylation . Interestingly , the same Plk1 inhibition experiment with the kendrin sensor did not reveal a dependency of sensor cleavage on Plk1 activity ( Figures 5B and C ) . This result excludes a role for Plk1 in separase targeting to the centrosomes or in separase specific activity since both reporters would be equally affected if this were the case . Consistently , separase's localization on centrosomes was not affected by Plk1 inhibition when compared with nocodazole arrested prometaphase cells ( Figure 5D ) . In contrast , Plk1 inhibition affected localization of γ-tubulin at centrosomes implying that Plk1 inhibition worked as expected ( Figure 5D ) [53] . Taken together , a likely explanation of our results is therefore that Plk1 activates the Scc1 substrate whereas such an activation step is not required for kendrin . In conclusion , we have constructed reporter proteins that measure the activity of separase at centrosomes . With these sensors in hand , we have tested putative regulators of centrosomal separase . This analysis indicates that astrin and Aki1 do not activate separase at centrosomes . Instead , we propose that the centriole separation phenotype that arises from astrin and Aki1 depletion is a secondary consequence of the loss of sister-chromatid cohesion [14] , [18] . This demonstrates the importance of using separase sensors to analyze separase activity at centrosomes . Morphological criteria such as multipolar spindles or multiple centrosomes do not support conclusions about separase activity at centrosomes as these phenotypes may arise from the loss of sister chromatid cohesion during prolonged mitotic arrests . The sensors we have constructed are excellent tools to find the regulators of separase at the centrosome in screening-based studies . Our data suggest that separase localizes to centrosomes from prometaphase until the end of mitosis with continued accumulation to enhanced levels during anaphase . Separase was active at centrosomes before it was activated at chromosomes , which may be explained by the early loss of Cdk1-cyclin B1 activity at the centrosomes ahead of the general wave of cyclin B1 degradation [36] , [54] , [55] . The APC/C complex may be initially activated at centrosomes before diffusing throughout the cell . We also found that Plk1 promotes cleavage of a subset of substrates by separase at centrosomes , while kendrin does not require Plk1 activation for separase cleavage . This finding at least in part explains the role of Plk1 in centriole disengagement . The following antibodies directed against the indicated proteins were used in this study: Sgo1 ( 1∶1000 , Thermo Scientific PA5-30869 ) , astrin ( 1∶1000 , Bethyl Laboratories A301-512A ) , tubulin ( 1∶1000 , Sigma T9026 ) , pericentrin ( 1∶2000 , Abcam ab4448 ) , cyclin B1 ( 1∶200 , CR UK V152 ) , PARP ( 1∶1000 , Cell Signaling #9532 ) , separase ( 1∶500 , Abcam ab16170 ) for WB , separase ( 1∶500 , Abcam ab3762 ) for IF and γ-tubulin ( 1∶1000 , Sigma ) . HeLa Centrin2-GFP cells , HeLa FRT cells , Separase-GFP expressing HeLa BAC cell line and U2OS cells were cultured in Dulbecco's Modified Eagle's Medium ( DMEM ) Glutamax ( Gibco ) supplemented with 10% FBS , 1% P/S and 1% Na-Pyruvate . Stable HeLa FRT cells were created and sustained as described previously [56] . At least two different siRNAs were used for depletion experiments of astrin , Aki1 and sSgo1 . siRNA oligos that were directed against the same mRNA gave identical phenotypes in depletion experiments . Therefore , the results of only one siRNA oligo ( marked with * ) per mRNA are shown in this manuscript . Cells were transfected with cDNA or siRNA according to the manufacturer's protocol via Lipofectamine 2000 or RNAiMax , respectively ( Invitrogen ) . Sgo1 siRNAs ( s45599*: 5′-CAUCUUAGCCUGAAGGAUAtt-3′ and s45600: 5′-GGCAAACGCAGGUCUUUUAtt-3′ , Ambion; #L-015475-00-0005 pool of: 5′-GUGAAGGAUUUACCGCAAA-3′ , 5′-AAACGCAGGUCUUUUAUAG-3′ , 5′-GUUACUAUCUCACAUGUCA-3′ , 5′-CAGCCAGCGUGAACUAUAA-3′ , Dharmacon ) were used at concentration of 100 µM . Aki1 siRNA ( #s226792*: 5′-AACAAAGACAUCCAGAUCGCCAGGG-3′ , Ambion; #GS54862 pool of: 5′-CACGAGCGCATCGTCAAGCAA-3′ , 5′-CAGCGCCAAGATGCGGCGCTA-3′ , 5′-CAAGTTCGAAGTGGTTCACAA-3′ and 5′-CCCGGCGTCCACGCCTACCTA-3′ , Qiagen ) , astrin siRNA ( #SI02653938: 5′-AAAUUAGCUCUACUCCUAAtt-3′ and #SI02653945*: 5′-CCGACAACUCACAGAGAAAtt-3′ ) , Espl1 siRNA ( #s121651: 5′-GCUUGUGAUGCCAUCCUGAtt-3′ , Ambion ) were used at concentration of 50 µM . Sgo1 depleted cells were checked after 24 h whereas astrin , Aki1 and Espl1 depleted cells were checked 48 h after transfection via microscopy and immunoblotting . For live cell imaging , cell cycle progression was blocked with 2 . 5 mM thymidine ( Sigma , #T1895 ) for 24 h . After three washes with PBS , cells were released into fresh media for 10 h . For inhibitor experiments , cells were arrested in prometaphase with 5 µM S-trityl-L-cysteine ( STLC , Sigma #164739 ) for 15 h , and Plk1 inhibitor BI2536 or 50 µM dynein inhibitor Ciliobrevin D ( #250401 , Millipore ) was added for 1 h more . 5 µM of Cdk1 inhibitor RO-3336 ( Millipore , #217699 ) was used to trigger mitotic exit . Z-VAD ( OMe ) -FMK was used for apoptosis inhibition ( Millipore , #627610 ) . Cells , grown on coverslips , were fixed with ice-cold methanol for 5 min , and rehydrated with PBS . Coverslips were incubated with 10% FBS ( fetal bovine serum ) for 1 h , and washed with PBS and then re-incubated with primary antibodies in 3% BSA ( Sigma , #05470 ) for 1 h . Following three washes with PBS , the coverslips were further incubated in 1∶500 dilution of 2 mg/ml Alexa-488/Alexa-555/Alexa-647 ( Molecular Probes ) conjugated secondary antibodies , which were diluted in 3% BSA plus 5 µg/ml Hoechst 33342 ( Molecular Probes ) , for 30 min . The coverslips were mounted in Prolong Gold Antifade ( #P36930 , Molecular Probes ) . For Espl1-GFP localization , HeLa cells were pre-extracted in 0 . 1% TX-100 plus 20 µg/ml Alexa-647 conjugated nanobody ( Chromotek ) for 6 min , following 3 washes with PBS , the cells were directly observed in PBS without fixation . For immunofluorescence analysis of separase in U2OS cells and co-localization of separase and centrosomal markers in HeLa Espl1-GFP cells , cells were pre-extracted with 0 . 1% TX-100 for either 1 min or 2 min , respectively , before fixation in ice-cold methanol for 5 min . Subsequent procedures were as above . The images were quantified using Fiji ( ImageJ , http://fiji . sc/Fiji ) . The onset of anaphase was marked by the separation of sister chromatids . The mean fluorescence intensities of GFP and mCherry at the centrosomes were quantified using raw data without projection since the Scc1-based sensor , which also localizes to the nucleus , disperses to the cytoplasm after nuclear envelope breakdown to create a background signal . This makes quantifications of Z-projections of the sensor incomparable . The centrosome signals are usually observed in only 1 stack , as the distance between each stack was 1 µm ( double the size of a centrosome ) . For the kendrin-based sensor , quantifications were made with Z-projected images as the sensor specifically localizes to the centrosome . For background correction , the cytoplasmic signal was subtracted from the measured centrosomal signal . The mCherry/eGFP ( RR ) ratio was used to represent sensor cleavage efficiency . In order to assess the rate of cleavage , each RR value was normalized to the average of two measured RR values . If the ratio was negative , it was considered to be zero . The graphs were plotted using Prism 6 software . For the H2B sensor , eGFP/mCherry ratio was used as the sensor was put C-terminally . For each quantification , n represents the number of centrosomes quantified . The centriole distance in 3D has been measured using Fiji . Stable HeLa FRT cells were seeded onto Labtek Chambers ( Thermo Scientific , #155411 ) and induced with 2 µg/ml doxycyclin ( Sigma , #D9891 ) for 24 h before being observed in Live Cell Imaging Media ( Gibco ) using DeltaVision Olympus IX71 microscope ( Applied Precision ) equipped with DAPI , FITC , TRITC , and Cy5 filters ( Chroma Technology ) and CoolSNAP HQ camera ( Photometrics ) . Images were taken every 6 min with 14 z-stack ( 1 µm/stack ) using Plan Apo 60× NA 1 . 4 oil-immersion objectives ( Olympus ) with 2×2 binning . Cells were grown in 6 cm dishes . 24 or 48 h after siRNA transfection , 100 ng/ml colcemid was added before a further incubation for 1 h ( Kryomax , Invitrogen ) . The experiment was continued as before with a slight modification [57] . In brief , cells were collected and suspended in 0 . 8% sodium citrate ( Sigma , #W302600 ) , and incubated for 10 min . After sedimentation at 1 , 000 rpm for 10 min , cells were fixed with freshly prepared fixation solution ( 75% methanol+25% acetic acid ) and incubated for 10 min . This process was repeated 3 times before final resuspending the cells in 300 µl of fixation solution and dropping them onto Fisher Superfrost/Plus slides ( Thermo Scientific ) followed by drying . Finally , the slides were incubated in 1 µg/µl Hoechst solution for 15 min and mounted with number 1 . 5 coverslips using Prolong Gold ( Molecular Probes ) . Cells were collected by scraping and washed with PBS . After lysis in 10 mM Tris-Cl pH 7 . 5; 150 mM NaCl; 5 mM EDTA; 0 . 1% SDS; 1% Triton X-100; 1% deoxycholate supplemented with 1 mM PMSF ( Sigma ) and Roche protease inhibitor cocktail for 30 min cell pellets were boiled with Laemmni buffer .
Centriole disengagement in telophase/G1 is the licensing step for centrosome duplication in the subsequent S phase . Recent data suggest that separase , together with polo-like kinase Plk1 , is essential for the centriole disengagement and individual depletion of either separase or Plk1 alone fails to suppress the centriole disengagement . This raises the question of how separase activity is regulated at the centrosome . By generating a series of separase sensors , we show that separase at centrosomes becomes active already in mid metaphase , well before its activity can be detected at the chromosomes . Depletion of the previously published inhibitors of centrosomal separase , astrin or Aki1 , did not promote separase activity at the centrosomes . This indicates that morphological criteria like the formation of multipolar spindles are insufficient criteria upon which to base predictions about separase regulation . Finally , the ability of Plk1 to promote cleavage of the Scc1-based reporter but not of the kendrin reporter reveals regulation of separase activity at the substrate level . These results provide partial explanation of the role of Plk1 in centriole disengagement .
[ "Abstract", "Introduction", "Results", "and", "Discussion", "Materials", "and", "Methods" ]
[ "biotechnology", "cell", "biology", "biology", "and", "life", "sciences", "molecular", "biology" ]
2014
Sensors at Centrosomes Reveal Determinants of Local Separase Activity
The mechanisms underlying prion-linked neurodegeneration remain to be elucidated , despite several recent advances in this field . Herein , we show that soluble , low molecular weight oligomers of the full-length prion protein ( PrP ) , which possess characteristics of PrP to PrPsc conversion intermediates such as partial protease resistance , are neurotoxic in vitro on primary cultures of neurons and in vivo after subcortical stereotaxic injection . Monomeric PrP was not toxic . Insoluble , fibrillar forms of PrP exhibited no toxicity in vitro and were less toxic than their oligomeric counterparts in vivo . The toxicity was independent of PrP expression in the neurons both in vitro and in vivo for the PrP oligomers and in vivo for the PrP fibrils . Rescue experiments with antibodies showed that the exposure of the hydrophobic stretch of PrP at the oligomeric surface was necessary for toxicity . This study identifies toxic PrP species in vivo . It shows that PrP-induced neurodegeneration shares common mechanisms with other brain amyloidoses like Alzheimer disease and opens new avenues for neuroprotective intervention strategies of prion diseases targeting PrP oligomers . Transmissible spongiform encephalopathies are infectious neurodegenerative diseases . They are characterized by the accumulation in the brain , and sometimes the lymphoid tissues [1 , 2] , of an abnormally structured form ( PrPsc ) of the host prion protein ( PrP ) [3] . PrPsc may constitute the infectious agent , also called prion , entirely [4] or in part [5 , 6] . The mechanism of neurodegeneration that ultimately leads to neuronal death and the occurrence of clinical symptoms , however , is still not known [7 , 8] . It has become apparent that immunohistochemically detectable PrPsc aggregates , of various sizes ranging from fine granular deposition to amyloid plaques , do not represent the neurotoxic entity of prion diseases . Indeed , PrPsc is not detectable in some cases of fatal familial insomnia [9] , in lethal scrapie-like disease in mice overexpressing mutant PrP transgenes [10] , in wild-type mice inoculated with bovine spongiform encephalopathy [11 , 12] or fatal familial insomnia [13] , and in prion-infected mice with a P101L mutation in their PrP gene [14] . The hypothesis has been made earlier that the critical events in pathogenesis occur at the submicroscopic level [15] . On the other hand , PrP peptides comprising the hydrophobic domain ( residues 106–126 ) of PrP are toxic to cultured neurons [16–19] . N-terminally truncated PrP also triggers neuronal death in the absence of expression of the normal form of the protein [20] . This shows that PrP has intrinsic properties that could render the protein toxic under certain conditions . There is growing evidence that in other brain amyloidoses , prefibrillar soluble protein aggregates , rather than insoluble fibrils , are toxic [21–24] . In vivo , 56-kD dodecameric assemblies of Aß1–42 , dubbed Aß* ( of note , PrP* has also been proposed as the biologically reactive form of PrP [25] ) , have been shown to be associated with memory deficits in a murine model of Alzheimer disease and to cause transient memory impairment after injection in the brains of rats [26] . In a zebrafish model , expression of polyQ-expanded fragments of huntingtin lead to their accumulation as large SDS-insoluble cell inclusions; however , apoptotic cells are devoid of visible aggregates . Remarkably , the treatment with two anti-prion compounds prevented the formation of insoluble aggregates but did not suppress abnormal embryo morphology or cell death , strongly suggesting that upstream soluble huntingtin assemblies constitute the toxic culprit [27] . Recently , soluble oligomers presenting an enriched ß-sheeted structure were proposed as intermediates in the amyloidogenesis process featured in prion diseases [28–31] . PrP oligomers were toxic in vitro [32 , 33] . We wanted to further investigate the hypothesis that prion diseases share a common mechanism of neurodegeneration with other brain amyloidosis , and set out to study the toxicity of PrP oligomers in vitro and in vivo in the presence or absence of endogenous PrP expression . We found that PrP oligomers exhibit considerably higher toxicity than PrP fibrils both in vitro and in vivo . PrP monomers were nontoxic . The toxicity occurred whether or not the neurons expressed PrPc . The toxicity of PrP oligomers could be abrogated by blocking the hydrophobic domain at the surface of the oligomers . We propose a comprehensive model of the possible mechanisms of prion-induced neurodegeneration . Two types of PrP oligomers were produced by either thermal refolding or expression of PrP in form of a tandem repeat . A recombinant ovine PrP ( 23–234 ) was generated and converted into a ß-sheeted form ( ß-PrP ) ( Figure 1A and 1B , left panel ) by thermal refolding ( see Materials and Methods and [34] ) . Both the ß-sheeted and the α-helical conformers had mobilities corresponding to a molecular weight of about 25 kDa by SDS-PAGE ( Figure 1C , left panel ) . Another type of PrP oligomer was created by exploiting the finding that dimerization has been described as a primary event in the PrP conversion and aggregation process [35] . Two monomeric PrP units were covalently linked head to tail via a flexible linker ( Figure 1A , right panel ) . This protein displayed a molecular weight double that of the monomeric PrP in the presence of detergents ( Figure 1C , right panel ) . The tandem murine PrP presents a higher ß-sheeted content than the monomeric PrP as judged by the increase in the 1 , 618 cm−1-peak ( Figure 1B , right panel ) . Size exclusion chromatography of both types of PrP preparations in physiological buffers showed that they were exclusively in an oligomeric state ( [36] and Figure 1D ) . In summary , the tandem mouse PrP oligomerized spontaneously after purification , while the ovine PrP oligomerized after heating . These results are consistent with the recent finding that α-PrP molecules convert into ß-sheeted oligomers with a molten globule intermediate in the absence of any detectable ß-sheeted monomeric PrP intermediate [37] . Both types of PrP oligomers showed slightly enhanced thioflavine T binding ( Figure 1E ) , strongly suggesting that they were on the pathway of amyloid fibril formation ( see below ) . We investigated whether oligomeric PrP was more resistant to proteinase K ( PK ) digestion than monomeric PrP . Each type of PrP was submitted to a range of PK concentrations . Both murine and ovine PrP oligomers exhibited partial resistance to PK digestion when compared to their respective monomeric counterparts ( Figure 1C ) , as shown by i ) the difference in the degradation profile between the tandem PrP oligomers and the monomer at 500 ng/ml and 1 μg/ml ( the degradation of the tandem levels out , whereas the monomer continues to be degraded ( compare arrows #1 ) ; ii ) a PK-resistant core of the tandem of 36 kDa , which appears with increasing PK concentrations ( see arrow #2 ) ; iii ) the 20-kDa degradation product from the tandem increases with increasing concentrations of PK contrarily to the same 20-kDa product from the monomer ( compare arrows #3 ) ; and iv ) the residual ∼25-kDa band of the ovine ß-PrP observed at the PK concentration of 500 ng/ml ( albeit weak , this signal was reproducible between experiments ) , contrasting with the complete digestion of ovine PrP monomers at the same concentration ( arrows #4 ) . We first analyzed the neurotoxic properties of the PrP oligomers in a murine primary cortical neuron model . Exposure of the neurons to both types of PrP oligomers resulted in a loss of nearly 50% of the neurons when compared to the untreated control cells , at a dose of 200 μg/ml ( Figure 2A ) and 100 μg/ml ( Figure 2D ) , both corresponding to a concentration of 3 μM . Hence , oligomeric PrP exhibited a roughly 30-fold higher toxic effect than the PrP peptide 105–132 , which inserts into cellular membranes , and which induced 40% neuronal death at 100 μM ( Figure 2E ) . The same levels of toxicity were observed in PrP0/0 neurons , indicating that the effect was not dependent on the expression of PrP by the cells ( Figure 2B for murine PrP oligomers , data not shown for ovine PrP oligomers ) . We then wanted to verify that the seven–amino acid linker or the His expression tag present in the murine PrP oligomers were not responsible for their toxicity . Neither the linker , flanked on both sides by ten residues from the N- and C-terminal regions of the PrP sequence , ( Figure 2C ) nor grb-2 [38] , an irrelevant protein of the same size as PrP ( 217 aa ) , generated in the same expression system as the tandem PrP and carrying the same His-tag , were toxic to the neurons ( Figure 2A and data not shown ) . To understand the type of neuronal death induced by these oligomers , the cells were analyzed morphologically using nuclear staining . Neuronal cultures treated with murine or ovine PrP oligomers ( Figure 2F ) revealed a high quantity of cells exhibiting condensed and fragmented chromatin , a hallmark of apoptosis . To identify the domains of PrP oligomers accountable for the observed toxicity , we occluded different regions of PrP oligomers by incubating them with a series of domain-specific PrP antibodies . Neurons exposed to murine or ovine PrP oligomers were fully protected against cell death using the monoclonal antibody Pri303 directed against the domain 106–126 of PrP ( Figure 3 and data not shown ) . In contrast , incubation with the PrP monoclonal antibodies SAF84 ( aa 161–170 ) , Pri917 ( aa 217–221 ) , or SAF32 ( aa 59–92 ) had no protective effect . These data show that the exposure of hydrophobic domain of PrP at the surface of the PrP oligomers is required for the neurotoxic mechanism . The effect of the various antibodies was similar on neurons expressing PrP or not ( Figure 3 ) , confirming in an independent experiment that PrP oligomers are toxic to primary neurons regardless of the expression of PrPc , and showing that the prevailing neurotoxic mechanism can not be counteracted by endogenous PrPc present at the cell surface . We then wanted to determine whether toxicity was limited to oligomeric PrP species or if PrP fibrils could also be toxic . We established that aging of PrP oligomers ( a temperature-dependent process , taking from minutes at 50 °C to one month at 4 °C ) led to their polymerization into PrP fibrils . Figure 4A shows by electron microscopy that PrP oligomers exhibit a mixed granular and protofibrillar structure , while aged preparations form long mature fibrils 15 nm in diameter . These fibrils had amyloid properties as they strongly bound to thioflavine T ( Figure 1E ) ; they also showed enhanced PK resistance when compared to the PrP oligomers ( not shown ) . Toxic PrP oligomers were soluble in sodium acetate , whereas aged PrP proteins were insoluble ( Figure 4C , compare young and aged in the pellet fraction-P- ) . Fibrillar PrP preparations were not toxic , in contrast with oligomeric PrP ( Figure 4B ) . To investigate the toxicity of different forms of PrP in vivo , stereotaxic subcortical injections of oligomeric or fibrillar PrP were carried out in the right hemispheres ( ipsilateral ) of C57BL/6 PrP+/+ or C57BL/6 PrP0/0 mice , and monomeric PrP or buffer alone was injected in the left hemispheres ( contralateral ) . Table 1 and Figure 5 describe the experiments performed with ovine PrP preparations . The injection scheme is summarized in Table 1 . Figure 5A shows the precise site of injection , just above the CA2 region of the hippocampus . The effect of the PrP preparations on neuronal toxicity was examined 24 h post-injection . The whole brains were sectioned and carefully screened for toxicity by gallocyanine staining , even though toxicity was detected only at the expected site in the CA2 region of the hippocampus . No toxicity was observed in mouse brains injected with buffer alone or PrP monomers ( Figure 5C , 5E , 5G , and 5I ) . PrP oligomers were highly toxic in both PrP-expressing and non-expressing mice , leading to an almost complete destruction of the pyramidal layer of neurons in the hippocampal region underneath the injection site ( Figure 5D and 5H ) . Murine PrP oligomers were as toxic as ovine PrP oligomers ( not shown ) . In vivo , PrP fibrils were also toxic but to a markedly milder extent than PrP oligomers ( Figure 5B and 5F ) . To see if the neurons were dying by apoptosis , the cells were labeled with ApopTag BrdU that binds to DNA breaks , a hallmark of apoptosis . As seen in Figure 6J and 6K , hippocampal neurons exposed to the toxic PrP oligomers exhibited intense BrdU labeling , which indicates that the neurons underwent apoptosis . Furthermore , the levels of BrdU labeling also provided a direct comparison of the level of toxicity of PrP oligomers versus PrP fibrils , showing again that the oligomers were more toxic than the fibrils . In summary , these data show in vivo that soluble particles of PrP oligomers exert a high intrinsic neurotoxicity , whereas large PrP fibrils exhibit low neurotoxicity , both independently of endogenous PrPc expression . There is a growing belief that intermediates in the formation of the protease-resistant prion protein PrPsc ( sometimes referred to as PrP* [25] ) , rather than PrPsc itself , are the pathogenic forms of PrP [10 , 11 , 13 , 14] . Moreover , there is evidence from other brain amyloidoses that soluble oligomeric forms of the disease-associated protein constitute the neurodegenerative trigger [21–24] . We tested this hypothesis using oligomeric ß-sheeted PrP preparations . Throughout the study , we used two different types of PrP preparations in order to obviate a possible bias due to the method of oligomer preparation . One was a murine tandem PrP construct that spontaneously formed oligomers , while the other was an ovine PrP , the oligomerisation of which was induced by thermal refolding into ß-sheeted PrP . Both have been characterized and used in previous studies [36 , 39] . We observed remarkably similar results with both types of oligomers in all the different experiments performed throughout this study . These oligomers were soluble in physiological buffers , showed mild PK resistance , and aggregated into insoluble amyloid fibrils upon aging , therefore resembling presumed PrPc to PrPsc conversion intermediates . We first showed that ß-PrP oligomers , but not α-PrP monomers , are toxic to cortical neurons in culture , in accordance with previous studies [32 , 33] . They were approximately 30 times more toxic than PrP peptides ( Figure 2E and [18] ) . We did not observe a species-specific effect of murine versus ovine oligomers , suggesting that the main toxicity mechanism does not depend on a homologous interaction between PrPc and the PrP oligomers . In fact , the toxicity was completely independent of endogenous PrP expression by the neurons ( Figure 2 ) . The toxic effect of the ß-PrP oligomers in PrP+/+ and PrP0/0 neurons could be reversed by blocking the 106–126 hydrophobic stretch of PrP with the Pri303 antibody , suggesting a direct role of this region in the toxicity . We have previously demonstrated the higher accessibility of hydrophobic clusters at the surface of our ß-PrP oligomers by 1-anilino 8-naphthalene sulfonic acid ( ANS ) fluorescence probing [36] . It is a phenomenon common to protein misfolding [40] , and other authors have shown that the hydrophobic stretch 90–120 of PrP is available for antibody binding in ß-oligomers [28] . Moreover , we have data ( not shown ) suggesting that ß-PrP oligomers undergo an increased cellular uptake . One possible explanation is that the hydrophobic surface of the PrP oligomers favors their insertion into the lipid bilayer . This finding is in accordance with studies using PrP peptides encompassing the hydrophobic PrP domain , showing that they insert metastably into membranes and are toxic independently of PrPc expression [18 , 19] . Interestingly , the SAF84 antibody actually increased the toxicity of the PrP oligomers . This effect is not linked to its binding to cell surface PrPc , since it was observed in PrP-expressing and non-expressing cells . Because SAF84 binds to the S2-H2 hinge loop involved in the oligomerization process [41] , a possible hypothesis is that it facilitates PrP oligomerisation and hence increases the toxicity . Upon aging , toxic ß-PrP oligomers assembled into insoluble fibrils that were not toxic on our primary cultures of cortical neurons . This finding is in accordance with the fact that the soluble , non-fibrillar amidated version of the hydrophobic PrP 106–126 peptide is toxic [42] and with the emerging view that the pathogenesis of amyloidotic diseases is related to soluble oligomeric species rather than to high molecular weight protein assemblies [21 , 24] . We then wanted to verify in vivo the relevance of our in vitro findings . We performed stereotaxical injections of either the control solution , PrP monomers , PrP oligomers , or PrP fibrils in the supra-hippocampal region of C57BL/6 PrP+/+ or C57BL/6 PrP0/0 mice ( Figure 5 ) . First , we confirmed that ß-PrP oligomers are highly toxic in vivo , both in PrP expressing or non-expressing mice . Like the in vitro experiments , the vehicle solution and α-PrP monomers were not toxic to the neurons in vivo . As a comparison , 10 μg of the 118–135 PrP peptide was toxic in vivo to retinal neurons after intravitreal inoculation [43] . Second , we found that PrP fibrils were toxic in vivo , but clearly less toxic than ß-PrP oligomers . The same phenomenon was observed in PrP+/+ and PrP0/0 mice . This is clearly shown in Figure 5 by the differences in the extent of neuronal damage in the hippocampal cell layer and by the difference in BrdU labeling for apoptosis . The fact that PrP fibrils revealed some toxicity in vivo but not in vitro may be due to a different level of sensitivity of the neuronal subpopulation examined in either case ( hipocampal versus cortical neurons ) , as well as an amplification of toxicity in vivo due to the presence of glial cells in the brain . Another explanation may be that , in vivo , the fibrils were partially broken down into smaller , more toxic aggregates . Another study showed in vitro that the toxicity of PrP oligomers and fibrils was dependent on the expression of PrP [33] , suggesting the existence of alternative pathways of toxicity . Interestingly , the PrPc dependency of the PrP-induced toxicity has always been a matter of debate [17 , 44–46] . However , because these authors also observed a different toxicity behavior of their PrP fibrils in vitro than we did , we reason that all these differences may be due to the fibrils corresponding to different variants of supramolecular PrP assemblies . These variants would expose differently their reactive interface and thus react differently with the cell surface . Different shapes of PrP fibrils might be related with the “prion strain” phenomenon , causing the brain to degenerate more or less rapidly and triggering the death of different subset of neurons . Hence , apparent differences between our in vitro study and that by Novitskaya et al . teaches us that we may be revealing only different components of the very complex phenomenon of neurodegeneration induced by amyloidotic proteins . Therefore , while the dissection of mechanisms in vitro is obviously important , in vivo approaches constitute the only way to assess their overall effect on the brain . In vivo , endogenous PrP is required to generate PrP oligomers , but , as shown by our experiment where we have externally provided the toxic PrP species to PrP0/0 cells , not to induce neuronal death . This is also in accordance with findings in a transgenic mouse model where prion replication and death of PrP0/0 neurons occurred by exclusive astrocytic prion release [46] . In another study , conditional suppression of PrPc expression in neurons during murine prion infection led to a halt in the neurodegenerative process and behavioral alterations [47 , 48] . In this model however , even if PrPsc continued to accumulate , it was found restricted to astrocytes , and the absence of supply of toxic PrP species in the vicinity of neurons was probably key to the neuroprotective effect . Our in vivo findings are in accordance with the emerging consensus that during prion diseases , small undetectable PrP aggregates , rather than plaque-type PrP deposits , are responsible for neuronal dysfunction and death . This is supported by the lack of correlation between neuronal death and the observation of PrP plaques in vivo [9 , 49 , 50] . Moreover , highly aggregated extracellular deposits of PrP in scrapie-infected “anchorless” transgenic mice exhibit very low toxicity , if any at all [51] . Even if not toxic , this amyloid PrP or another yet unknown component is infectious , as evidenced by transmission to wild-type mice . Interestingly , another recent study suggests dissociation also beteween the presence of Prp amyloid and prion infectivity [52] . In a previous study where focal PrPsc aggregates where found in PrP0/0 mice grafted with PrP+/+ tissue , no toxicity was observed , possibly due to the aggregation state of the PrPsc detected by immunohistochemistry [45] . The finding that soluble PrP oligomers , preceding the formation of PrP fibrils , are the main neurotoxic species in vivo , assigns prion diseases to the group of other brain amyloidoses , like Alzheimer and Parkinson disease , with regard to their mechanism of neurodegeneration [7] . The commonality of this mechanism is remarkable . It involves a conformational change of the protein monomer , leading to the formation of soluble aggregates , which become insoluble as the protofilaments grow into amyloid fibrils . An antibody recognizing common structural elements from different cytotoxic oligomers was able to inhibit their cellular toxicity , hinting at a commonality also in the primary targets of toxicity [22] . Because some amyloid proteins , like Aß , are located in the extracellular space , whereas others ( α-synuclein ) are cytosolic , it is likely that cell membranes that are accessible from both compartments constitute one of these targets . The early prefibrilar aggregates of HypF-N ( a disease-unrelated protein used as a model to study aggregate-forming , pathogenic proteins ) were shown to be able to permeate synthetic phospholipid membranes [53] . Recently , the physical mechanism of toxicity associated with the intermediate-size Aß peptide oligomers was found to be the formation of conducting pores in lipid bilayers [54] . Figure 6 reviews the most probable scenarios of PrP-induced toxicity , showing how our data feed into the context of earlier findings . In this model , the toxicity of the PrP oligomers would be 3-fold : the first scenario is linked to the conformational change of oligomeric PrP , resulting in the loss of the N-terminal flexibility in the oligomers , which thereby mimic the effect of ΔPrP constructs described in earlier studies ( Figure 6 , #3 and #4 ) ; the second is the membrane insertion and destabilization of PrP oligomers , similar to the effects of PrP peptides ( Figure 6 , #5 ) ; and the third relates to the intracellular effects of PrP oligomers , comparable to those described with cytoplasmic PrP ( mainly Figure 6 , # 6 ) . In normal cells , PrPc is thought to convey a survival message by interacting with a cell surface ligand , LPrP . Several studies have shown that the PrPc binding domain is located in the structured core of the protein while the activating domain is in the flexible N-terminus of the protein [20 , 55–57] ( Figure 6 , #1 ) . One of the scenarios proposed is that in PrP0/0 mice , a hypothetical functional homologue of PrP ( π ) binds to LPrP and transduces the signal ( Figure 6 , #2 ) . However , PrP0/0 mice engineered to express an N-terminally truncated PrP , or a PrP truncated in the most C-terminal part of the flexible domain ( ΔPrP ) or Doppel ( a protein of the PrP supergene family that lacks the N-terminus equivalent of PrP ) , harbor a neurotoxic phenotype , because Doppel and ΔPrP bind to LPrP with higher affinity than π but lack the domain responsible for the transduction of the survival message ( this is the so-called Shmerling or Doppel effect; Figure 6 , #3 ) . In PrP oligomers , the N-terminus of PrP is thought to be buried [36] and hence the oligomers would behave similarly to Doppel or ΔPrP with regard to their interaction with LPrP ( Figure 6 , #4 ) . Cellular uptake of PrP oligomers is likely to induce intracellular toxicity by the accumulation of protein oligomers at the mitochondrial membrane , resulting in the release of cytochrome C and subsequent activation of the apoptotic cascade ( Figure 6 , #7 ) , as suggested for Parkinson and Alzheimer diseases [58] . Finally , it has been shown that a highly concentrated intracellular abnormal PrP species is likely to end up accumulating in the aggresome/proteasome system [59 , 60] . Increased uptake and intracellular accumulation of PrP oligomers is likely to saturate intracellular degradation pathways like the proteasome , thereby triggering the apoptotic cascade ( Figure 6 , #6 ) . The latter neurotoxic mechanism would also explain why most amyloid diseases are associated with old age , when there is likely to be an increased tendency of proteasome dysfunction and for proteins to become misfolded or damaged , in conjunction with the reduced efficiency of the molecular chaperone and unfolded protein responses [61 , 62] . The present study establishes ß-PrP oligomers as a major neurotoxic species in vitro and in vivo , which likely represents the culprit PrP* responsible for the development of transmissible spongiform encephalopathy–linked neurodegeneration . Targeting ß-PrP oligomers , and their hydrophobic domain in particular , will allow researchers to devise rational neuroprotective treatments for these highly debilitating diseases . The recombinant proteins used in this study were a monomeric mouse PrP sequence ( 23–231 ) , a mouse tandem PrP composed of two monomeric sequences linked head to tail from the carboxy terminal to the amino terminal by a linker ( flexible sequence ) to allow for proper folding of the dimer , an α-helical sheep PrP , and a ß-sheeted version of the sheep PrP . The grb-2 protein and the linker sequence flanked at both sides by ten amino acids of the PrP sequence were used as control proteins . Tandem PrP consists of two covalently linked murine PrP sequences without N- and C-terminal signal peptides . This recombinant protein was expressed and purified as previously described [41] . The proteins were stored at −20 °C in their elution buffer ( 8 M urea , 20 mM sodium phosphate , 500 mM sodium chloride , 500 mM imidazole , [pH 6 . 3] ) until needed ( see below ) . The ovine PrP full-length protein was purified as described previously [64] . Briefly , the gene encoding the full-length ARQ variant ( A136 R154 Q171 ) was cloned in pET 22b+ and expressed by IPTG induction in the Escherichia coli BL21 DE3 strain . After lysis , sonication , and solubilization of the inclusion bodies with urea , purification and renaturation of the prion protein were performed on an Ni Sepharose column by heterogeneous phase renaturation , taking advantage of the intrinsic affinity of the full-length protein for Ni . For conversion , PrP ( pH 7 . 2 in 20 mM MOPS ) was heated at 72 °C for 15 min and cooled to room temperature . Fourier transform infrared spectra confirmed that in these conditions , PrP forms oligomeric ß-sheeted PrP . The characterization and mechanism of formation of these ß-sheeted oligomers is published elsewhere [36] . Briefly , they form discrete 12-mer and 36-mer species , are oblate-shaped , have distinct secondary structure features , and display exposures of hydrophobic clusters . The synthetic peptides used in this study were mouse PrP 105–132: KTNLKHVAGAAAAG-AVVGGLGGYMLGSA and mouse PrP scrambled 105–132: NGAGKAGMVGLYGAHG-ATAKVSLVGALA . They were prepared as described in [18] . Mouse proteins were stored at −20 °C in their elution buffer ( see above ) . The proteins were dialyzed just before use against ultrapure water or 10 mM sodium acetate ( pH 4 . 5 ) , and the concentration was obtained by the micro BCA protein assay . The sodium acetate did not affect the pH of the culture medium or the viability of the neurons at the dilutions used . Sheep PrPs were produced just before use and kept at 4 °C for a maximum of 30 d . PrP+/+ mice used in this study were wild-type C57BL/6 mice . PrP0/0 mice were obtained by backcrossing PrP knockout mice , kindly provided by Charles Weissmann , with C57BL/6 mice over nine generations , and are therefore named C57BL/6 PrP0/0 mice . Primary cortical cells were extracted from 15-d-old mouse embryos . Cortices were dissected under a binocular microscope in Ca2+/Mg2+-free PBS ( Invitrogen , http://www . invitrogen . com/ ) supplemented with glucose at a final concentration of 3% . Then , they were carefully freed of meninges and incubated in trypsin/EDTA solution ( Eurobio , http://www . eurobio . fr/ ) for 10 min at 37 °C . The trypsin was removed and the leftover was inactivated with DMEM ( Dulbecco's Modified Eagle's Medium , Invitrogen ) containing 4 . 5 g/l glucose , Glutamax-I , and 1% FCS ( fetal calf serum , Invitrogen ) . Cells were then mechanically dissociated using a flame-narrowed Pasteur pipette in the same culture medium . The cell suspension was then centrifuged and the pellet resuspended in DMEM supplemented with B27 ( Invitrogen ) and 3% FCS . Cells were seeded on plates coated with 10 μg/ml of poly-D-lysine ( Sigma , http://www . sigmaaldrich . com/ ) initially in DMEM supplemented with B27 ( 2% ) , FCS ( 3% ) , and 100 U/ml penicillin/streptomycin . After 2 d , the culture medium was replaced by serum-free DMEM containing N2 supplements ( 1%; Invitrogen ) and penicillin/streptomycin . Cultures were kept in a 37 °C water-saturated incubator at 5% CO2 . Female C57BL/6 PrP+/+ and C57BL/6 PrP0/0 mice ( see paragraph above ) were anesthetized with isoflurane ( 1%–2 . 5% ) and positioned on a stereotaxic frame . Once the bregma was identified and holes drilled , 2 μl of 1 mg/ml of various PrP preparations or the same volume of buffer were injected into the hippocampus of the ipsi and controlateral hemispheres ( 1 . 5 mm posterior , +/−2 . 00 mm lateral , and 1 . 75 mm ventral to bregma , Figure 5A ) at a rate of 0 . 4 μl/min . The animals were killed by cervical dislocation at 24 h post-injection . The brains were dissected out , fixed in 4% buffered paraformaldehyde , and paraffin embedded . For the visualization of the neurons , 5-μm horizontal sections from the mid-brain region were stained for nucleic acids with gallocyanine according to standard protocols . To test for apoptosis , adjacent sections of selected brain sections were analyzed with the ApopTag BrdU kit according to the manufacturer's instructions ( Molecular Probes , http://probes . invitrogen . com/ ) . Slides were examined on an epifluorescence Zeiss microscope ( http://www . zeiss . com/ ) . All animal experiments were performed in accordance with national and European Union ( EU ) regulations . Analysis of PK resistance was performed by incubating 10 μg/ml of each protein for 15 min in the presence of various concentrations of PK at 37 °C . The samples were then precipitated with four volumes of methanol , resuspended in the loading buffer , and analyzed by western blot with the monoclonal antibodies 8G8 and Pri917 for the ovine and mouse PrP samples , respectively . For toxicity monitoring , cells were seeded at a density of 7 × 104 cells per wells in a 96-well poly-D-lysine–coated plate ( in each plate , only the 60 wells in the center contained cells and the outer wells were filled with PBS to prevent any drying ) . After 5 d in culture , neurons were incubated with the different recombinant PrP proteins for 72 h . In order to keep steady culture medium concentrations , the proteins were diluted in 2× culture medium and the proper volume of water and vehicle solution were added to get a final concentration of 1× . For controls , the cells were left untreated or were exposed to an equivalent volume of vehicle solution . After exposure of the neurons to the proteins , the viability was measured either with MTT or with WST-1 . For MTT , the medium was replaced with 500 μg/ml of 3 , [4 , 5 dimethylthiazol-2yl]-2 , 5 diphenyltetrazolium bromide ( MTT; Sigma ) dissolved in PBS . After 2 h of incubation at 37 °C , the solution was removed and the blue formazan was solubilized with an isopropanol/HCL 1N ( 92:8 ) solution . Then , the optical density was measured at 540 nm with a reference wavelength of 630 nm . For WST-1 ( Roche , http://www . roche . com/ ) , 10 μl of the reagent was added directly to the culture medium containing the cells and incubated for 1 . 5 h . Then , optical density measures were taken at 450 nm against a reference wavelength of 630 nm . In this case , a negative control , consisting of DMEM without cells , was used and subtracted from all samples . This was performed by staining cell nuclei with Hoechst 33342 . Cells were seeded in poly-D-lysine-coated 8-well Labtek ( Labtek II; Nalgene Nunc International , http://www . nalgenunc . com/ ) culture dishes at a density of 1 . 6 × 105 cells/wells . After treatment with the recombinant proteins , the cells were mounted with Vectashield ( Vector Laboratories , http://www . vectorlabs . com/ ) supplemented with 5 μg/ml of Hoechst 33342 reagent ( Molecular Probes ) . The slides were visualized using an axiovert ( Zeiss ) fluorescence microscope . All monoclonal PrP antibodies used in this study have been purified with Protein-A or Protein-G affinity columns and dialyzed against ultra-pure water . These steps were carried out to remove growth factors and anti-microbial agents from the antibody solutions . Antibodies were added directly to the culture media containing the recombinant proteins of interest . Then these were incubated with the cells for 72 h . All protein samples were first added ( 0 . 2–1 . 5 mg/ml ) to serum-free DMEM containing N2 supplements ( to be in the same conditions as the neurotoxicity experiments ) and incubated for 2 h at 37 °C . Following this step , a 10-μl aliquot of protein preparation was applied to formar- and carbon-coated grids . The excess fluid was drained with filter paper and the sample was stained for 1 min with 2% uranyl acetate . The grid was air-dried and examined in a Philips EM CM120 at 80 kV at a magnification of 15–75000 . Young and aged PrP dimers were centrifuged at 100 , 000g for 1 h and the supernatant was separated from the pellet . The PrP was then visualized by western blot with the antibody 4H11 . Thioflavine T fluorescence mesurements were performed at 20 °C on a Jasco 6200 spectrofluorimeter ( http://www . jascoint . co . jp/ ) with a 1 mm × 10 mm optical path-length cuvette . The concentation of protein was adjusted to 15 μM ( equivalent monomer ) for each species before incubation with 15 μM thioflavine T . Excitation was performed at 432 nm .
Prion diseases are transmissible neurodegenerative diseases caused by an infectious agent thought to be composed mainly of a host protein , the prion protein ( PrP ) . The mechanisms of neurodegeneration prevailing in these diseases are not well understood . In the present study , we demonstrate that small PrP aggregates , called oligomers , cause the death of neurons in culture and after injection in vivo . On the contrary , larger PrP aggregates , visualized as fibrils by electron microscopy , do not cause the death of cultured neurons and are much less toxic than PrP oligomers in vivo . We propose that the PrP oligomers exert their toxicity by disturbing neuronal membranes , as well as by an excessive intracellular concentration leading to the generation of death signals ( also called apoptotic signals ) by the cell . Moreover , the use of antibodies recognizing a certain portion of the PrP oligomers could prevent neuronal death . This study assigns prion diseases to the same group of diseases as Alzheimer disease , in which protein oligomers constitute the major trigger of the neurodegenerative process , and suggests new possible neuroprotective approaches for therapeutic strategies .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "neurological", "disorders", "eukaryotes", "vertebrates", "mus", "(mouse)", "animals" ]
2007
In Vitro and In Vivo Neurotoxicity of Prion Protein Oligomers
In Mozambique , schistosomiasis is highly endemic across the whole country . The Schistosomiasis Consortium for Operational Research and Evaluation ( SCORE ) coordinates a five-year study that has been implemented in various African countries , including Mozambique . The overall goal of SCORE was to better understand how to best apply preventive chemotherapy with praziquantel ( PZQ ) for schistosomiasis control by evaluating the impact of alternative treatment approaches . This was a cluster-randomised trial that compared the impact of different treatment strategies in study areas with prevalence among school children of ≥21% S . haematobium infection by urine dipstick . Each village was randomly allocated to one of six possible combinations of community-wide treatment ( CWT ) , school-based treatment ( SBT ) , and/or drug holidays over a period of four years , followed by final data collection in the fifth year . The most intense intervention arm involved four years of CWT , while the least intensive arm involved two years of SBT followed by two consecutive years of PZQ holiday . Each study arm included 25 villages randomly assigned to one of the six treatment arms . The primary outcome of interest was change in prevalence and intensity of S . haematobium among 100 children aged 9-to-12-years that were sampled each year in every village . In addition to children aged 9-to-12 years , 100 children aged 5–8 years in their first-year of school and 50 adults ( aged 20–55 years ) were tested in the first and final fifth year of the study . Prevalence and intensity of S . haematobium infection was evaluated by two filtrations , each of 10mL , from a single urine specimen . In total , data was collected from 81 , 167 individuals across 149 villages in ten districts of Cabo Delgado province , Northern Mozambique . Overall PZQ treatment resulted in a significant reduction in the prevalence of S . haematobium infection from Year 1 to Year 5 , where the average prevalence went from 60 . 5% to 38 . 8% , across all age groups and treatment arms . The proportion of those heavily infected also reduced from 17 . 6% to 11 . 9% over five years . There was a significantly higher likelihood of males being infected than females at baseline , but no significant difference between the sexes in their response to treatment . The only significant response based on a study arm was seen in both the 9-to-12-year-old and first-year cross sections , where two consecutive treatment holidays resulted in a significantly higher final prevalence of S . haematobium than no treatment holidays . When the arms were grouped together , four rounds of treatment ( regardless of whether it was CWT or SBT ) , however , did result in a significantly greater reduction in S . haematobium prevalence than two rounds of treatment ( i . e . with two intermittent or consecutive holiday years ) over a five-year period . Although PC was successful in reducing the burden of active infection , even among those heavily infected , annual CWT did not have a significantly greater impact on disease prevalence or intensity than less intense treatment arms . This may be due to extremely high starting prevalence and intensity in the study area , with frequent exposure to reinfection , or related to challenges in achieving high treatment coverage More frequent treatment had a greater impact on prevalence and intensity of infection when arms were grouped by number of treatments , however , cost efficiency was greater in arms only receiving two treatments . Finally , a significant reduction in prevalence of S . haematobium was seen in adults even in the SBT arms implying the rate of transmission in the community had been decreased , even where only school children have been treated , which has significant logistical and cost-saving implications for a national control programme in justifying CWT . Schistosomiasis is a major yet neglected public health problem , second only to malaria in terms of parasite-induced human morbidity and mortality worldwide [1] . Estimates show that globally at least 218 million people required preventive treatment in 2015 [2–4] , and at least 20 million suffer from severe and debilitating forms of the disease [5] . Schistosomiasis is a major public health problem in Mozambique , as shown by an epidemiological survey of schistosomiasis and soil-transmitted helminthiasis among school children carried out between 2005 and 2007 [6] . The mean estimated prevalence of urogenital schistosomiasis , Schistosoma haematobium , was 47% while that of intestinal schistosomiasis , S . mansoni , was much lower ( around 1% ) across all of Mozambique . In Cabo Delgado province , the area where this study took place , the prevalence of S . haematobium was 57 . 9% , ranging from 8 . 8% on the coast to 93% inland [6] . In 2001 , the World Health Organisation ( WHO ) endorsed preventive chemotherapy ( PC ) as the global strategy to control morbidity due to schistosomiasis through regular treatment with praziquantel ( PZQ ) [7] . Treating all school-aged children ( SAC ) is more cost-effective than a test-and-treat approach [8 , 9] , which is achieved by allocating a geographic area ( typically the district ) to a recommended WHO treatment category for schistosomiasis based on infection prevalence [7] . As a result , most programmes control morbidity associated with schistosomiasis through school-based deworming , as it is highly cost-effective [10] . However , the limitation of this approach is poor coverage among out-of-school children , particularly older children and those living far from schools , and neglecting children younger than four years and adults [11] . Studies have highlighted the advantages of a community-wide treatment ( CWT ) approach in addition to a school-based treatment ( SBT ) in reducing prevalence and intensity of schistosomiasis infection , particularly in communities where not all children attend school [11–15] . Furthermore , questions remain about optimal frequency of PZQ treatment for infection and morbidity control . It has been observed in some studies that more frequent dosing can improve reductions in worm burden and increase parasitological cure , particularly where schistosomiasis is highly endemic [16] . Whereas others have shown that a single dose of PZQ results in sustained low transmission of S . haematobium for two years [17] . The Schistosomiasis Consortium for Operational Research and Evaluation ( SCORE ) was established in 2008 to answer strategic questions about schistosomiasis control [18] . It includes multi-country field studies that aim to understand the benefits and costs of alternative approaches to PC involving CWT , SBT and “drug holidays” ( i . e . years without PC ) . The gaining and sustaining SCORE study protocol and baseline characteristics have been described elsewhere [18–21] . The primary research question presented here is which strategy for PC provided the greatest reduction in prevalence and intensity of S . haematobium infection among 9-to-12-year olds after four years of intervention in Cabo Delgado , Northern Mozambique . In addition , the impact of treatment on first-year students and adults sampled in each village was also assessed . These findings will provide an evidence base for the Mozambique national control programme for schistosomiasis to address strategic questions about schistosomiasis treatment and potentially shift from morbidity control to interruption of transmission , and subsequently elimination . This study was a parallel cluster-randomised , intervention trial with six study arms ( Fig 1 ) . Communities received various combinations of CWT , SBT or drug holiday over a four-year period , with the final round of data collection carried out 12 months after Year 4 treatment . All communities received CWT directly after Year 5 data collection , as they were no longer participating in the trial . The most intensive intervention arm involves four years of CWT ( Arm 1 ) , whilst the least intensive treatment strategy was two years of SBT PC followed by two consecutive years of drug holidays ( Arm 5 ) . The area for this study was 10 out of 17 districts of Mozambique’s northern most province , Cabo Delgado . The area was chosen as previous mapping had shown a high prevalence of S . haematobium and a low prevalence of S . mansoni , as one of the country selection criteria was no mixed infections to ensure that species type did not confound response to a particular treatment strategy [18] . Communities to be included in the study were determined by convenience sampling based on three criteria: ( i ) selecting only villages that had a primary school ( so that it could be randomised to SBT ) , ( ii ) village and school had no history of PC using PZQ against schistosomiasis , ( iii ) and the village has a school attended by a minimum of 100 children aged 9-to-12-years . Given that children who test positive must be treated , the eligibility survey was carried out among fifty 13-to-14-year olds in each village , therefore treating those infected did not affect subsequent study results , especially where prevalence was high [18] . The starting prevalence of S . haematobium was evaluated by reagent strip testing for microhaematuria on a single mid-day urine ( communities were eligible only if ≥21% by urine dipstick was detected ) [22] . A total of 150 communities found eligible were randomly assigned using a computer-based randomisation procedure , without stratification , to one of the six study arms . Since the rainy season lasts from November to April , data were collected between July and October each year to omit seasonal variation . A door-to-door census was conducted prior to treatment in Year 1 in all selected communities to provide a baseline for estimating coverage . The aim was to enrol 25 villages per study arm , and to monitor each village’s prevalence and intensity of S . haematobium infection among 100 school children aged 9-to-12-years . In each school , 50 boys and 50 girls were selected using systematic random sampling from those in the second , third and fourth classes . A total of 150 villages were enrolled , with 15 , 000 children tested each year . Parasitological data were collected prior to treatment from Year 1 through to Year 5 . To evaluate the effect of treatment holidays , currently recommended by WHO PC guidelines whereby moderate-risk communities are treated once every two years [7] , no testing of children was conducted during holiday years as children who were found to be infected would have needed to be treated . Sample size calculations assumed treatment interventions would reduce schistosomiasis prevalence in high endemicity areas from 50% in Year 1 to 15% by the end of the study in the most intense treatment ( Arm 1 ) . Power computations used generalized estimating equations to fit a logistic regression model that included treatment arm and time effects and treatment-by-time interaction , and assumed an over-dispersion parameter of φ = 5 . 0 . The minimum effect size was computed so that a difference over time could be detected with 90% power for a 2-sided α = 0 . 05 level test . Negligible correlation was assumed between variables in Year 1 and at study conclusion . Based on these assumptions , the calculations estimated that studying 25 villages per arm and 100 children per village were sufficient to detect an overall difference between arms of 11 . 4% prevalence at the conclusion of the study . In addition to children aged 9-to-12-years , systematic random sampling was used in each village to select 100 first-year students ( aged 5-to-8-years old ) and a convenience sample of 50 adults ( aged 20-to-55-years ) in the first and fifth years only . In each school , selected children were given a plastic pot labelled with an adhesive barcode with unique identification numbers and asked to provide a single urine specimen . The sex , age , and school class for each child were recorded . All samples were collected between 10am and 2pm and examined immediately in the school . Two filtrations of 10mL each were carried out on a single urine sample using a nylon filter with a pore size of 20µm ( Sefar AG; Heiden , Switzerland ) [23 , 24] . Both filters were examined for S . haematobium eggs under a light microscope and number of S . haematobium eggs were counted . All parasitological examinations were performed by trained laboratory technicians . For quality control , around 10% of all microscope slides were re-examined by a senior technician . The intensity of infection was expressed as the number of eggs per 10mL of urine filtered . For specimens of less than 10 mL , the volume of urine filtered was measured and the number of eggs per 10mL calculated . If estimated counts were above 1 , 000 eggs per 10mL , they were truncated at 1 , 000 . The arithmetic mean of two filtrations taken from a single urine specimen was calculated to be the egg count of the child [25] . A child was deemed egg positive if one or more eggs were found in any of the slides examined . Praziquantel tablets were delivered at approximately 40mg/kg using a WHO dose pole [26] . All treatment was carried out in the village on the same day as sampling whereby everyone was treated regardless of their parasitological results , which were anonymous . During SBT , directly-observed treatment with PZQ was administered by trained teachers to all children attending school . Efforts were made to treat non-school attendees through community sensitisation and mobilisation efforts . CWT involved providing treatment to the entire eligible population using community drug distributors either door-to-door or at fixed points in the study community , which only excluded children under 4 years of age or under 94 cm in height . Everyone who had taken the medication in SBT was monitored for adverse events for four hours after treatment , since the analysis was carried out in the school . In the CWT , since the drug distributor lives in the village they were available in the community . At baseline ( Year 1 ) a census was carried out in all selected communities of the total population and proportion of all SAC ( aged 5-14-years ) recorded in the population to provide a baseline for estimating coverage . Informed consent was obtained from all individuals ≥18 years of age and from parents or legal guardians of children less than 18 years of age . The purpose of the study was explained to all schoolchildren and verbal assent was obtained from the children . Permission was also obtained from school headmasters . Ethical clearance was obtained from the National Bio-ethical Committee for Health of Mozambique ( NBCHM ) , and the survey was conducted according to NBCHM guidelines ( reference no . IRB00002657 ) . The trial is registered with the International Standard Randomised Controlled Trial registry under ISRTC number 14117624 for Mozambique . The study protocol was also approved by Imperial College London ( ICREC_10_2_2 ) . Demographic data were collected on smartphones and uploaded to a dedicated database maintained on a central server ( EpiCollect at Imperial College London ) . Laboratory data were collected on paper forms and entered onto the smartphone retrospectively using the barcode with unique identification number to link with the individual’s demographic information . The electronic data capture system involved entering data in the field , synching the data to a central server and downloading the data retrospectively for cleaning and analysis . Data cleaning and management was carried out by biostatisticians at the Schistosomiasis Control Initiative ( SCI ) . Data analysis was performed using R version 3 . 2 ( R Core Team ( 2013 ) : R: A language and environment for statistical computing . R Foundation for Statistical Computing , Vienna , Austria ) . Since 9-to-12-year olds are the only age group to be consistently sampled from baseline to Year 5 , the primary research question presented here is which strategy for PC provided the greatest reduction in prevalence and intensity of S . haematobium infection among 9-to-12-year olds after four years of intervention . In addition , the impact of treatment on first-year students and adults have also been reviewed and analysed . Individuals without data on age , sex , and presence or absence of eggs on at least one slide were not included in the study . For each year of data , three infection categories for S . haematobium infection were created: no infection , light infection ( <50 eggs/10mL of urine ) , and heavy infection ( ≥50 eggs/10mL of urine ) [7] . Indicator variables were created for infection status ( 0 = not infected , 1 = infected ) and heavy infection status ( 0 = egg count <50 , 1 = egg count>50 ) . These were averaged across each village to produce a village level prevalence and village level prevalence of heavy infected , respectively . 95% confidence intervals were calculated for village and study arm level prevalence values . Survey package [27] was used to consider survey design effects . Prevalence of infection and heavy infection was calculated as arithmetic means of the infection categories , aggregated by the relevant factors ( e . g . age , sex ) . The arithmetic mean of infection intensity was calculated using both egg positive and negative , aggregated by grouping factors ( village , study arm and gender ) . Although , mean intensity was underestimated as egg counts were capped at 1000 eggs/10mL , this was done consistently over the years therefore the trend in intensity change is believed to be valid . The egg reduction rate was calculated as the reduction in the intensity of infection assessed indirectly , using egg count via the following formula: % egg = 10mL reduction ( 1−arithmetric mean of eggs/10mL urine after treatment in Year 5 ) x 100 arithmetic mean of eggs = 10mL urine before treatment at Baseline . To assess overall population-level programmatic impact on the prevalence of S . haematobium between study arms , as per the standard analysis plan , agreed prior to analysis , Generalised Estimated Equations ( GEE ) were used to estimate the differences between arms in year 5 only; unadjusted estimates using only village and study arm as covariates and adjusted estimates including sex , age and weighting for number of children who provided data were modelled using SAS software 9 . 1 . 2 . ( SAS Institute Inc . , Cary , NC , USA ) . The models were run on the three cross-sections of data: 9-to-12-year olds , first-year students ( 5-to-8-year olds ) , and adults ( 20-to-55-year olds ) . Prevalence was modelled using a binomial GEE with logit link function with Village IDs treated as the repeated measure and ‘Lsmestimate’ used to test pre-specified differences between arms . In some villages , the enrollment was less than the target study population size . To account for this , a village-weight term was added to the GEE model to weight results according to numbers of children tested per village . Mean number of eggs per 10mL urine ( mean intensity of infection ) was modelled with negative-binomial GEE and log link function . To avoid issues of multiple testing we focused on specific arm comparisons . These comparisons were: Arm 1 ( cccc ) vs Arm 2 ( ccss ) , Arm 1 ( cccc ) vs Arm 3 ( cchh ) , Arm 1 ( cccc ) vs Arm 4 ( ssss ) , Arm 4 ( ssss ) vs Arm 5 ( sshh ) , and Arm 4 ( ssss ) vs Arm 6 ( shsh ) ( Fig 1 ) . To assess the significance of the observed reduction in prevalence of S . haematobium in adults in the SBT arms ( 4 , 5 , and 6 ) we performed a binomial Generalised Linear Mixed Model ( GLMM ) with logit link function with infection status ( 0/1 ) as the response , age ( standardised ) , sex , study arm and study year as fixed effects and village as a random effect on a subset of the parasitological data including only adults in the school based study arms for Year 1 and Year 5 . Nominal treatment coverage stipulated in the study protocol was 75% . In practice this was not achieved in many places . Despite additional data collection and considerable analytical effort , we were unable to adequately validate coverage; for this reason further analysis incorporating treatment coverage would be inappropriate . As the issues appear to be consistent throughout the study villages , the randomised allocation of villages to study arms means between arm comparisons could still have validity . Kulldorff’s space-time scan statistics were used to detect high-risk spatial clusters for schistosomiasis infection using the SatScan software version 9 . 1 . 1 . ( Information Management Services , Inc . , Boston , MA , USA; www . satscan . org ) [28 , 29] . To detect the high-risk spatial clusters of cases , the statistics use a moving elliptical window scanning the study area , and the maximum size of which is no more than 50% of the total population . We reported statistically significant clusters with an indicated p value <0 . 05 . The SaTScan program was used to obtain reported observed cases , expected cases , relative risk of infection , and locations of specific cluster . Over five years , 42 , 731 independent observations were taken of children aged 9-to-12 years from 149 communities randomly allocated across six study arms . See S1 Table for a summary of S . haematobium infection rates for each study year and study arm ( 9-to-12-year olds only ) . The results in Table 2 and Fig 2 demonstrate the impact of treatment strategy on the prevalence and proportion of heavy infection of S . haematobium for the 9-to-12-year olds at baseline and Year 5 . The initial prevalence of S . haematobium infection was 66 . 7% across all study arms for this age group , with 22 . 8% prevalence of heavy intensity of infection . Our findings show a reduction in Year 5 where S . haematobium infection decreased to 42 . 5% over all treatment arms and the proportion of those heavily infected reduced to 13 . 4% . The arithmetic mean intensity of infection at the village level , reduced over the course of the study from 69 . 1 eggs per 10ml urine to 58 . 1 eggs per 10ml , with changes in mean intensity between the study arms . The egg reduction rate from baseline to Year 5 was 13 . 5% ( Table 2 ) . Fig 3 shows the change in overall prevalence over time from the start of the project at baseline to the final Year 5 in each community across the 10 districts of the study . In both Arms 3 ( cchh ) and 5 ( sshh ) there are two consecutive years of a break in treatment ( “Holiday” ) in Years 3 and 4 , following which there was an increase in prevalence and heavy intensity . Prevalence by gender demonstrated a higher prevalence of infection , as well as a greater proportion of those heavily infected , among males ( p<0 . 001 ) ( Table 3 ) . Response to treatment was similar by gender , with both males and females showing reduced infection over time across all arms , except for Arms 3 and 5 ( Fig 4 ) . Thus , prevalence and intensity of infection appears to have increased after the treatment hiatus . The effects of treatment were analysed using Arm 1 , the most frequent and wide treatment approach , as the reference case . Arm 1 ( annual CWT ) , had a comparable impact on prevalence as the less intense Arm 6 ( SBT every two years ) . Arm 1 had a greater reduction on prevalence than Arm 2 , 3 and 4 across all years , although the difference was not statistically significant ( Table 3 ) . Arm 1 did have a significantly larger impact on S . haematobium infection than Arm 5 in Year 5 ( p<0 . 024 ) . Significance testing to assess whether the prevalence of S . haematobium varied over time between study arms showed that gender ( p<0 . 001 ) and age ( p<0 . 001 ) had a significant effect on infection status with higher prevalence and proportion of those heavily infected seen in males and among the 9-to-12-year age group in Year 5 ( Table 3 and S2 Table ) . Across study year , prevalence of infection significantly decreases over the five years ( p<0 . 001 ) with no statistically significant effect across the study arms . For the SBT arms , Arm 4 ( annual SBT ) was used as the reference arm to assess the impact of treatment holidays on prevalence . There was no significant difference seen following holidays . The impact of four versus two treatments was also assessed with the GEE model , where four treatments over four years ( for both CWT and SBT ) had a significantly greater impact in reducing prevalence of infection ( p<0 . 024 ) than two treatments over four years . There was no significant impact between the rounds of treatment and intensity of infection ( S3 Table ) . In Year 1 and 5 of the study an additional 31 , 542 observations were recorded for first-year students ( aged 5-to-8-years ) and 50 adults ( aged 20-to-55-years ) ( Table 4 ) . At baseline , examination revealed that of the 7 , 456 first-year students , 62 . 8% were infected with S . haematobium and out of 4 , 253 adults , 44 . 5% were found to be infected . The proportion of heavily infected first-year students was higher compared to adults , with 19 . 3% and 7 . 1% , respectively . In Year 5 prevalence had fallen to 39 . 3% and 26 . 4% among first-year students and adults , respectively , and proportion of heavily infected had decreased to 12 . 8% and 5 . 6% , respectively . Significance testing to assess whether the prevalence of S . haematobium differed between study arms across the first-year students and adults in Year 5 are shown in Table 3 and S4 Table . From the GEE prevalence models adjusted for age and sex , gender was a significant effect in first-students only ( p<0 . 001 ) with males displaying a higher probability of being infected than females . Increasing age was also significantly associated with infection among first-year students , with the oldest respondents ( 8 years ) being more likely to be infected than seven and six-year olds ( p<0 . 001 ) . There was no statistical association between age or sex with risk of infection in adults . For first-year students and adults , both the adjusted and unadjusted prevalence models show no significant difference in prevalence between the study arms at the end of the study . Of particular interest is the statistically significant reduction in prevalence of infection for adults from Year 1 to 5 in the SBT arms ( Fig 5 ) . Adults did not receive treatment in these arms , however , the GEE prevalence model shows no significant difference in prevalence for adult’s focal comparison arms . This would suggest that SBT alone has an impact on disease transmission . Drug coverage was defined as the proportion of individuals who have ingested the PZQ [7] . The denominator is the estimated target population . The SBT coverage was determined by the percentage of school-aged children ( 5-12-years ) that were treated , including those not enrolled in school . CWT coverage was determined by the total population treated using a denominator of the whole population based on the census carried out by the SCORE study in 2011 . Coverage by study arm for each year is outlined in Table 5 . The nominal treatment coverage stipulated by the study protocol was coverage of more than 75% for both SBT and CWT [7] , which did not occur in many communities due to suspected inaccuracies in denominator values . The results shown in Table 5 shows that SBT coverage remained consistently low over time across all arms . CWT coverage , however , did increase over time across all arms , with no significant difference seen between arms . When coverage was put into the multivariate model looking at impact on changes of prevalence over time , there was no clear trend or significant relationship with impact on infection . Delivery costs ( defined as the cost per person treated minus the drug costs ) was $0 . 31 for SBT and $0 . 36 for CWT . The relative costs by each activity and input are summarised in Table 6 . Our cost-analysis does not consider unpaid days of labour for individuals such as teachers , or other costs related to the SCORE field work . When the financial costs were broken down by activity , there was substantial cost saving for SBT for supervision and monitoring as this was carried out by the SCORE field teams during the prevalence survey . For CWT on the other hand , additional costs were incurred as supervisors were sent back to the villages post-survey to supervise and collect treatment registers . According to input costs , there was a greater cost in per diems due to additional costs of community drug distributors salary and incentives ( where one distributor was recruited for every 500 people in the village ) , whereas teachers were not paid extra in the schools but given incentives ( a t-shirt ) only . Fuel costs were also higher for CWT since the teams needed to re-visit the communities a second time to collect any left-over drugs and the treatment registers . In SBT the treatment was done on the same day as the prevalence survey and the registers taken . The additional material costs for CWT were incurred due to additional treatment registers printed for larger numbers being treated . The results obtained show that Cabo Delgado province in Northern Mozambique is highly endemic for urinary schistosomiasis . Although PC was successful in reducing the burden of active infection in all study arms , a more intense treatment approach , such as annual CWT , did not have as much impact as expected . This may be due to extremely high starting prevalence and intensity in the study area , with frequent exposure to reinfection [47] . It also may be related to poor treatment coverage and the challenge of performing a long-term study in a resource-poor setting , which may not be valid in other locations . These findings highlighted the need to complement mass drug administration with extensive public health education and behavioural modifications to reduce the risk of reinfection , and to consider the use of vector control through mollusciciding in areas where compliance to treatment proves to be challenging [38 , 48] . There is a need to explore further those individuals harbouring a high parasite burden in such highly endemic populations to understand whether they are being re-infected each year , are more likely to be non-compliant in terms of taking the treatment , or if the parasites might have developed resistance to treatment . The results of this study have also highlighted the challenge of achieving high treatment coverage especially with such highly migrant communities , specifically acquiring accurate population figures , and the importance of independent coverage surveys that do not rely on denominator values to accurately evaluate the impact of a treatment programme . Furthermore , more frequent treatment had a greater impact on prevalence of infection when arms were grouped by number of treatments , however , the costs efficiency was greater in arms only receiving two treatments . Finally , the significant reduction in prevalence of schistosomiasis among adults even in the SBT Arms implying transmission in the community has been decreased , has significant logistical and cost-saving implications for a national control programme as they challenge the justification for CWT .
Urogenital schistosomiasis is highly endemic in Mozambique . This study was part of a multi-country trial , including Mozambique , designed to understand the impact of different schistosomiasis treatment strategies involving community-wide treatment ( CWT ) , school-based ( SBT ) , and treatment holidays over a five-year period . Results from Mozambique showed that although preventive chemotherapy was successful in reducing the prevalence of Schistosoma haematobium over five-years , the most intense treatment approach , annual CWT , did not have a significantly greater impact than less intense treatment strategies , such as bi-annual SBT . Infection rates were higher among males , but there was no difference in response to treatment by gender . Four rounds of treatment ( regardless of whether it was given in the community or school ) did result in a significantly greater reduction of S . haematobium prevalence than two rounds of treatment over a five-year period . There was , however , a resurgent increase in prevalence and intensity of S . haematobium infection shown after two consecutive treatment-holiday years , implying a bounce back in infection after a two year pause in treatment . Interestingly and unexpectedly , there was a significant reduction in prevalence of schistosomiasis in adults even in communities that had received SBT implying the force of transmission in the community had been decreased , even where only school children had been treated . These findings provide an evidence-base with significant logistical and cost-saving implications for programmatic decisions on how best to gain control of Schistosoma haematobium .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "schistosoma", "invertebrates", "medicine", "and", "health", "sciences", "body", "fluids", "education", "helminths", "sociology", "tropical", "diseases", "geographical", "locations", "social", "sciences", "parasitic", "diseases", "animals", "arithmetic", "urine", "mathematics", "pharmaceutics", "neglected", "tropical", "diseases", "africa", "schistosoma", "haematobium", "schools", "people", "and", "places", "mozambique", "helminth", "infections", "schistosomiasis", "eukaryota", "anatomy", "physiology", "biology", "and", "life", "sciences", "physical", "sciences", "drug", "therapy", "organisms" ]
2017
Assessing the benefits of five years of different approaches to treatment of urogenital schistosomiasis: A SCORE project in Northern Mozambique
Viral reservoirs that persist in HIV-1 infected individuals on antiretroviral therapy ( ART ) are the major obstacle to viral eradication . The identification and definition of viral reservoirs in patients on ART is needed in order to understand viral persistence and achieve the goal of viral eradication . We examined whether analysis of episomal HIV-1 genomes provided the means to characterize virus that persists during ART and whether it could reveal the virus that contributes to treatment failure in patients on ART . For six individuals in which virus replication was highly suppressed for at least 20 months , proviral and episomal genomes present just prior to rebound were phylogenetically compared to RNA genomes of rebounding virus after therapy interruption . Episomal envelope sequences , but not proviral envelope sequences , were highly similar to sequences in rebounding virus . Since episomes are products of recent infections , the phylogenetic relationships support the conclusion that viral rebound originated from a cryptic viral reservoir . To evaluate whether the reservoir revealed by episomal sequence analysis was of clinical relevance , we examined whether episomal sequences define a viral population that contributes to virologic failure in individuals receiving the CCR5 antagonist , Vicriviroc . Episomal envelope sequences at or near baseline predicted treatment failure due to the presence of X4 or D/M ( dual/mixed ) viral variants . In patients that did not harbor X4 or D/M viruses , the basis for Vicriviroc treatment failure was indeterminate . Although these samples were obtained from viremic patients , the assay would be applicable to a large percentage of aviremic patients , based on previous studies . Summarily , the results support the use of episomal HIV-1 as an additional or alternative approach to traditional assays to characterize virus that is maintained during long-term , suppressive ART . Despite great advances in the treatment of HIV infection and disease , therapeutic eradication of viral infection is currently not possible . Individuals who respond well to ART and maximally suppress virus replication based on standard assays , harbor viral reservoirs that fuel a rapid rebound in viral replication upon interruption of antiviral treatment . Although the biological relevance of different reservoirs is subject to ongoing debate , there is evidence to support the existence of at least two distinct viral reservoirs that persist during effective , prolonged suppression of HIV-1 replication . One is a latent reservoir that is comprised of lymphocytes that were infected and subsequently reverted to a quiescent state [1]–[3] . Reactivation of latently infected cells results in viral gene expression and subsequent virion production . In patients on HAART , this reservoir has been estimated to decay with a half-life of greater than 44 months and is considered to be a major obstacle to complete clearance of HIV-1 infection [4] . In addition to latently infected cells , there is mounting evidence to support the existence of a reservoir of low-level ongoing replication in patients on HAART . Evolution of viral envelope sequences in the context of HAART has been documented for HIV-1 infected patients [5] , [6] and detection of one and two long terminal repeat circles ( episomal HIV-1 cDNAs ) in patients on HAART indicates that new rounds of infection continue despite highly suppressive treatment [7] . While short-term in vitro experiments have suggested that 2-LTR circles are stable [8] , [9] , in vivo analysis has demonstrated their labile nature , which supports the use of episomal HIV-1 cDNAs as a valid surrogate marker of recently infected cells [10]–[12] . Perhaps the most compelling evidence supporting the existence of a reservoir in which low-level replication persists is derived from a study utilizing a novel antiviral drug that targets the enzymatic activity of integrase . In approximately 30% of patients on long-term suppressive antiretroviral therapy , treatment with the integrase inhibitor raltegravir led to a transient increase in 2-LTR circles and a normalization of immune activation markers [13] . These results support the conclusion that , at least in some patients , standard antiretroviral therapy is not fully suppressive and a reservoir of cryptic replication fuels viral persistence . Other groups have also focused on defining the effects of therapy intensification on residual viremia using raltegravir , yielding different conclusions [14]–[17] . As in the study by Buzón and colleagues , one group observed an increase in 2-LTR episomal DNA levels in antiretroviral-experienced patients upon therapy intensification [15] . While a third group did not observe an increase in episomes in response to switching raltegravir for enfuvirtide [14] , the effects of raltegravir were assessed at week 24 and 48 , which is likely to be well after the effects of intensification occur . The remaining groups focused on measuring residual viremia in order to gauge the effects of therapy intensification using raltegravir [16] , [17] . Their main conclusion is that there is no significant change in viremia in response to raltegravir treatment , so the observed residual viremia is not due to ongoing cycles of HIV-1 infection . It is unclear at this point what the residual viremia represents . If it were derived from long-lived cells that harbor integrated proviruses , one would not expect to observe an effect upon therapy intensification with a new , potent antiviral . While further work is necessary , episomal DNA may be a more accurate marker of cryptic replication than residual viremia . In patients who suppress virus replication to levels below the limit of detection of standard assays , low-level ongoing replication can be detected through the analysis of the HIV-1 episomes . Therefore , in highly suppressed individuals who have undetectable virus in plasma , analysis via episomal HIV-1 cDNA provides the means to monitor and define the nature of actively replicating virus that persists in the face of ART . Here we have focused on analyzing episomal envelope ( env ) sequences to probe the nature of actively replicating virus that persists during ART and demonstrate the utility of episomal sequence analysis in guiding clinical treatment of infected individuals . Envelope sequences were compared to define the phylogenetic relationships between episomal and proviral genomes prior to rebound in patients on ART to RNA genomes of virus that emerged upon therapy interruption . Additionally , episomal env genes were analyzed from a group of patients undergoing salvage therapy with Vicriviroc ( VCV ) in order to predict the virologic response to this CCR5 antagonist . Several approaches have been used in previous studies to attempt to characterize the virus that fuels the rapid rebound of viremia upon interruption of ART with conflicting results [18]–[21] . To address this issue , we compared rebound virus env sequences to episomal and proviral env sequences that were present immediately prior to treatment interruption in a group of six individuals . The rationale for this analysis is that episomal HIV-1 genomes are a dynamic marker for recent infections and are representative of a reservoir in which HIV-1 is actively replicating , while proviral genomes are predominantly archival and defective [22] , [23] . Peripheral blood lymphocytes and plasma were obtained for a group of patients who had plasma viral RNA measurements below the level of detection for a minimum of 20 months ( Fig 1 ) . Episomal env sequences could not be amplified from four of the original set of patient samples and were excluded from the analysis . During the treatment period , patients suppressed viral replication with a combination of two nRTIs and at least one protease inhibitor ( Table1 ) . It should be noted that apparent increases in plasma viral RNA resulted from the use of assays with different limits of detection ( <50 or <500 HIV-1 RNA copies per ml ) and not from transient increases in viral replication . Upon therapy interruption , HIV-1 replication , based on plasma viral RNA measurements , rapidly resurged in all patients ( Fig 1 ) . DNA from peripheral blood lymphocytes was purified to selectively enrich for chromosomal and extrachromosomal fractions and the C2 to V4 regions of env were amplified by nested PCR using episomal-specific or proviral-specific primer pairs ( Fig 2 ) . Using this fractionation step greatly increases the likelihood that only the intended target DNA is amplified . The majority of unintegrated HIV-1 genomes remain in the supernatant and only a small amount of chromosomal DNA , potentially harboring an integrated provirus , partitions to the extrachromosomal fraction . Depending on the number of proviruses in a given sample , the level of contamination ranges from about 1 to 2 percent ( Fig S1 ) . Since the proviral frequency in patients on HAART is low [11] , [24] , amplifying env from a proviral template in the extrachromosomal fraction is unlikely . In order to promote phylogenetic comparison between baseline and rebounding viral genomes , plasma virus was sampled shortly after viral rebound . This minimized sequence diversity that develops during uncontrolled virus replication at therapy interruption . Env sequences from plasma virions collected from plasma sampled shortly after rebound were generated by RT-PCR . Nucleotide sequences were aligned using ClustalW ( MacVector 8 . 1 ) and neighbor-joining phylogenetic trees were constructed using the Kimura two-parameter model as implemented in the MEGA Version 4 program [25] . Confidence values for individual branches using 1000 replicates were estimated by bootstrap re-sampling of the neighbor-joining trees ( Fig 1 ) . Since the initial phylogenetic analyses may have included sequences based on PCR re-sampling , redundant sequences were removed from the alignments and best trees were generated using MacVector 8 . 1 to demonstrate data consistency and calculate genetic distances for different sequences ( Figs S2–S7 ) . All patient sequences were aligned to each other and in each case the patient sequences clustered with one another , but not with sequences from other patients or reference lab strains . In the majority of patients , env sequences in the rebounding virus were highly similar to episomal sequences present just prior to treatment interruption , but not to proviral sequences obtained from the same sampling time ( Fig 1 , Figs S2–S7 ) . In some patients , there was tight intermingling of rebound RNA and episomal sequences demonstrating very close genetic similarity supporting the conclusion that viral rebound originated from a reservoir in which viral replication was ongoing ( Fig 1 , Figs S2–S4 ) . Phylogenetic analysis of viral env sequences in individuals who interrupted therapy indicated that plasma viremia originated from a cryptic viral reservoir as identified by episomal sequences ( Fig 1 ) . However , it is possible that the viral variants identified by episomal sequences were of limited biological relevance to the immunopathogenic status of the host . To evaluate whether the cryptic viral reservoir that is revealed by episomal viral cDNA was of virologic relevance , we examined whether episomal sequences define a viral population that contributes to the virologic outcome of individuals receiving co-receptor inhibitors . HIV-1 infected individuals most frequently fail CCR5 inhibitor therapy because of the presence of a low frequency of X4 virus variants that are insensitive to CCR5 antagonists . Therefore , we hypothesized that identification of X4 viruses based on V3 env sequences in episomal cDNA would predict treatment failure . From ACTG trial 5211 in which patients received the CCR5 antagonist Vicriviroc ( VCV ) , we selected fourteen patients who experienced protocol-defined virologic failure . Virologic failure for this protocol is defined as failure to experience a log reduction in viral replication from baseline values at or after week 16 . Episomal env sequences were generated by PCR from lymphocyte DNA isolated from baseline through week 48 after initiation of VCV therapy . Full-length env genes were amplified from episomal cDNA and cloned into an expression vector . Pseudotyped viruses were generated with patient-derived envelopes and an NL4-3 proviral clone expressing luciferase in place of envelope . Co-receptor dependence was then gauged in an infection assay utilizing U87-based indicator cells . Amplification of full-length env genes was problematic for a small number of samples . Therefore , in order to derive secondary information on virus genotypes from these samples , short fragments spanning the V3 region of env were amplified and sequenced . Tropism predictions were determined using the Geno2Pheno algorithm with a false positive rate of five and ten percent as well as coupled 11/25 and net charge rules . The phenotypic/genotypic data is summarized in Tables 2 and S1 and tropism assignments based on an RNA phenotyping assay ( Trofile , Monogram Biosciences ) are listed for comparison . We were able to amplify either full-length or short episomal env fragments from 74 of 91 ( 81 . 3% ) PBMC samples . The Trofile assay and phenotypic assay based on episomal env sequences were concordant at all timepoints for 8 of the 14 patients . In these individuals , R5 viruses persisted at all time points based on both phenotypic assays and virologic failure could not be explained by outgrowth of X4 virus ( Tables 2 , S1 ) . In the remaining 6 patient samples , tropism assignments resulted in notable discordance . In one individual ( Patient A ) , the Trofile assay indicated the presence of D/M virus at all time points , while our assay detected only CCR5-dependent virus . PBMC samples from patients J and K showed the emergence of X4 or D/M viruses at baseline or week 2 , which was prior to assignments based on the Trofile assay . However , co-receptor use based on re-testing of baseline samples with an enhanced-sensitivity Trofile assay revealed the presence of D/M viral variants in patients D , J , and K , which is in accordance with our assay based on episomal env sequences [26 , Table S2] . Therefore , analysis of tropism from sequences contained with env of episomal cDNA revealed the presence of X4 variants at or near baseline and predicted virologic failure . Although current antiviral treatment can successfully reduce viral loads to undetectable levels in HIV-1 infected individuals , viral reservoirs persist . In order to guide efforts aimed at eradication of the virus from infected cells , it is critical to develop a comprehensive knowledge of the viral reservoirs that are maintained in the face of suppressive antiviral treatment . Since well-suppressed individuals have extremely low to undetectable levels of virus in peripheral blood , an alternative to virion RNA analysis is needed . Detection and analysis of episomal HIV-1 genomes , in patients in which virus replication is suppressed to levels below the limit of detection of standard assays , provides an option to characterize virus that persists in such individuals . We have previously shown that episomes are labile in vivo , and therefore , are valid surrogate markers for recent infections [10] . Here we have applied episomal analysis to characterize virus that rebounds upon antiviral treatment interruption . In an analysis of six patients , there was a rapid rebound in plasma viral RNA when therapy was interrupted after a prolonged period of sustained suppression of viral replication . Phylogenetic relationships based on C2 to V4 env sequences indicated that in the majority of patients , rebounding virus was highly similar to episomal sequences that existed prior to treatment interruption , but were not closely related to proviral sequences present at the same sampling time . As such , HIV-1 episomal cDNA is representative of a relevant biological reservoir that persists in individuals on ART and whose characteristics may not be defined by other assays . We observed considerable variability in the diversity of episomal sequences derived from the different patients . In patients on HAART , episomal HIV-1 genomes are rare and inter-patient variability can be high . We have previously observed that 2-LTR HIV-1 quantities in patients receiving highly suppressive antiviral therapy range from less than one to greater than 600 copies per million PBMCs [7] . In this study , env sequence diversity was dependant on the relative abundance of episomal genomes present in the samples ( data not shown ) . Previous studies aimed at revealing the origin of virus that rebounds upon therapy interruption have reached different conclusions . Both activation of latently infected CD4+ T cells and low-level active viral replication have been implicated in the rapid resurgence of viremia following treatment interruption [18]–[21] , [27] . Our analysis provides additional in vivo evidence that residual viral replication persists in patients on highly suppressive therapies and that viral rebound is fueled by this cryptic replication . While the present study supports the hypothesis that HIV-1 rebounds from a reservoir in which replication is ongoing , a recent study by Joos et al . concluded that rebounding virus is derived from the activation of latently infected cells [27] . The conclusion is based upon comparisons of residual viremia and virus that rebounds upon multiple treatment interruptions . Although the data is consistent with activation from latently infected cells , analysis of proviruses was not included , so one cannot be certain of the source of rebounding virus . Here we have directly compared proviruses and episomes to rebounding virus and conclude that it is more likely that the rebounding virus is derived from actively replicating virus . Work by others has suggested that at least some of the plasma virions that are produced in the setting of ART harbor replication competent virus [28] . Although this suggests that residual viremia can fuel HIV-1 rebound upon therapy interruption , the study was done with a single patient , so it is difficult to generalize the findings . Phylogenetic analysis of tat sequences derived from plasma virions and CD4+ T cells from the same patient revealed that most sequences generated from plasma were distinct from those in CD4+ T cells , which is consistent with previous studies [29]–[31] . These studies have concluded that residual viremia is derived from a source other than CD4+ T cells . Our analysis focused on genomes that were associated with PBLs , and given the genetic similarity between episomes and rebounding virus , episomal genomes may be derived from a reservoir that is distinct from the source of residual viremia . Although it would be potentially informative to compare env sequences that we generated to env present in patient plasma prior to rebound , it was not possible due to the archival nature of our samples . Additionally , one might predict that the sources of residual viremia and episomes are distinct based on the results of therapy intensification with raltegravir in which episomes increase transiently [13] , [15] while residual viremia remains unchanged [16] , [17] . Evidently , more work is needed to better define the viral reservoirs that persist despite highly suppressive ART . To further support the methodology and demonstrate that episomal analysis has the potential to provide information with which to guide clinical decisions regarding patient therapy , we analyzed samples from individuals undergoing salvage treatment with the CCR5 antagonist VCV . Although these patients had varying levels of viremia , we wanted to determine whether episomal HIV-1 cDNA analysis could provide information on the effects of adding VCV to a regimen that was no longer effective in suppressing viral replication . We were able to generate full-length env genes from sixty-four percent of the samples and of the samples in which viral plasma RNA copies were below 100 , we could amplify env fifty percent of the time . Thus , targeting episomal genomes provides a feasible approach to the study of residual virus replication . Although VCV is considered to be a potent inhibitor of R5 HIV-1 in vitro and in vivo [32] , [33] , the patients we focused on exhibited a poor response to therapy as defined by the clinical protocol . In five patients , phenotypic or genotypic analysis of episomal env genes indicated the presence of dual or X4 viruses while undergoing therapy . For these patients , it is highly likely that failure to respond to VCV therapy was due to the presence of viral variants that were unaffected by the CCR5 antagonist . In all cases , D/M or X4 viruses were present at early time points of the trial , so it is unlikely that selective pressure from VCV therapy resulted in a replacement of R5 with X4 virus . We observed very little variability in the primary V3 loop sequences of the patient samples , so the basis for VCV therapy failure is unclear in the subset of patients that did not harbor X4 or D/M viruses . These results are consistent with previous work studying the same group of patients [34] and imply that resistance to the antagonist may involve env sequences that are peripheral to the V3 loop or involve other , as yet undefined determinants . Alternatively , patients who experienced virologic failure with R5 virus may not have been fully compliant with the regimen . Since most of the samples were analyzed while patients were experiencing viremic episodes , we were able to compare our assay data to phenotypic data previously obtained via the Trofile assay [33] . Trofile is a single-cycle recombinant virus assay in which pseudoviruses are generated from full-length RNA-derived env genes to determine HIV-1 tropism from plasma virions [35] . This assay is the current “gold standard” to determine viral tropism and to guide whether CCR5 antagonists should be considered in the clinical management of an infected individual . Clinicians need tropism determinations to exclude the possibility that CCR5 antagonist use will result in outgrowth of a more pathogenic virus utilizing the CXCR4 co-receptor . However , a significant limitation to the assay is the requirement that viral plasma RNA levels be greater than 1000 copies/ml [35] . The Trofile assay and phenotypic assay based on episomal env sequences were highly concordant . The high degree of correlation between the two assays indicates that episomes are not archival , but are evolving and derived from a reservoir of actively replicating virus . While the majority of samples analyzed were from time points in which viral plasma RNA was greater than the limit of detection , we would expect episomal analysis to be a viable approach in patients that suppress virus replication to levels below the limit of detection of standard assays . Having a method to determine viral co-receptor usage in patients with highly suppressed viremia would be advantageous for patient management . It is common for patients to experience toxicity from the drug regimens in use and defining the virus co-receptor dependence would allow a clinician to switch therapy to a better tolerated drug such as a CCR5 antagonist . Previous studies have shown that 2- LTR episomes are detectable in a high percentage of patients on long-term highly suppressive antiviral therapy [7] , [13] . Additionally , the approach we used to amplify env from episomes also targets 1-LTR circles that are approximately ten times more abundant than 2-LTR circles resulting in a much greater sensitivity of detection [36] . Taken together , the results support the use of episomal HIV-1 cDNA as an additional or alternative approach to traditional assays to monitor the effects of antiviral therapy , and to help guide decisions on which patients may be most responsive to co-receptor inhibitor therapy , even for patients in which viremia is undetectable based on standard assays . After obtaining written informed consent , cells and plasma were collected by phlebotomy from HIV-1 infected volunteers at the NIAID and research centers involved in AIDS Clinical Trials Group ( ACTG ) protocol A5211 . Eligible participants were age 18 or older and either voluntarily suspended ART or chose to receive a new antiviral compound in the context of salvage therapy . The study was reviewed and approved by both the NIAID and the University of Massachusetts's institutional review boards . Human experimentation guidelines of the US Department of Health and Human Services were followed in the conduct of this research .
Infection by HIV-1 and the related effects on human health continue to be a major problem throughout the world . Since the early 1980's , more than 25 million people have died from AIDS and the only treatment option for infected individuals is likely to be life-long treatment with a combination of antiviral drugs . While antiviral drug therapy can reduce viral replication to levels that are undetectable by currently used assays , there is a rapid recrudescence of viremia upon interruption of therapy . This indicates that there are viral reservoirs , undetectable by conventional diagnostic assays that sustain the virus in the face of ART . We have developed an alternative or additional approach to study cryptic viral replication based on episomal HIV-1 genomes . Although HIV-1 episomes are not suitable substrates for integration and thus are dead-end products in the viral life cycle , episomal HIV-1 genomes are useful surrogate markers of viral replication since they are labile and indicative of recent infection events . Here we have used episomal HIV-1 analysis to study the reservoir that fuels viral rebound during treatment interruption and to demonstrate the utility of this approach in guiding the clinical treatment of infected individuals .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "infectious", "diseases/hiv", "infection", "and", "aids", "virology/immunodeficiency", "viruses", "molecular", "biology" ]
2011
Episomal Viral cDNAs Identify a Reservoir That Fuels Viral Rebound after Treatment Interruption and That Contributes to Treatment Failure
Endocytic vesicle formation is a complex process that couples sequential protein recruitment and lipid modifications with dramatic shape transformations of the plasma membrane . Although individual molecular players have been studied intensively , how they all fit into a coherent picture of endocytosis remains unclear . That is , how the proper temporal and spatial coordination of endocytic events is achieved and what drives vesicle scission are not known . Drawing upon detailed knowledge from experiments in yeast , we develop the first integrated mechanochemical model that quantitatively recapitulates the temporal and spatial progression of endocytic events leading to vesicle scission . The central idea is that membrane curvature is coupled to the accompanying biochemical reactions . This coupling ensures that the process is robust and culminates in an interfacial force that pinches off the vesicle . Calculated phase diagrams reproduce endocytic mutant phenotypes observed in experiments and predict unique testable endocytic phenotypes in yeast and mammalian cells . The combination of experiments and theory in this work suggest a unified mechanism for endocytic vesicle formation across eukaryotes . During clathrin-mediated endocytosis , cells regulate plasma membrane molecular composition and internalize essential nutrients . This process involves coordination of biochemical activities with membrane shape changes [1] , [2] . Multicolor real-time fluorescence microscopy studies in mammalian cells and yeast established that proteins are sequentially recruited to the endocytic site to drive membrane invagination and vesicle scission [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] . Real-time movies and EM studies in yeast and mammals have demonstrated that the endocytic membrane is composed of different regions ( bud and tubule/neck ) , each with a distinct protein composition and spatial profile [13] , [14] , [15] . Comparisons between yeast and mammalian endocytic systems have highlighted similarities and differences [2] , [16] . The extent to which common principles underlie endocytosis in different eukaryotic cells is currently a matter of speculation and debate . Among the most obvious differences , clathrin-mediated endocytosis in mammalian cells involves formation of spherical clathrin-coated vesicle buds and recruitment of the GTPase dynamin to the vesicle neck , while endocytic structures in yeast are tubular invaginations lacking dynamin [15] , [17] . Also , actin assembly is required for formation of the membrane invagination and for vesicle scission in yeast [8] , while in mammalian cells these steps appear only to be assisted by actin assembly [18] . On the other hand , many endocytic proteins , including clathrin , adaptor proteins , and cytoskeletal proteins , are highly conserved from yeast to mammals . In both yeast and mammalian cells , dynamics of the key endocytic proteins are coordinated in space and time , and internalization and vesicle scission are accompanied by a transient burst of actin assembly [1] , [2] . Despite intensive study in many laboratories , the mechanisms underlying coordination of protein recruitment , lipid modification , and membrane shape changes are not well understood in any organism . From a mechanical standpoint , endocytosis appears to proceed in two stages: invagination of the membrane , followed by pinching off of the vesicle . The cell cortex is quite resistant to deformation , so the shape changes accompanying endocytosis incur a large energy penalty [19] . Consequently , the cell must generate a considerable mechanical force to deform the endocytic membrane . To do so , endocytosis must involve biochemical reactions at the endocytic site that control the pulling and pinching forces . In budding yeast , actin polymerization and myosin motor activity have been implicated in providing the pulling force for membrane invagination [10] . Pinching off of the membrane vesicle entails even larger membrane curvatures at the scission site than does generation of the invaginated membrane . In mammalian cells , dynamin GTPases have been proposed to act as “pinchases” that physically constrict membrane tubules [20] , [21] . However , endocytic vesicles form in budding yeast despite the absence of dynamin at endocytic sites . In vitro studies have suggested a possible scission mechanism; an interfacial force arising at the boundary between two lipid phases can provide the driving force for vesicle scission [22] , [23] . We previously proposed that such a mechanism might drive endocytic vesicle scission in vivo [11] , [24] . Reciprocally , emerging experimental evidence suggests that membrane curvature created by mechanical force can modulate the local biochemical activities of several key endocytic proteins [25] . Experiments suggest that membrane curvature may act as a guiding signal to direct BAR ( Bin/Amphiphysin/Rvs ) domain proteins to the endocytic membrane invagination [26] . Conversely , BAR domain proteins ( BDPs ) are also capable of deforming the membrane into the preferred shape for their binding [27] , [28] , [29] , [30] , [31] , [32] . However , in the context of the coherent process of endocytosis , the exact functional role of these physical properties of endocytic proteins remains elusive . Here we attempt to combine detailed knowledge of endocytic protein dynamics and function in budding yeast with mechanochemical concepts to develop an integrated systems model for the endocytic internalization pathway . Our model stands in contrast to previous models [22] , [23] , [24] . Rather than focusing on one sub-process , our model seeks to reproduce the correct sequence of events in a coherent manner , including the local biochemical reactions and membrane shape changes . We propose a mechanochemical feedback mechanism that can generate successful endocytosis over a broad range of its parameter space . The model fits quantitatively the correct temporal and spatial profiles measured in budding yeast . Furthermore , when the parameters are varied to mimic endocytic mutants , the model accounts for many endocytic phenotypes in budding yeast and yields experimentally testable predictions . Finally , we argue that , despite some differences in molecular details , the underlying principles likely apply to mammalian endocytosis as well . In this section , we will describe the qualitative features of our model . The quantitative mathematical formulations will be relegated to the Experimental Procedures . Temporal control and spatial arrangement of proteins and the lipid PI ( 4 , 5 ) P2 at budding yeast endocytic sites are key features in the development of our model ( Figure 1 ) . First , each of the key endocytic proteins appears to localize along the membrane invagination with a distinct spatial profile , predicted by dynamic properties [8] , [9] , [11] and confirmed by EM [15] . Second , these proteins can be grouped into four “protein modules” based on their distinct dynamics and functions [9] , [15] . Lastly , we previously obtained evidence for a PI ( 4 , 5 ) P2 “lipid module” that is dynamically regulated during endocytosis [11] . For this model , we describe clathrin-mediated endocytic dynamics on the level of functional modules , which allows us to look beyond roles of individual molecular players that may vary from one organism to another and to focus upon collective behaviors in membrane shape transformations and local biochemical pathways . Thus , our model can serve as a unified framework for endocytosis across diverse organisms . We propose that the five modules along with their functions are as follows ( Figure 2 provides an overview of the model ) : From a mechanical standpoint , the pulling forces generated by the actin/myosin functional module impinge on the bud and invaginate the membrane . The initial pinching force is generated as follows . Because of the protection afforded by BDPs on the tubule , more PIP2 is hydrolyzed at the bud region . This leads to lipid phase segregation—PIP2 levels along the membrane invagination differ , and the resulting interfacial force at the bud-tubule interface squeezes the neck . From a chemical perspective , the local chemical reactions ( e . g . , actin assembly , PIP2 hydrolysis ) control pulling and pinching forces . Equally important , the resulting membrane curvature generated by the mechanical forces also influences the local reaction rates ( Figure 2 ) . In this way , endocytic dynamics are controlled by mechanochemical feedback between endocytic membrane shape changes ( membrane curvature ) and the local chemical reactions that control the mechanical forces ( pulling and pinching forces ) . This key notion , as we will show below , is essential for the robustness of the sequential endocytic protein recruitment and timely vesicle scission . This qualitative picture is captured by Equations 1–6 in the Experimental Procedures . The coupling between the mechanical and chemical processes of endocytosis is specified by the dependence of the reaction rates on membrane curvature and by the dependence of the local membrane curvature and the mechanical force on the local levels and activities of the functional modules . To calculate the dynamics of endocytic events , we numerically integrate Equations 1–6 over time starting from the initial condition: the endocytic membrane is flat and the initial coverage for all of the protein modules is set to zero . The initial PIP2 coverage is set to 2% corresponding to its normal average level [48] . At each step , the system is characterized by the instantaneous shape of the endocytic membrane and the local levels of the functional modules as represented in mole fraction . The values of the parameters used in the model are listed in Table 1 with references in Protocol S1 . Below , we first study the endocytic dynamics of budding yeast by choosing the parameter set that quantitatively fits the time-lapse experimental data in Figure 1A . We then vary the parameters to mimic mutant experiments to predict and analyze the associated phenotypes . As the model dynamics are controlled by many parameters in Equations 1–6 , there could in principle be many outcomes depending on parameter choices . To circumvent this problem , 21 of the 25 parameters used in the model were taken from independent experiments ( Table 1 in Protocol S1 ) . The four unmeasured parameters all characterize BDP dynamics; they are the intrinsic BDP recruitment rate , actin-aided recruitment rate , turnover rate , and the relative timescale of BDP dynamics with regard to actin dynamics . With 21 measured parameters being fixed , we only vary the four free value parameters to fit the five time-lapse curves of endocytic dynamics observed in wild-type budding yeast ( Figure 1A ) . The values of these four parameters are constrained because these kinetic rates must be comparable to those experimentally determined for each of the other functional modules . The dynamics of all of the modules are tightly coupled: one sub-process cannot be much faster/slower than the others . In what follows , we use specific proteins or lipids to represent the corresponding functional modules . We stress from outset that the goal of the paper is to illuminate the collective dynamics of endocytosis generated by the interactions among the functional modules , rather than identifying detailed molecular players . Figure 3A shows that the endocytic dynamics predicted by our model ( continuous lines ) fit quantitatively with the experimental data ( discontinuous lines ) [8] , [11 , and the measurements in this paper] . Figure 3B shows snap shots of the corresponding computed membrane shape changes ( a movie of the process derived from model calculation is provided in Video S1 ) . Because the fitting parameters are constrained by measurements from independent studies , the agreement between our theoretical results and experimental observations lends validation to our model . An important feature of the process is that each functional module is activated sequentially in step with the membrane shape changes ( Figure 3A and 3B ) . We next describe steps in the endocytic process in greater detail based on our model . Early in the process ( 0–20 s , Figure 3A ) coat proteins begin to accumulate . During this period , the membrane is deformed by the coat proteins , which generate a small dome ( less than 50 nm in height and ∼50 nm in width , t∼20 s in Figure 3B ) . However , there is a delay before actin polymerization fully commences , because it takes a while for the nucleation factors to be recruited and activated and because actin assembly is autocatalytic due to Arp2/3 activation by actin filaments . Without the assistance of the actomyosin force , the dome-like membrane deformation would not progress further , which is consistent with observations from recent EM studies [15] . Indeed , this dome shape could be the prerequisite for further development of a deep invagination , because the local membrane shape may provide a suitable angle at which the F-actin pulling force can be exerted upon the bud region effectively . At ∼20–25 s ( Figure 3A ) , F-actin polymerization is promoted by nucleation factors recruited by the coat proteins , and the pulling force upon the bud region increases . This drives the endocytic membrane to invaginate further ( t∼22 s in Figure 3B ) . As the membrane invaginates , actin monomers rapidly incorporate into the existing actin filaments with their barbed ends facing the cell cortex [8] , while myosin pushes the actin network away from the plasma membrane into the cytoplasm . Meanwhile , the PIP2 phosphatase begins to accumulate all over the endocytic site . Concurrently , BDPs also start to accumulate along the tubule region rapidly , and they increase from 10% to the peak level in only 3 s ( Figure 3A ) . Now the question is: what drives the rapid BDP accumulation ? We show that curvature-sensing and deforming activities of BDPs form an intrinsic positive feedback loop ( see quantitative calculations in Figure S1 ) . As schematized in Figure 4A , as they bind to the membrane , BDPs deform the adjacent membrane into the preferred curvature for their binding . This leads to a faster recruitment rate , which further promotes BDP recruitment and tubulation of the membrane . This positive feedback also explains and reconciles the two classes of experimental observations , which provided evidence for curvature-sensing and membrane-deforming activities [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] . In our scenario , actin assembly and myosin contractile forces invaginate the membrane . The resulting membrane curvature fits relatively favorably to the preferred shape of BDPs and , hence , promotes rapid BDP binding at the right location and at the right time due to the curvature-sensing activity . In turn , BDP binding invaginates the membrane further and generates optimal curvature for BDP binding in the elongating tubule , which self-accelerates BDP accumulation . Thus , the initial membrane invagination generated by the actin/myosin force triggers the positive feedback between BDP binding and membrane tubulation . During this same period , PIP2 hydrolysis rates are faster on the bud than on the tubule , as the BDPs protect the PIP2 on the underlying tubule from hydrolysis . Lipid-protein interactions involving BDPs could limit PIP2 diffusion in the membrane [45] , allowing formation of a lipid-phase boundary . An interfacial force at the bud-tubule boundary thus starts to build up , constricting the neck . Eventually ( t∼29 s in Figure 3A and 3B ) , the interfacial force narrows the neck down to <5 nm , at which distance the opposed bilayers would fuse spontaneously [49] , resulting in rapid vesicle scission . Upon vesicle scission , BDPs disassemble from the membrane tubule within 3 s as the tubule retracts due to loss of the actin pulling force . A second crucial effect of the PIP2 phosphatase activity on the vesicle bud is to trigger disassembly of the endocytic coat ( t∼25–29 s , Figure 3A ) . As coat proteins disassemble , the F-actin attachments to the bud weaken , resulting in loss of pulling force on the invagination . We predict that this leads to a small retraction of the endocytic membrane tip concurrent with vesicle scission ( see Figure 3A ) and propose that loss of the pulling force on the membrane may be a prerequisite for vesicle scission . Our description of the endocytic process ( Figure 3 ) raises the following interesting questions: How is the interfacial scission force generated ? How does vesicle scission occur so rapidly ? And what turns off the positive feedback loop for BDP assembly and drives their extremely fast disassembly ? In this section , we propose answers to these questions . Our proposal that an interfacial force can drive vesicle scission is supported by in vitro experiments [22] , [23] , in which lipid phase segregation is induced by lowering temperature . In vivo , however , cells always maintain constant temperature; instead , lipid-protein interactions could be utilized to yield effective lipid phase segregation . Here , we present two possible scenarios for how the interfacial force is developed in endocytosis ( schematized in Figure 5A ) : ( 1 ) As PIP2 hydrolysis at the bud eliminates hydrogen bonds that had bridged the interfacial boundary , hydrogen bond shielding of the hydrophobic hydrocarbon chains is lost , and at the boundary these aliphatic tails are exposed to water , which is energetically unfavorable . The resulting line tension is proportional to the PIP2 difference across the interface , which contracts to minimize these unfavorable contacts , thus squeezing the neck . ( 2 ) The reduced hydrogen bond network at the bud lowers the membrane surface tension of the outer leaflet , which thus tends to expand . Effectively , this is a lateral surface pressure that propagates from the high-lateral pressure region towards the interfacial boundary . Due to the local concavity of the membrane created by the initial interfacial tension , this lateral pressure is directed inwards at the phase boundary and provides an additional pinching force . This additional lateral pressure also increases with the difference in PIP2 levels across the phase boundary ( see the detailed derivations in Protocol S1 ) . Figure 5B shows the calculated time course for interfacial force development during endocytosis , while Figure 5C shows the calculated profiles for PIP2 levels around the bud-tubule boundary at different time points . Figure 5B and 5C show that the interfacial force undergoes rapid changes . During t∼0–21 s , PIP2 accumulates uniformly over the entire endocytic site , as promoted by kinase-mediated synthesis . From around t∼21 s ( Figure 5C ) , PIP2 levels decline non-uniformly; consequently , the interfacial force starts to build up ( Figure 5B ) . This spatial non-uniformity is because around the same time as the phosphatase is recruited , BDPs start to accumulate at the tubule region of the endocytic membrane ( t∼21 s in Figure 3A ) . As a result of the BDP protection at the tubule , relatively more PIP2 is hydrolyzed on the bud , leading to lipid phase segregation at the BDP–coat protein boundary . This phase separation gives rise to the initial interfacial force at the phase boundary . From t∼21–27 s ( Figure 5B and 5C ) , the interfacial force grows sharply . Such rapid growth of the interfacial force is the result of another positive feedback loop involving curvature-enhanced PIP2 hydrolysis . We schematize the qualitative mechanism in Figure 4B . As the initial interfacial force squeezes the neck , it creates a higher mean curvature at the interface . The higher the mean curvature of the membrane , the more PIP2 is exposed and susceptible to phosphatase activity . Consequently , more PIP2 is depleted at the interface region along the membrane invagination . Thus , a larger difference in local PIP2 levels bounding this location is induced ( ∼21–27 s , Figure 5B and 5C ) , which in turn speeds up the growth of the interfacial force and , hence , further squeezes the interface . This is a self-accelerating process . The sharp dip of the PIP2 levels around the bud-tubule interface compared to the smaller difference between those of tubule and bud ( t∼23 s and 27 s in Figure 5C ) suggests that curvature-dependent PIP2 hydrolysis is the predominant driving force for generating the interfacial force . Our model thus predicts that the pinching force arises as a result of differential phosphatase activity along the membrane invagination . This prediction is consistent with the observations that phosphatase activity is essential for endocytic vesicle scission in yeast , that the phosphatase concentrates at the endocytic site during the late stages of endocytic vesicle internalization , and that it moves into the cell with the forming vesicle , possibly suggesting enrichment at the vesicle tip [11] . During t∼27–29 s ( Figure 5B and 5C ) , as the pinching force squeezes the neck , the membrane curvature in the radial direction of the tubule deviates from the optimal shape for BDP binding ( t∼28 s and 29 s in Figure 3B ) . This deviation acts as a “disassembly signal” and invokes the intrinsic positive feedback loop between curvature sensing and curvature deforming of BDPs ( Figure 4A ) , triggering the rapid BDPs turnover ( ∼27–29 s in Figure 3A ) . Meanwhile , PIP2 gets hydrolyzed not only at the bud but also on the tubule due to the lack of BDP protection ( t∼29 s , Figure 5C ) . Although this leads to a fast decrease in the interfacial force ( ∼27–29 s , Figure 5B ) , the pinching force is still sufficient to drive rapid vesicle scission according to our calculations . We need to point out that , while the in vitro systems on lipid phase segregation are crucial for identifying mechanical forces that might be involved in vesicle scission , the experimental conditions used are quite different from the in vivo conditions during endocytosis . Once the lipid phase segregation takes place in the in vitro systems , the resulting interfacial force persists and there is no time limit for the vesicle scission process . All that matters is that the interfacial force needs to be sufficiently large to overcome the membrane bending resistance [24] , [50] . In cells , the timing of the lipid phase segregation is predicted to be critical for successful endocytosis . The threshold interfacial force value required for scission can be determined by force-balance calculations [24] , [50] . A rapid nonlinear time course for interfacial force development in endocytosis means that successful scission in vivo can only occur within a short time window ( the shaded region in Figure 5B ) . In this section , we will explore in detail how mechanochemical feedback ensures the precise timing and sequence of endocytic events and guarantees rapid endocytic vesicle scission . In Figure 6A–6D phase diagrams for endocytosis are computed for different pairs of model parameters . These diagrams serve several purposes . First , they show that the model is robust: it can generate successful endocytosis over a large range of the parameters . Second , equipped with these phase diagrams , we can vary the parameters to mimic the conditions of mutant experiments . Third , they constitute an independent experimental test of the model . This is because the identities of the functional modules were in part derived from mutant experiments , but we did not explicitly take into account the mutant phenotypes in the model . That is , we used the five time-lapse curves and membrane shape changes to determine the four free parameters in the model , and then used these parameter values to predict mutant phenotypes . Thus , these predictions are independent of the parameter set , and consequently the agreement between predicted and observed phenotypes constitutes cross-validation of the model . Finally , based on the calculated phase diagrams , we can predict endocytic phenotypes for mutants that have not yet been made , thus guiding further experiments . Figure 6A shows that endocytosis can only be successful when the curvature-dependent PIP2 hydrolysis rate is sufficiently fast . Otherwise , the PIP2 level difference across the interfacial boundary will not have had sufficient time to grow before the membrane bending energy resists squeezing and quickly balances the interfacial force without triggering the positive feedback loop ( Figure 4B ) . Accordingly , the absence of positive feedback between the interfacial force and the local membrane curvature leads to a distinct phenotype ( phenotype 1 , wherein the PIP2 hydrolysis rate k2 is reduced from 20 ( nm ) per second to zero ) : F-actin associated forces could still drive membrane invagination; the interfacial force , however , would not squeeze the neck effectively , because the force cannot grow large enough . Thus , the whole system would eventually reach a mechanochemical equilibrium wherein a slightly curved membrane invagination could persist for a time without vesicle scission . This phenotype is consistent with the budding yeast mutant sjl1Δ sjl2Δ [11] , wherein the PIP2 hydrolysis is dramatically reduced . If the PIP2 hydrolysis rate is very fast but independent of the local membrane curvature , then the positive feedback between the interfacial force and the local membrane curvature is ablated ( see Figure 4B and 45 ) . Without this positive feedback , the interfacial force would always remain at its initial basal level , which is insufficient to pinch off the vesicle ( see details in Figure S2 ) . Successful endocytosis , therefore , requires the positive feedback between interfacial force and curvature-dependent PIP2 hydrolysis activity . This is further dictated by two conditions: first , the PIP2 hydrolysis rate must be faster than the typical response time scale of the membrane , and second , PIP2 hydrolysis must be curvature-dependent . The former can be tuned by the local concentration of phosphatases , and the latter is intrinsic to the mechanism of enzyme activity . Figure 6A shows that , even with a sufficiently high curvature-dependent PIP2 hydrolysis rate , endocytosis may not be successful unless the protection of PIP2 at the tubule by BDPs is sufficiently effective ( large K2 ) . Otherwise ( small K2 ) , the resulting interfacial force would be too small to drive vesicle scission . On the other hand , if the protection is too effective , then PIP2 levels at the tubule would be maintained at a high level , which in turn would lead to persistent BDP accumulation . As BDPs tend to deform the membrane to a specific , preferred shape ( diameter ∼30 nm ) , persistence of the BDPs would effectively hold the neck and prevent any further narrowing of the membrane tubule , hindering vesicle scission . This leads to prediction of a unique phenotype ( phenotype 2 , wherein the protection strength of PIP2 hydrolysis at the tubule region increases from 0 . 5 μM−1 to 2 . 5 μM−1 ) , in which the absolute levels and the lifetimes of the BDPs would increase significantly as compared with the wild-type situation . Furthermore , a long and narrow membrane invagination could persist without vesicle scission . This is because BDPs have their own preferred shape ( a tubule of ∼30 nm in diameter ) , and their persistence would tend to preserve the shape of membrane tubule , preventing any further squeezing in response to the interfacial force . Our model predicts that within the successful endocytosis region in Figure 6A , increasing the curvature-dependent PIP2 hydrolysis rate k2 will speed up endocytosis and that this effect will saturate at large k2 . This is because in this case endocytic dynamics are limited by the phosphatase recruitment rate , instead of by its activity . As shown in Figure 6B , positive feedback between interfacial force development and local membrane curvature will not develop if the phosphatase activity is not sufficient . Insufficient phosphatase results in a phenotype similar to those observed when PIP2 hydrolysis curvature dependence is insufficient , as shown in Figure 6A , and/or when PIP2 hydrolysis is independent of curvature , as shown in Figure S2 . On the other hand , endocytosis will also be impeded if the phosphatase is overexpressed or overactive at the endocytic site , which leads to phenotype 3 ( where the curvature-dependent factor of phosphatase recruitment rate α increases from 100 nm to 500 nm ) . Here scission fails because the excessive phosphatase diminishes the initial PIP2 level difference across the bud-tubule boundary , thus preventing the development of the initial squeezing force . As a result , the membrane at the interface cannot be deformed sufficiently to invoke positive feedback between interfacial force development and the curvature-dependent PIP2 hydrolysis activity . A surprising conclusion from our model is that coat proteins will still assemble at the endocytic site in the presence of excessive phosphatase and will disassemble slowly . This conclusion is based on the linear dependence of the PIP2 hydrolysis rate on the local membrane curvature , which is in accordance to experimental observations . PIP2 hydrolysis is relatively slow despite high phosphatase levels because the membrane is not highly curved ( e . g . , phenotype 3 ) . Thus , even though the phosphatase recruitment is very fast in phenotype 3 , its action is limited by the lack of membrane curvature , which is low because a pronounced phase boundary does not develop . Figure 6C shows that successful endocytosis also critically depends on the coordinated dynamics of BDP recruitment and F-actin polymerization . Without actin polymerization , the endocytic membrane cannot become deeply invaginated . Failure to invaginate the membrane prevents BDP accumulation and the ensuing development of the interfacial force . Consequently , the membrane cannot deform into a deep invagination , nor proceed to vesicle scission . This situation is similar to having excessive phosphatase at the endocytic site , leading to phenotype 3 in Figure 6 , consistent with actin-assembly inhibition phenotype in budding yeast [8] . When actin polymerizes normally , efficient endocytosis requires sufficiently fast BDP accumulation . Insufficient BDP recruitment would lead to phenotype 4 ( wherein the BDP recruitment rate drops to zero ) : the endocytic membrane will be pulled out and will then retract without vesicle scission ( a movie of the process is given in Video S2 ) . This is because although the peak interfacial force is large enough to squeeze the neck in phenotype 4 , the force declines so rapidly that the membrane does not have time to undergo deformation and , hence , the vesicle cannot be successfully pinched off . A large interfacial force can develop in the absence of the BDPs in phenotype 4 because the actin filaments contact actin-binding proteins associated with the coat so that the actin pulling force impinges on the entire bud region of the endocytic membrane , including the bud-tubule boundary . Although very small , the force from the actin module can still deform the membrane at the neck slightly , which activates the curvature-dependent PIP2 phosphatase activity . Hence , the positive feedback loop is triggered , leading to generation of a large interfacial force . However , without BDP protection , this large interfacial force is too short-lived and vesicle scission does not occur . On the other hand , in the absence of sufficient numbers of BDPs , the high curvature of the membrane invagination generated by F-actin polymerization would still induce phosphatase recruitment , which would result in disassembly of the entire endocytic apparatus and retraction of the membrane invagination . This predicted phenotype is consistent with the phenotype of a budding yeast rvs167 ( a BDP ) knockout mutant [9] and a lipid-binding defective rvs167 point mutant ( Kishimoto and Drubin , unpublished ) . The lifetime of BDPs at endocytic sites is extremely short ( ∼10 s ) in wild-type budding yeast [9] , [11] . We have shown for phenotype 2 of Figure 6A that prolonged accumulation of BDPs could prevent endocytosis . A key message emerging from these two observations is that the interplay between the interfacial force and BDP turnover is critical for successful endocytosis . As the interfacial force squeezes the interface , it tends to narrow the adjacent membrane tubule , which deviates from the shape preferred by BDPs . This deviation leads to a curvature mismatch and acts as a “disassembly” signal for the BDPs as dictated by the BDP sensitivity factor ( the exponential term χ in Equation 5 ) . Accordingly , upon narrowing of the tubule , the higher the sensitivity factor χ , the faster the turnover of the BDPs , and hence the more that vesicle scission is facilitated . As Figure 6D shows , when the interfacial force is very large ( >60 pN ) , it is capable of squeezing the interfacial boundary even if the BDPs are not disassembled; endocytosis would proceed normally even with prolonged BDP accumulation at the tubule ( χ = 0 ) . On the other hand , when the interfacial force is in an intermediate range ( e . g . , 30–60 pN ) , its action could be insufficient to overcome the bending resistance of the preferred membrane shape set by the BDPs . Given that the interfacial force will also dissipate in a short period of time ( ∼5 s , Figure 5A ) , a minimal level of curvature-dependent sensitivity in BDP accumulation is required to induce fast BDP turnover upon squeezing of the membrane tubule , relieving the bending resistance , and hence facilitating vesicle scission . This sets the lower threshold of the curvature-dependent sensitivity of BDP dynamics for successful vesicle scission . Note that the curvature sensitivity , χ , is central to the positive feedback between BDP recruitment and the local membrane deformation ( Figure 4A ) . The above results imply that successful endocytosis requires that BDP binding feeds back positively with the underlying membrane shape . During endocytosis , recruitment of the endocytic proteins is sequential and self-reinforcing , or autocatalytic [3] , [4] , [8] , [9] , [10] , [11] , [12] , [35] . We propose that these features are properties of positive mechanochemical feedback loops between membrane curvature and the various reactions leading to vesicle formation and scission ( Figures 2–6 ) . To our knowledge , our model is the first of its kind that can coherently capture all of the key endocytic events in budding yeast . The dynamics predicted by the model fit well with time-lapse experimental measurements ( Figure 1A ) . Moreover , the parameter diagrams in Figure 6 show that successful endocytosis can be realized over a broad range of parameter space . Thus the endocytic process is largely buffered against variations in the activities of specific molecular players . Endocytosis in budding yeast evolves in a sequence of events that are explained by the model ( as schematized in Figure 7A ) . As PIP2 accumulates at the endocytic site , it recruits coat proteins to the bud region that nucleate actin polymerization . Using anchorage to the coat proteins ( e . g . , Sla2 ) , F-actin polymerization and myosin motor activity generate a pulling force that deforms the membrane into a tubule . The high curvature of the tubule in turn recruits BDPs that coat the tubule by binding to PIP2 . The BDPs protect the PIP2 along the tubule from hydrolysis by the phosphatase . The coat proteins on the vesicle bud do not protect the PIP2 from hydrolysis as effectively , so a boundary region is created that develops a circumferential interfacial tension . This tension exerts a squeezing force on the phase boundary , which further increases the curvature at the bud neck , which in turn increases the hydrolysis there . Thus a positive feedback loop arises between membrane curvature and PIP2 hydrolysis rates at the interface , the result of which is the rapid growth of the interfacial force leading to vesicle scission ( Figure 5 ) . Furthermore , the positive feedback loop between the curvature-sensing and deforming activities of the BDPs ensures rapid turnover of the BDPs , facilitating timely vesicle scission . After scission , PIP2 is hydrolyzed all over the membrane surface , promoting disassembly of the entire endocytic apparatus . Therefore , it is the two intertwined positive feedback loops ( Figure 4 ) that ensure rapid , robust , and timely endocytosis in budding yeast . Our model depicts endocytosis at the level of functional modules , rather than at the level of particular proteins; the model enables us to discern the general features of the process and to dissect how the sub-processes fit together . As different proteins can play the same functional role in different organisms , our model can be extended to account for the endocytosis in other organisms . We have applied this framework to endocytosis in mammalian cells; the predictions from our model are largely consistent with experiments and provide further mechanistic insight , suggesting that similar principles may dictate the dynamics and robustness of protein recruitment , and the vesicle scission mechanism . Our model predicts that the main profile of the endocytic membrane in mammalian cells is a constricted coated pit instead of the tubular structure in yeast . The interfacial force generated by lipid phase segregation is sufficient to pinch off the vesicle , and actin is largely dispensable while the membrane-deforming dynamin GTPase and clathrin are essential . We schematize our main findings of mammalian endocytosis in Figure 7B and relegate the detailed discussions to Protocol S1 . The model reproduces the behavior of observed endocytic mutant phenotypes and predicts several phenotypes that have not yet been studied in experiments . We predict that yeast endocytosis will be hindered if BDP protection of PIP2 on the tubule is either too weak or too strong , which is testable by BDP mutant analysis . Weak protection of PIP2 would reduce the PIP2 difference and , hence , the interfacial squeezing force . On the other hand , the more persistently the BDPs coat the tubule , the more resistant the tubule will be to the further squeezing from the interfacial force ( phenotype 2 in Figure 6 ) . This is because BDPs prefer a well-defined membrane shape ( tubules of 30 nm diameter ) . In addition to rapid BDP assembly , therefore , BDP disassembly concurrent with vesicle scission is also essential for endocytosis . The role of BDPs in vesicle scission suggests an explanation for dynamin mechanism that contrasts with the conventional view of dynamin as a pinchase ( see Section F in Protocol S1 for a detailed discussion of dynamin ) . Dynamin disassembly precedes membrane fission [51] , [52] , which suggests that dynamin may act to disrupt local membrane structure , perhaps through generation of a phase boundary . Disassembly would be required to release the underlying membrane , allowing a line tension to constrict the vesicle neck to drive scission . Successful endocytosis also entails three constraints on PIP2 hydrolysis rates , all of which lie at the heart of the mechanochemical feedback loop and can be tested by in vivo and in vitro experiments . First , the PIP2 hydrolysis rate must be curvature-dependent ( see Figure S2 ) . Second , it must be faster than the response time scale of the membrane deformation ( Figure 6A ) . Third , it must be slower than the time scale for assembling the endocytic apparatus ( Figure 6B ) . We predict that when the PIP2 hydrolysis rate drops below a threshold , endocytosis will cease , but the endocytic membrane invagination will persist ( phenotype 1 in Figure 6 ) . Thus , the phosphatase not only uncoats proteins from the endocytic vesicle , but it also is essential for vesicle scission . This dual function makes sense because endocytosis is a sequential process: each step paves the way for the next one . The coat proteins on the bud must disassemble upon—or shortly after—vesicle scission . Uncoating is essential for the fusion of endocytic vesicle with early endosomes and coat protein recycling . This prediction provides a fresh perspective on the functions of phosphatase/lipase in endocytosis in yeast as well as in mammalian cells , e . g . , synaptojanin in neurons [36] . Given the small number of proteins present at each endocytic site at different times in the process ( ∼10–100 ) [10] , [53] , it would appear that the process should be very stochastic . Typically , stochastic protein recruitment arises from variations in the assembly “source signal” and in the number of proteins being recruited . The rapid sequential recruitment of endocytic proteins , such as the BDPs and phosphatase , implies a highly cooperative process: the Hill coefficient for BDP recruitment by actin is >6 as inferred from [9] , [10] . Thus , without compensating mechanisms , small variations in the source signal would be amplified to large uncertainties in recruitment . And yet the timing of endocytic protein recruitment is very robust , and endocytosis proceeds smoothly . The effects of small variations in protein levels and activity could be overcome if extremely specific protein-protein interactions acted as a template for recruitment , which requires the free energy decrease for protein binding to be well above the level of thermal fluctuations , i . e . , >10 kBT . Our model implies an alternative mechanism: using local membrane curvature as the source signal; i . e . , to assemble and disassemble BDPs . If we add random noise to Equations 1–5 and Equation 6 to mimic the instantaneous fluctuations in protein numbers and membrane shape fluctuations , respectively , endocytosis remains stable up to 20%–30% variation in the maximum levels for each module ( unpublished data ) . The reason for this stability is the small diameter of the endocytic invagination ( ∼50 nm ) . On this scale , the membrane is quite stiff , and so the membrane curvature will not fluctuate much because of the energy penalty associated with stochastic fluctuations in membrane shape ( ∼100 kBT ) [54] , [55] . Moreover , since a curvature mismatch increases the free energy associated with BDP binding , the membrane curvature modulates the BDP recruitment rate via a Boltzmann factor ( Equation 5 ) . Thus , the local membrane curvature is instantaneously stable throughout the process and dictates the timing and location of BDP assembly and disassembly accurately despite stochastic fluctuations . Hence , the mechanochemical feedback has a build-in robustness that ensures successful endocytosis . In the future , much experimental and theoretical work will be required to test and refine our model . Here we discuss aspects of our model for budding yeast endocytosis that we have not yet addressed . A related discussion for mammalian cells is presented in Section F in Protocol S1 . For our model , the key to promoting rapid vesicle scission was to invoke positive feedback between growth of the interfacial force and curvature-dependent PIP2 hydrolysis at the interfacial boundary , resulting in a sharp dip in the local PIP2 concentration at the interface . For this mechanism , all that is needed is to induce a localized membrane deformation ( i . e . , higher mean curvature ) at a specific site along the membrane tubule . This in turn will trigger a positive feedback effect on PIP2 hydrolysis . There are many ways in which a localized membrane deformation can be generated . In this paper , we only entertained one scenario , in which the initial squeezing of the membrane at the interfacial boundary is the result of an initial PIP2 level difference ( lower in the bud region ) due to BDP protection of PIP2 hydrolysis on the tubule . However , other scenarios are also feasible . For instance , as phenotype 4 shows , even without BDPs , the impact from normal actin/myosin force could deform the membrane neck so as to invoke positive feedback and hence a large interfacial force . Although in this case the interfacial force is too short-lived to drive vesicle scission , this scenario nonetheless suggests other avenues to generate a sufficiently strong and persistent force . Also , it could be that the coat proteins protect PIP2 on the bud more effectively than the BDPs protect PIP2 on the tubule . This will result in a higher PIP2 level at the bud relative to the tubule , which could equally well induce an interfacial force . Although this scenario seems less likely due to the apparent concentration of the phosphatase at the bud tip , clearly experimental work is needed to determine how yeast pinch off endocytic vesicles in the absence of dynamin . Also , studies on the mechanisms that recruit PIP2 phosphatases to endocytic sites are needed . In fact , actin has been shown to recruit the phosphatase via the actin-binding protein Abp1 [11] , [35] , although this effect alone cannot account for the full phosphatase recruitment to the endocytic site in yeast [11] . What is not clear is whether actin or the actin-dependent membrane curvature , or the combined effects , are responsible for PIP2 phosphatase recruitment . In our model , we treated PIP2 phosphatase recruitment as curvature dependent without delving into the specific contributions of direct actin-mediated recruitment versus indirect membrane curvature-dependent recruitment . We can show that the curvature-dependence of PIP2 phosphatase recruitment is not essential for efficient endocytosis as long as the effective phosphatase recruitment rate is neither too fast nor too slow as compared to PIP2 synthesis ( Figure S4 ) and the hydrolysis rate is curvature-dependent . Future experimental studies must mechanistically address the contributions of BDPs , actin , and coat proteins in the vesicle formation process . In summary , our model is based on the notion that the local curvature of the endocytic membrane is both slave to , and master over , the accompanying biochemical reaction pathways . The coupling between curvature and biochemical reactions orchestrates a robust sequence of events leading to vesicle scission . Formulating the model in terms of functional modules allowed us to look beyond the molecular details and explore the larger features of how membrane dynamics and biochemical reactions fit together during endocytosis . This scheme can quantitatively describe clathrin-mediated endocytosis in budding yeast and the analogous process in mammalian cells . Thus , our model can serve as a unified framework for dissecting endocytosis in general . We incorporate the qualitative ingredients of the model into a set of quantitative equations . The detailed assumptions and the choices of the parameters are given in Protocol S1 . Equations 1–5 describe the dynamics of the chemical reactions of the functional modules on the surface of the endocytic membrane . Levels of functional modules are expressed as the coverage fraction ( mole fraction ) . We assume that the endocytic membrane has cylindrical symmetry . The local spatial coordinates along the membrane surface represent the arc length s with unit length 1 nm . The local membrane shape is uniquely defined by the tangent angle φ ( s ) and the radius r ( s ) ( see Figure 2 ) . The bud region is defined by the arc length s = 0–100; the tubule region is defined by s = 101–500 . PIP2 dynamics in the bud region ( Notation: P ) : ( 1a ) PIP2 dynamics in the tubule region: ( 1b ) Enzyme ( lipid phosphatase or lipase ) dynamics ( Notation: E ) : ( 2 ) Coat protein dynamics in the bud region ( Notation: C ) : ( 3 ) Actin dynamics in the bud region ( Notation: A ) : ( 4 ) BDP dynamics in the tubule region ( Notation: B ) : ( 5 ) In Equations 1–5 , Ω ( s ) and Ω ( R ) ( s ) are the mean curvature and the curvature in radial direction of the local membrane invagination , respectively , which are defined by local membrane orientation φ ( s ) and radius r ( s ) ( see Figure 2 and Protocol S1 for their formula ) . and are the preferred curvatures by coat proteins at the bud and by the BDPs at the tubule , respectively . ΩC and ΩB are the preferred curvatures for the bud region and the tubule region , respectively , when they are fully covered by their corresponding proteins ( C = 1 , B = 1 ) . The key mechanochemical couplings are: the PIP2 hydrolysis rate linearly depends on the local membrane curvature in Equation 1; BDP recruitment rate depends exponentially on its fit to the local membrane curvature in Equation 5 . Furthermore , term in Equation 5 represents the actin-aided BDP recruitment , where is the average actin level at the endocytic site ( see Protocol S1 for details ) . The feedback between the chemical reactions and the membrane shape is specified by how the local chemical reactions directly control the membrane dynamics . The membrane dynamics is governed by Equation 6: ( 6 ) Here , F[φ ( s ) ] is the Helfrich-like free energy for the endocytic membrane , which is characterized by the membrane bending energy and surface tension that specify the energy penalty associated with membrane deformations . Γ is the relative timescale of the membrane dynamics compared to the local chemical reactions . Equation 6 describes the membrane dynamics affected by the interfacial force λ , the spontaneous curvatures , and the pulling force f in the bud region , which are all controlled by the local chemical reactions . The interfacial force λ is a function of the PIP2 level difference across the interface between the bud region and the tubule region , , where λ0 is the interfacial force constant and s = 100 is the interfacial boundary position ( see Figure 2 ) . Note that the pulling force on the bud region must anchor to the coat protein to be effective . We neglect protein diffusion in Equations 1–5 and the in-plane hydrodynamics of membrane flow in Equation 6 . The justifications for these assumptions are given in Protocol S1 .
Endocytosis is a complex and efficient process that cells utilize to take up nutrients and communicate with other cells . Eukaryotes have diverse endocytic pathways with two common features , mechanical and chemical . Proper mechanical forces are necessary to deform the plasma membrane and , eventually , pinch off the cargo-laden endocytic vesicles; and tightly regulated endocytic protein assembly and disassembly reactions drive the progression of endocytosis . Many experiments have yielded a lot of detailed information on the sub-processes of endocytosis , but how these sub-processes fit together into a coherent process in vivo is still not clear . To address this question , we constructed the first integrated theoretical model of endocytic vesicle formation , building on detailed knowledge from experiments in yeast . The key notion is that the mechanical force generation during endocytosis is both slave to , and master over , the accompanying endocytic reaction pathway , which is mediated by local membrane curvature . Our model can quantitatively recapitulate the endocytic events leading to vesicle scission in budding yeast and can explain key aspects of mammalian endocytosis . The phenotypes predicted from variations within the feedback components of our model reproduce observed mutant phenotypes , and we predict additional unique and testable endocytic phenotypes in yeast and mammalian cells . We further demonstrate that the functional significance of such mechanochemical feedback is to ensure the robustness of endocytic vesicle scission .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "cell", "biology/cell", "signaling", "biophysics/theory", "and", "simulation", "cell", "biology/membranes", "and", "sorting", "biophysics/membrane", "proteins", "and", "energy", "transduction", "computational", "biology/systems", "biology", "cell", "biology/cytoskeleton" ]
2009
The Mechanochemistry of Endocytosis
Synapses on dendritic spines of pyramidal neurons show a remarkable ability to induce phosphorylation of transcription factors at the nuclear level with a short latency , incompatible with a diffusion process from the dendritic spines to the nucleus . To account for these findings , we formulated a novel extension of the classical cable theory by considering the fact that the endoplasmic reticulum ( ER ) is an effective charge separator , forming an intrinsic compartment that extends from the spine to the nuclear membrane . We use realistic parameters to show that an electrotonic signal may be transmitted along the ER from the dendritic spines to the nucleus . We found that this type of signal transduction can additionally account for the remarkable ability of the cell nucleus to differentiate between depolarizing synaptic signals that originate from the dendritic spines and back-propagating action potentials . This study considers a novel computational role for dendritic spines , and sheds new light on how spines and ER may jointly create an additional level of processing within the single neuron . Glutamatergic synaptic inputs onto dendritic spines of pyramidal neurons induce phosphorylation of the transcription factor CREB ( cAMP-Responsive-Element Binding protein ) in the nucleus [1]–[3] . CREB phosphorylation is important for converting specific synaptic inputs into long-term memory in several animal species [4] , [5] . Interestingly , action potential ( AP ) trains induced post-synaptically by direct intracellular current injection fail to initiate CREB phosphorylation [1] , [6] . Several studies [1]–[3] , [7] , [8] have aimed at finding the spine-to-nucleus signaling involved in CREB phosphorylation that enables the nucleus to discriminate between orthodromic and antidromic signals . The nature of this signal transduction , however , remained unclear . It has been shown that bulk elevation in cytosolic Ca2+ is neither necessary nor sufficient for activity-dependent CREB phosphorylation [1] , [2] , [7] . It was further shown that regenerative Ca2+ waves along the dendritic endoplasmic-reticulum ( ER ) are not necessary for mediating this synapse-to-nucleus signaling [1] . The means by which signals travel from spines to nucleus has therefore been suggested to involve diffusion of a second messenger . Since the Ca2+-Calmodulin complex ( Ca2+/CaM ) is readily generated in the spine during synaptic activity and since activity-dependent CREB phosphorylation follows translocation of Ca2+/CaM from cytosol to nucleus , Ca2+/CaM diffusion was suggested to carry the spine-to-nucleus signal [3] , [8] . However , CREB phosphorylation appears 15 seconds after the beginning of the stimulus , which is substantially faster than expected from diffusion of CaM [8] . During a 15 second period , the mean-square displacement of CaM is 5 µm , whereas the diameter of pyramidal somata ranges between 15–20 µm and the most proximal spines do not appear within 10–15 µm from the soma ( spine density approaches zero at the first 25 µm , [9] , [10] and the first spine was reported to appear 39 . 7±12 . 1 µm from the soma [9] ) . Mermelstein et al . have therefore suggested that CaM diffuses in a phosphorylated form , which can reach 20 µm during 15 seconds due to an increased cytoplasmic diffusion rate . This suggestion , which provides the best , up-to-date , estimate for synapse-to-nucleus signaling , disregards the fact that the spine neck acts as a diffusion barrier for second messengers as small as cAMP , cGMP , and IP3 [11] , [12] ( molecular weights 300–1000 D; Compared with 16 . 8 kD [13] for CaM ) . We hereby suggest an alternative means of signal transduction that readily complies with the described time frame of spine-to-nucleus signaling , namely , an electrotonic signal along internal membranes ( Table 1 [8] , [14]–[16] ) . By the end of the 90's it was acknowledged that the endoplasmic reticulum ( ER ) forms a continuous network of tubes and sacs that extends from the nuclear envelope out to the cell periphery [17]–[20] . This view followed studies which employed EM reconstruction [18] and diffusion of dye along internal membranes [20] to show the ER continuity across the axon , soma , dendrites and the spine apparatus at the dendritic spines' heads . Accordingly , the ER has been suggested to act as a ‘neuron-within-neuron’ , as originally suggested by Michael Berridge [21] . However , until now signal propagation and integration along the ER have been described to take place via regenerative Ca2+ wave [21] . Here , we propose a passive electrotonic potential along the ER lumen and across the ER membrane ( Figure 1A ) . This hypothesis is supported by reconstruction studies of spiny dendrites describing the ER as a continuous network of anastomosing tubes running parallel to the longitudinal axis of the dendrite [22] and extends , virtually , into all mature dendritic spines [18] , [20] . This hypothesis is further supported by direct recordings from ER in skinned myocytes having an input resistance of ∼850 MΩ and a resting membrane potential around 0 mV between the ER lumen and the cytosol [23] ( values of ∼7 . 5 kΩ/cm2 and 15–20 mV were estimated earlier for ER membrane specific resistance [24] and membrane potential [25] , respectively ) . Those studies provide the experimental grounds for suggesting that ER membrane can separate charges and that it exhibits a specific resistance that is similar in magnitude to the plasma membrane ( e . g . a typical input resistance for L2/3 pyramidal cells is around 100 MΩ [26] with 20 kΩ/cm2 specific resistance for plasma membrane [27] ) . In order to test the suggested hypothesis against realistic parameters , provide realistic predictions and enable analytic study of the theory , we developed a mathematical model of a cable-in-cable , thereby generalizing the classical cable theory developed by Rall [28] ( Figure 1B and 1C ) . The model shows that current flow along a system of a cable-in-cable ( CIC ) would , essentially , follow the predictions of the classical cable theory along the external cable ( i . e . the plasma membrane ) , but at the same time , would exhibit counter-intuitive properties over the internal cable , which cannot be predicted by the classical cable theory . Using the CIC model we show that under realistic parameters the excitatory synaptic activity can give rise to an EPSP-like depolarization across the nuclear envelope , whereas a depolarizing signal initiating at the soma ( e . g . action potential ) would result in hyperpolarization of the nuclear envelope . This study provides a novel electrotonic explanation for the ability of the neuronal nucleus to discriminate between orthodromic and antidromic sources of membrane depolarizations . The study further predicts a novel role for compartmentalization of Ca2+ within dendritic spines and proposes an additional dimension for synaptic plasticity . The cable-in-cable model principally follows the conventional cable theory and represents the internal membrane system as one passive internal cable that lies within another passive cable of plasma membrane . The key assumptions of the model , ER continuity [17]–[20] and its ability to separate charge similar to the external membrane [23]–[25] , rely on reports employing different experimental approaches . To simplify the qualitative description of the CIC theory , the analytical description of the cable-in-cable is reduced into 4 non-dimensional parameters: the ratio between ER diameter and the PM diameter ( E ) , the fraction of the non-conductive cross-section ( e . g . mitochondria , nucleus ) from the PM cross-section ( N ) , the ratio between membrane resistivity of ER and PM ( m ) and the ratio between the current actively injected into the ER and the current injected into the PM ( I ) . The CIC model can be viewed as an extension to the conventional cable theory , as it collapses to the traditional equations when the internal cable is reduced to zero ( E = 0 ) and no axial obstacles are allowed ( N = 0; for details see ‘Non-dimensional representation’ in the Methods section ) . The CIC system demonstrates a few noteworthy , qualitative properties: ( 1 ) The CIC system is governed by two space constants , where both space-constants affect each of the membranes; ( 2 ) As the transmembrane potential along the internal cable ( VmE ) is given by the difference between two decaying exponents ( the potential in the cytosol , Vi , and the potential inside the ER , VER ) , it is capable of generating an intriguing non-monotonic pattern as shown in Figure 2A ( inset ) . Namely , localized injection of current into the CIC system would induce depolarization at the external cable and hyperpolarization at the internal cable . However , while in both cases the transmembrane potential would approach zero with distance , the transmembrane potential across the internal cable would continue rising with distance , beyond zero , to form a region of depolarization and thereafter it would decay again to zero . We term the area , where a locally-distinct region of depolarization emerges along the internal cable after a segment of hyperpolarization , ‘virtual electrode’ ( VE; Dashed area in Figure 2A; see Discussion for details ) . Using the realistic parameters described in Table 2 , we plotted the steady-state potential inside the cytosolic compartment ( Vi ) and inside the ER lumen ( VER ) following local current injection into an infinite CIC system . Figure 2A shows that under these parameters the potential along both compartments ( i . e . cytosol and ER-lumen ) decays gradually towards zero . Nevertheless , the transmembrane potential along the internal membrane , given by the difference between these two compartments ( VmE≡VER−Vi ) , forms a virtual electrode ( inset of Figure 2A ) . The VE starts and reaches its peak depolarization after a distance of ∼0 . 6 and ∼1 . 3 electrotonic units , respectively . The electrotonic unit followed the space constant definition used by the conventional cable theory ( defined by Eq . G2 . 1 in the Methods section ) , which is equivalent to ∼1 mm using the parameters in Table 2 . The conventional cable theory is well supported by numerous transmembrane recordings . It is therefore interesting to compare the transmembrane potential along the plasma membrane predicted by the CIC model and the transmembrane potential predicted by the conventional model . Figure 2B shows the steady-state change across the external cable ( plasma membrane; VmP ) and compares it to the prediction of the conventional cable theory ( see ‘Space constant considerations’ in Methods for details ) . Both models predict exponential decay of transmembrane potential along the plasma membrane , whereas the difference between these two predictions for VmP is negligible ( ∼1–2%; Figure 2B ) and therefore , would be difficult to detect empirically . In order to test the significance of the VE amplitude , its peak was compared to the EPSP amplitude . We , therefore , normalized the VE amplitude to the EPSP ( Normalized VE Amplitude; nVE ) by dividing VmE by the amplitude of the VmP at the position where the VE-peak occurred ( Figure 2C ) . Thus , the peak amplitude of nVE represents , in percents , the ratio between VE-peak and EPSP at the same position and time . Depending on the specific set of CIC parameters the amplitudes of the VE-peak exhibit EPSP-like levels ( nVE range 150%–10%; Figure 2D ) . Moreover , representing the VE amplitude by nVE is underestimating the relation between VE amplitude and EPSP amplitude , since the ratio between the depolarization across the internal cable ( the VE amplitude ) and the potential along the external cable ( the EPSP amplitude ) , gets bigger with distance ( Figure 2C and 2D , dashed lines ) . Thus , the fraction of VmE amplitude relative to the local EPSP amplitude is substantially larger at positions beyond the VE peak . Moreover , when the initial EPSP amplitude ( i . e . at the synapse ) is altered , the proportion between transmembrane potentials of the internal and external cables is maintained , indicating that the relation between EPSP and VE amplitudes is determined by the specific cable parameters and not affected by changes in synaptic efficacy ( see inset for Figure 3B ) . An analytic rationale for relating the VE amplitude to VmP arrives from Equations H13 . 1 and H13 . 2 , which show that at any point in space and time , the amplitudes of both transmembrane potentials are linearly dependent on VmP ( x = 0 , t ) , the transmembrane potentials across the plasma membrane at the synapse ( or dependent on Ii ( x = 0 , t ) , the axial current entering the cytosolic compartment at the synapse; since VmP ( x = 0 , t ) = Ii ( x = 0 , t ) ·ri ) . Namely , the ratio between VmE ( x , t ) and VmP ( x , t ) along a given CIC system ( i . e . the pattern over space and time ) is fixed and not affected by the magnitude of the synaptic signal . Thus , introducing a realistic set of parameters to the CIC model predicts that excitatory synaptic activity can give rise to depolarization across the internal membrane , with an EPSP-like amplitude at a realistic distance from the synapse . Moreover , the unique VE-shape of transmembrane potential along the internal cable can explain the ability of the cell's nucleus to differentiate between dendritic origin and somatic origin of a depolarizing signal . Namely , a depolarizing signal that is proximal to the target ( e . g . antidromic signal originating from the soma ) would hyperpolarize the internal membrane at the target ( i . e . around the nucleus ) , whereas depolarizing signals with remote origin would depolarize the internal membrane at the target . The effect of the signal along the internal cable ( i . e . the VE ) would be further subjected to modulations of synaptic efficacy ( e . g . LTP or LTD ) . Evidently , different synaptic inputs originate from a wide range of distances from the cell nucleus . Yet , the VE predicted by the CIC model is essentially a spatial phenomenon that reaches its peak at a fixed distance from the synapse namely , the distance between the VE-peak and the synapse is fixed for any given set of passive cable properties , regardless of the initial potential at the synapse . It is , therefore , interesting to examine its range limits and its significance for distal synapses . For that purpose let us define imER and imPL , as the currents that are actively injected across the ER membrane and across the plasma membrane at the synapse ( x = 0 ) , respectively ( see Discussion for an actual mechanism which may generate imER in synchrony with imPL ) . As illustrated by the circuit in Figure 1C ( and implemented in Eq . D1–D5 formulating the Kirchhoff's law ) , Ii ( x = 0 ) is given by the difference between imPL , the current actively entering the cytosol through plasma membrane , and imER , the current actively leaving the cytosol into the ER lumen at the synapse; whereas , IER ( x = 0 ) is given by imER , the current actively entering the ER lumen through the ER membrane at the synapse . Along distance , Ii ( x = 0 ) leaks out to the external compartment and also into the ER lumen , thereby feeding the axial currents Ie and IER , respectively . The rest of Ii ( x = 0 ) travels axially along the cytosol as Ii ( as illustrated in the inset to Figure 1A and 1C and formulated in the ‘Methods’ ) . Accordingly , imER represents a supplementary current that is generated by active processes at the ER membrane simultaneously with the specific synaptic activity . Positive imER would , therefore , augment IER and diminish Ii whereas negative imER would diminish IER and augment Ii . Alternatively , the effect of imER may be simplistically illustrated as an increase ( for imER>0 ) or a decrease ( for imER<0 ) of the VmE at the synapse ( VmE ( x = 0 ) ; red curve in Figure 2A ) The analytical description of the transmembrane potential along the internal cable ( Eq . H13 . 2 in the ‘Methods’ section ) suggests that the ratio ( I ) between the initial axial currents at the synapse ( ; Eq . G1 . 4 , G1 . 5 ) can modify the pattern of transmembrane potential along distance . Since this ratio is determined at the synapse , we found it interesting to single out the qualitative features of the VE that are governed by I . As a first step in answering this question , we used the realistic set of parameters in Table 2 , for plotting the effect of I on the amplitude and location of VE's peak . Figure 3 shows that VE location can be greatly modified by I ( Figure 3A and 3B ) with no effect on nVE amplitude ( Figure 3B , inset ) . The ability of the CIC system to generate the VE pattern along the internal cable without active current injection into the ER-lumen indicates that the principle VE pattern can be induced passively following synaptic activity , whereas VE location can be further tuned by active processes at the synapse-ER complex . Examples for actual processes which may involve negative and positive imER are activation of Ryanodine receptors and/or activity of the electrogenic SERCA pumps . Both are localized at the ER in the spine heads and both processes can be triggered by excitatory synaptic activity ( via calcium influx through activation of glutamate receptors; see Discussion for details ) . This ability of an individual synapse-ER complex to determine the VE location may play two roles: First , it may serve as a mechanism for compensating for the wide range of synapse-to-nucleus distances and second , it can introduce a parallel level of synaptic plasticity , which is specifically modulating the synapse-to-nucleus signal in a manner that is largely independent of the efficacy of the specific synapse ( i . e . the EPSP ) . This second level of synaptic plasticity is demonstrated in Figure 3C , where VmE level at a wide range of arbitrary distances from the synapse , can be modulated or inversed , solely , by properties of the individual synapse ( range: −200% to +100% of EPSP ) . Thus , local modulations of the internal compartment at the synapse are capable of introducing a second level of synaptic plasticity , which would modulate the effect of the VE signal on the nucleus . Such modulations could be facilitated by passive properties ( e . g . local changes in membrane permeability or surface area of the ER at the synapse ) as well as by active properties ( e . g . electrogenic pumps and ion channels; see Discussion for details ) . The majority of the synaptic activity in the cortex is mediated by glutamatergic synapses onto pyramidal neurons . These synapses terminate on mushroom-like structures , dendritic spines . Principally , the above description of VE along the ER can be generated by a synapse located directly on the dendritic shafts . Does the CIC hypothesis predict an advantage of introducing synaptic input via secluded compartments such as dendritic spines ? A plausible answer to this question may be linked to compartmentalization of Ca2+ dynamics , which is commonly conceived as one of the main roles of dendritic spines . Excitatory synaptic activation on a dendritic spine initiates Ca2+ influx into the spine mainly through glutamatergic receptors ( i . e . N-methyl D-aspartate receptors; NMDAR ) . Approximately 30% of the Ca2+ entering the spine is carried into the ER lumen by the electrogenic [29] Ca2+ pump , SERCA ( Sarcoplasmic Endoplasmic Reticulum Calcium-ATPase ) [11] . Additionally , Ca2+ influx into the spine has been suggested to induce Ca2+-induced Ca2+ release ( CICR ) from the ER within the spine [30] , [31] . Thus , excitatory synaptic activity onto the spine is coupled with positive and/or negative Ca2+-mediated currents flowing into the ER lumen at the spine head . In the context of the CIC system , these two processes actively govern the I ratio presented above . Under the assumption that VEs play a role in synaptic signaling , one would expect that the synaptic parameter governing their properties ( i . e . the ratio I ) would be synapse-specific . Namely , different synapses would maintain different I ratios . In order to achieve this , ( 1 ) the ER segment , which directly responds to the increase in cytosolic Ca2+ , should employ different levels of CICR and SERCA; and ( 2 ) the cytosolic Ca2+ elevation evoked by synaptic activity should be confined to that specific segment of ER ( i . e . confined to the ER segment which binds a particular I ratio to a specific synapse ) . Figure 3D presents the predicted spatial decay of Ca2+ level along the distance from a point source of Ca2+ in the cytoplasm with endogenous Ca2+-buffer . ( The endogenous Ca2+-buffer parameters were taken from Naraghi et al . [32] and the calculations employed conventional models [33] , [34] ) . This estimate demonstrates that , under realistic spine density of 20–30 spines per 10 µm [35] , [36] ( up to 60 spines per 10 µm where reported [10] at the distal dendritic branches ) , activation of a single glutamatergic synapse is expected to trigger calcium-induced currents at multiple surrounding synapses . Namely , in order to enable a synapse-specific I ratio and comply with the realistic spine density , the spatial expansion of Ca2+ elevation should be significantly restricted by at least one order of magnitude . Therefore , we suggest that compartmentalization of free calcium by the dendritic spines is essential for maintaining synapse-specific tuning of signaling via VE along the internal membrane . This assumption is further supported by experimental evidence indicating that each dendritic spine usually accommodates a single synapse [37] , [38] . A pivotal stage in processing synaptic inputs is their convergence and integration at the soma , which leads to initiation of action potentials ( APs ) and activation of transcription factors at the nucleus . The soma is typically characterized by two anatomical features: ( 1 ) it is the widest region of the neuron and ( 2 ) it contains the cell nucleus . If VE participates in synapse-to-nucleus signaling it is useful to examine the CIC system at the transition from the dendrite to the soma . In order to model the effect of dendrite-to-soma transition of the VE signal , a second CIC compartment ( somatic-CIC ) was connected to the CIC system described above ( for details regarding multiple CIC systems please find ‘Finite CIC system with arbitrary boundary conditions’ in ‘Methods’ ) . The somatic-CIC construct was aimed at representing the soma at the peri-nuclear region . The peri-nuclear region is characterized by two nuclear envelopes ( NE ) , where the outer envelope is continuous with the ER membrane [39] . These two envelopes enclose the nucleus and form between them a space that is continuous with the ER lumen [39] . The NE allows continuity between the nucleoplasm and the cytosol through nuclear pores ( P; about 9 nm in diameter , see Figure 4A ) . The nuclear pores allow non-selective flux of ions and therefore enable electrical continuity between cytoplasm and nucleoplasm . For illustrating the VE at the peri-nuclear region the somatic-CIC had wider diameter ( 16 µm ) and included an initial part with narrow cytosolic cross-section ( representing the perinuclear area ) followed by a part with larger non-conductive cross-secession , representing the nucleus ( Figure 4B ) . Except for these parameters the others parameters were kept as described above ( Table 2 ) . Figure 4C shows a simulation of two VE signals arriving at the soma from two electrotonically-dispersed synapses . It illustrates ( in Figure 4C , right ) that the transition from a dendritic-CIC into somatic-CIC may act on disperse VEs as a “converging lens” . Namely , amplifying the VEs amplitude and converging them to the soma . This converging effect of the soma preserves the ability of current ratio at the dendritic spine ( I ) to modulate the VE amplitude and actual manifestation at the nucleus . The VE pattern displayed above represents the steady-state difference between potentials in the ER-lumen and in the cytosol . However , since actual synaptic currents are confined in time , the validity of a steady-state description of VE needs to be evaluated at the time scale of synaptic input duration . To address this question , we simulated the ER-membrane potential at several time points after the beginning of synaptic activity . We described CIC dynamics by units of the conventional membrane time constant ( τm; τm≡RmCm ) , which is equivalent to 48 ms under our specific parameters ( Table 2 ) . Indeed , Figure 5A shows that VE pattern is not a unique steady-state phenomenon , as it is already established within 0 . 005 time constants ( equivalent to 0 . 2 . 5 ms ) whereas the amplitude of its peak develops over time similarly to the development of an EPSP over time ( Figure 5B ) . Figure 3A ( dashed line ) shows that while the VE travels ( electrochemically ) along the internal cable , the ratio between the amplitudes of the VE-peak and EPSP ( nVE ) is higher than the steady-state ratio at the final position of the VE-peak . In order to get a better estimate of the VE kinetics over time , we compared ( Figure 5C ) the change over time of the two transmembrane potentials ( VmE and VmP ) at the position of the VE peak ( X = 1 . 29; the peak of the blue trace , T = 100 , in Figure 5A ) . We therefore used the conventional cable theory [40] for simulating the development of plasma-membrane potential , VmP , over-time ( as described explicitly in Eq . I1 in the Methods ) . Using the conventional spatio-temporal solution described by Jack et al . [40] ( Eq . I1 ) and the conventional definition for traveling speed of electrotonic signals , Figure 5D , reveals that VmE amplitude rises , to its steady-state level , slightly faster than EPSP amplitude . Moreover , despite the fact that the electrotonic time constants are the same for both the inner and outer cables , the VE pattern and its amplitude are established dramatically faster than the EPSP , at the segment around VE-peak ( Figure 5C and 5D ) . The fact that at the position of VE-peak , VmE amplitude reaches its steady-state level within ∼0 . 6 time constants ( 29 ms ) and thereafter overshoots its steady-state peak by 20% shows higher efficacy for VE as electrotonic signal for signal durations around 1 time constant . This is in line with the typical duration of the synaptic current induced by glutamatergic synapse ( EPSC's time to 50% decay: ∼10 ms [41] ) and the expected time for it to spread out to that position . In conclusion , time domain analysis shows that electrotonic signaling by means of VE along the internal cable has kinetics that are similar and slightly faster than electrotonic kinetics of the EPSP along the external cable . The comparable kinetics indicates that VE can , similarly , convey synaptic signals induced by realistic synaptic current duration . Altogether , time domain analysis demonstrates that the steady-state analysis provides plausible representation of VE . ER is conventionally regarded as an unstructured network of tubes and sacs . Thus , an equivalent cylinder with a cross-section similar to the axial cross-section of the ER network may misrepresent the effective axial resistance along the ER lumen . For example , a cross-section measurement of a single tube tangled in a bigger volume will appear misleadingly higher than the actual cross-section available for an axial current traveling along that tube , generating an underestimation of the actual axial resistance along that tube . Thus , lumen cross-section in an unstructured network can not faithfully represent the effective axial cross-section . However , a detailed structural study of the neuronal ER architecture by Martone et al . [22] , reveals that the ER in the dendrites of a spiny neuron forms a network of tubules running in parallel to the longitudinal axis of the dendrite . Thus , dendritic ER architecture appears to support axial conductance , whereby axial ER cross-section provides a more realistic estimation for its axial resistance . A key question that lies beyond the focus of our electrotonic model is: how would a depolarization at the ER pass a signal into the cell nucleus ? One plausible route may be electrotonic signals across the nuclear envelopes ( NEs ) . Since the ER lumen is continuous with the lumen between the inner and outer nuclear envelopes and the nucleoplasm is continuous with the cytosolic compartment via holes ( i . e . the nuclear pores ) through the NEs , the transmembrane potential across the NEs follows the transmembrane potential changes across the ER ( namely , VE ) . Thus , voltage-sensitive properties across the ER membrane forming the outer nuclear envelope , may mediate the signal into the nucleus . This proposal for nuclear signaling is in line with reports about several types of voltage sensitive ER channels [23] , [42]–[46] provide partial support this possibility . A second option is an initiation of locally-distinct perinuclear , Ca2+ signals , which may have a bearing on nuclear moieties . A single VE or sequence of multiple VEs may initiate and modulate theses signals through activation of voltage-sensitive properties cross the ER membrane . The fact that Ca2+-elevation in the nucleus is necessary for numerous nuclear activities and specifically activity-dependent CREB phosphorylation [3] , [47] , implies that voltage-activated Ca2+-channels may initiate a local Ca2+ signal that will be amplified and modulated by Ca2+-activated Ca2+-channels . This possibility is supported by ( 1 ) experimental reports from the CNS [43] and from non-nerve tissue [44] describing ER Ca2+ channels which increase their opening probability sharply by depolarization; and ( 2 ) studies showing that the inner NE expresses intracellular Ca-activated Ca release channel , i . e . inositol 1 , 4 , 5-trisphosphate receptors ( IP3Rs ) and ryanodine receptors ( RyRs ) [48] , [49] . Moreover , this explanation is consistent with various experimental observations showing that: ( 1 ) locally-distinct cytoplasmic events of ER-Ca2+-release ( e . g . Ca2+ puffs ) , originating within a 2–3 micron perinuclear zone , appear to initiate Ca2+ elevation in the nucleus , [50] ( 2 ) The NE is a functional calcium store [51] , [52] and Ca2+ signals within the nucleus can be evoked in the absence of elevation in cytosolic Ca2+ [48] , [51] , [52] . Thus , co-localization of VE with voltage-sensitive channels [23] , [42] , [45] , [46] , voltage-sensitive calcium channels and calcium-sensitive calcium channels [48] , [49] along the ER at the nuclear envelopes , is one possibility for instantly coupling VE with perinuclear and nuclear calcium signals . Such machinery introduces a new layer of Ca2+-mediated control of nuclear function in neurons and , possibly , in non-neuronal cells . Modification of the effect that a specific synaptic activity has on the postsynaptic cell is conventionally termed synaptic plasticity . This theoretical study shows that a synapse-specific property , the I ratio ( defined in Eq . G1 . 4 ) , can modulate the effect a specific synaptic activity has on the transmembrane potential across the nuclear envelopes of the postsynaptic cell . Modification of the synapse-specific I ratio may , therefore , represent a second level of synaptic plasticity . Figure 3C shows that regardless of the strength of the signal across the plasma membrane ( e . g . EPSP ) , the signal across the internal membrane ( VE ) at an arbitrary distance from the synapse can be set exclusively by the I ratio to be positive , negative or zero . Nevertheless , the magnitude the VE signal will be subjected to the conventional synaptic plasticity as well ( i . e . potentiation or depression of EPSP ) . This suggests that the synapse-to-nucleus signal bares the capability for independent synaptic plasticity at various ranges of electrotonic distances between synapse and nucleus . One plausible physiological mechanism , which may sustain a synapse-specific I ratio modulation , may be electrogenic calcium fluxes across the ER membrane at the synapse . This suggestion is inline with the fact that a typical EPSP in the cortex , which is generated by glutamatergic synaptic activity onto dendritic spines , involves calcium influx from the extracellular compartment into the specific spine head . The extension of the ER into the spine head ( spine apparatus ) exhibits capabilities to link elevation in spine-calcium into inward or outward currents across the ER at the spine . Inward calcium-dependent current across the ER may be mediated by the electrogenic activity of SERCA pumps [29] , whereas outward currents across the ER in the spine head may be mediated by Ca2+-sensitive channels [31] . Immunocytochmical studies shows that RyR labeling is notable in dendritic spines of cortical pyramidal cells , whereas their dendritic shafts are mostly unlabeled [53] . A large body of theoretical studies supported by experimental data [11] , [54]–[57] shows that the interaction between SERCA , RyR , IP3R , endogenic buffers and intracellular calcium stores can generate a wide variety of Ca2+ dynamics , which are fundamentally dependent on the temporal pattern of Ca2+-inputs . Taken together , the spine head seems to contain the hardware necessary for generating synapse-specific modulation in VE , which may be further modified by the pattern of the specific synaptic input . This assumption may be further supported by the facts that: ( 1 ) the majority of excitatory communication in the cortex is mediated via dendritic spines which are structures that can compartmentalized Ca2+ [11]; ( 2 ) each spine head receives a single glutamatergic synaptic input [37] , [38]; and that ( 3 ) pyramidal neurons , the main source for glutamatergic synaptic inputs in the cortex , respond to their preferred sensory input by burst patterns of action potentials . Thus , the CIC prediction for the I ratio combined with the current knowledge on excitatory synaptic signaling in the cortex , provide circumstantial support to the existence of synaptic plasticity of the spine-to-nucleus signaling , which may be further modified by the pattern of the specific synaptic input . Evidently , the VE pattern and amplitude is parameter-dependent . For ruling out the possibility that the model's predictions are specific to a narrow range of parameters ( as described in Table 2 ) , we evaluated the robustness of its predictions over a wide range of parameters . Using one-dimensional parameter-mapping , we show ( Figure 6 ) that VE along the internal cable is a reliable phenomenon and its amplitude has an EPSP-like magnitude . For simplicity , we focused our study on analytical description of the CIC theory and therefore we have neglected the role of ER curvatures . Likewise , for simplifying the time-domain analysis , we have assumed that the inner and outer the cables have identical time-constants ( τm ) . Nevertheless , we allowed different membrane-specific resistivities for ER and PM ( ; Eq . G1 . 2 ) , and kept the similar time constant for both PM and ER membranes by constraining the relation of the two membrane-specific capacitances ( ; Eq . H8 ) . This constraint over the relation between the two membrane-specific capacitances does not affect the analytical analysis of different membrane resistivities at steady-state . One of the major features of the ER , which was neglected in our study , is the network structure of the ER . One may ask whether this simplification can breach the prediction of the CIC model ? Apparently , the principal prediction of the CIC model , the VE , is in line with a model specifically developed for describing a network of passive cable elements , [58] the unequal anisotropic bidomain model ( for review see [59] ) . Moreover , virtual electrodes predicted by the bidomain model have been demonstrated empirically over cardiac myocardium [60] , [61] . Thus , the ability of a network of passive cable elements to generate VE , is well supported . The CIC theory provides several experimentally testable predictions . Interestingly , we found that each prediction can be supported ( at least partially ) by recent experimental reports . The first prediction resolves the question presented above , regarding the traveling speed of the ‘synapse-to-CREB’ signal . The CIC model predicts that ( 1st prediction ) synapse-to-nucleus signaling would exhibit an electrotonically-fast propagation velocity that is 2 or 3 orders of magnitudes higher than expected from a regenerative Ca2+-wave or diffusion of a second messenger ( i . e . kinase-bound CaM , proposed previously ) , respectively ( see Table 1 ) . This prediction is in line with the ‘synapse-to-CREB’ time ( ∼15 seconds ) reported by Mermelstein et al . [8] . Moreover , this prediction expands our ability to comprehend the way synapses , as myriad sources of fast electrical signals , communicate their information stream to the distant nucleus . The CIC model suggests that active properties within the spine heads ( e . g . Ca2+-mediated currents across the spine apparatus , via SERCA pumps , ryanodine receptors and IP3 receptors ) encode an additional level of synaptic plasticity by determining the efficacy of the VE at the nucleus . This suggests that ( 2nd prediction ) as an information-encoding parameter , spine Ca2+-dynamics would exhibit high variability between spines in the same cell and spines in the same cell group . Namely , measurements of the fraction of Ca2+ , which enters the ER at the spine head following excitatory synaptic activity , would show a wide range of values between spines of similar neurons at similar location . This prediction is supported by Sabatini et al . [11] who measured the fraction of Ca2+ entering the ER at the spine head of CA1 pyramidal neurons . The CIC model shows that the ability of a dendritic spine to induce effective VE at the nucleus is impaired if the spine is too close to the cell nucleus . Therefore , some properties of dendritic spines are predicted to undergo gradual change in relation to their distance from the nucleus . For example ( 3rd prediction ) spines , which otherwise exhibit high density along the dendrites , should be absent from the soma and proximal part of the dendrites , which has been observed in several studies [9] , [10] , [35] , [37] , [62] , [63] . Likewise , it is expected ( 4th prediction ) that on average , a proximal spine would exhibit a lower activity of CICR and/or higher activity of SERCA , compared to a dendritic spine located at remote dendritic regions . Similarly , for facilitating the passive conductance of synaptic currents into the ER , ( 5th prediction ) the ER branch at the spine head ( the spine apparatus ) should exhibit varying degrees of laminar organization and increased surface area compared to the spine head enclosing it [64] . For example , the ratio between the surface area of the spine apparatus and spine head would be ( on average ) greater for spines which are distal from the nucleus . These last two predictions should be testable by appropriate physiological , immunocytochemical and morphological experiments . Finally , while activation of glutamatergic synapses at the dendrite induces robust CREB phosphorylation at the nucleus , ( 6th prediction ) a concomitant activation of extra-synaptic glutamatergic receptors at the soma would suppress the electrotonic induction of VE at the nucleus and therefore suppress CREB activation . This prediction is supported by Hardingham et al . [65] who showed that , while synaptic activation of glutamatergic synapses induces CREB phosphorylation , bath application of glutamate suppresses it . One way of obtaining direct experimental evidence is to apply the patch clamp technique for recording and manipulating the transmembrane potential simultaneously across both the ER and the PL , during synaptic activity . This can be achieved by employing the pipette-within-pipette patching technique described by Jonas et al [66] . Although this approach would be technically challenging , its successful application would enable a simultaneous recording of the two transmembrane potentials . Such an experiment would directly address the question of whether a direct interaction is present or not . In summary , the significant contribution of the current study is proposing a VE along the ER membrane as a means of ultra-fast intracellular signal transduction and demonstrating its feasibility under realistic parameters using a cable-in-cable model . The CIC hypothesis presented here contributes also by introducing the possibility of an additional level of synaptic plasticity and a new perspective for the role of dendritic spines , which densely populates the dendrites of spiny neurons . Since ER is continuous also in non-neuronal cells , electrotonic signaling along internal membranes may act as a general means of fast signaling between cell periphery and nucleus and other sub-cellular compartments . This study shows that intracellular level biophysical theory may introduce concepts and principles that appear counter-intuitive with views originating from conventional cellular level electrophysiology , suggesting that the phenomenological richness of intracellular architecture and the associated electrophysiology may still offer surprises . The model follows the classic cable theory [40] , [67] , [68] and introduces a model of a cable in cable . We used Mathematica5 ( Wolfram Research ) for numerical calculation and for checking the analytical derivations . Model assumptions are: The equations below follow the circuit in Figure 1C . The parameters and their definitions are provided in Table 2 . A . Ohmic Axial current: ( A1 ) ( A2 ) ( A3 ) B . Total axial current ( IT ) is constant: ( B1 ) C . Radial ( trans-membranal ) currents in a cable with no additional current source: ( C1 ) ( C2 ) D . Kirchhoff's law: ( Inward current is defined , negative ) ( D1 ) ( D2 ) Therefore: ( D3 ) ( D4 ) ( D5 ) A system of ODE is obtained from combining all the above: ( E1 ) ( E2 ) ( E3 ) The system can be represented as: where ( E4 ) The general steady-state solution is characterized by two space constants ( ) given as the sum of two decaying exponents: ( F1 ) ( F2 ) For the explicit solution , see ‘Time Domain’ below . We found it advantageous to describe the solution ( Eq . F1 and Eq . F2 ) by four non-dimensional and independent parameters . For that purpose we defined the following parameters ( Eq . G1 . 1–G1 . 4 ) : Note that ( Eq . G1 . 5; see text for details ) The conventional cable theory defines the space constant ( λ ) as: . Under the assumption that re→0 , λ is often represented as . In order to avoid non-specific parameters ( ri , rm ) we followed the second representation and defined: ( G2 . 1 ) Non-dimensional scaling is obtained by defining: ( G2 . 2 - G2 . 5 ) For non-steady state conditions the trans-membranal current of cylindrical cable includes transient capacitance currents and is given by: ( H1 ) where: Accordingly , ImP and ImE can be described as ( H2 ) ( H3 ) The ODE system becomeswhere: M1 is as described above ( Eq . E4 ) ( H4 ) For enabling the analytical solution we assumed similar time constant ( τm ) for both PM and ER membranes . We , therefore , defined specific membrane parameters ( Cm , Rm ) : τm≡Rm·Cm , Cm≡CmP and Rm≡RmP ( Eq . H5–H7 ) ( Units: sec , F/cm2 , Ω·cm2 , respectively ) . We allowed different membrane-specific resistivities for ER and PM ( ; Eq . G1 . 2 ) , and forced a similar time constant RmE· CmE = τm ( = RmP· CmP ) for both PM and ER membranes by assuming: ( H8 ) This assumption ( Eq . H8 ) , which is taken for enabling an analytical solution for the time-domain ( see below ) , do not affect the steady-state solution . By incorporating the specific membrane parameters ( Eq . H5–H8 ) , matrices M1 and M2 become: ( H9 ) ( H10 ) where: The system becomes: where:The non-dimensional representation of the system is: where: Eigenvalues of : ( H12 ) where: κe→0 The explicit solution ( obtained analytically using Laplace transform ) [40] is: ( H13 . 1 ) ( H13 . 2 ) where VmP ( X , T ) ≡Vi ( X , T ) −Ve ( X , T ) and VmE ( X , T ) ≡VER ( X , T ) −Vi ( X , T ) . ( Note that VmP ( X , T ) = Vi ( X , T ) under the assumption that Ve ( X , T ) →0 ) where ƒ is a non-dimensional function of X and T: ( H14 . 1 ) where erfc is the complementary error-function: erfc ( x ) ≡1−erf ( x ) Note that at steady-stat ( T→∞ ) : fi ( X , T ) →1 where λ1 , λ2 are non-dimensional space constants: ( H14 . 2 ) ( H14 . 3 ) Note that for any realistic set of parameters: {0≤N<1 , 0≤E<1 , 0<m , 0< ( 1−N−E2 ) } As a result: λ1 and λ2 has real solution where C1–C5 are constants defined as followed: ( H14 . 4 ) ( H14 . 5 ) ( Note that ( 1−N−E2 ) describes the fraction of the cytosolic cross-section and therefore: ( 1−N−E2 ) >0 ) ( H14 . 6 ) ( H14 . 7 ) ( H14 . 8 ) Note that when the internal cable collapses to zero ( E = 0 ) and no axial obstacles are allowed ( N = 0 ) , the system collapses to the conventional cable equation . Namely , , C1→1 , C2→0 , C3→1 , ( C4 , C5 are not defined ) and make Eq . H13 . 1 collapses into the traditional solution: . It can be shown that when E = 0 , the CIC system collapses to the conventional cable equation , for any realistic N: {0≤N<1} ( see ‘Space constant considerations’ below , for details ) . Where the electrotonic kinetics predicted by CIC model are compared with those predicted by the conventional cable theory , we followed the conventional spatio-temporal solution described by Jack et al . [40]: ( 11 ) where erfc is the complementary error-function: erfc ( x ) ≡1−erf ( x ) . The classic cable theory assumes no obstacles for the axial current . It practically defines an effective axial intracellular resistivity , Ri , which is already adjusted ( empirically ) to the actual non-conductive cross-sections ( e . g . mitochondria ) along the specific cable . In contrast , the CIC model incorporates an independent , axial non-conductive cross-section . Therefore , the CIC model assumes that the axial intracellular resistivity represents a cytoplasm without non-conductive cross-sections . Evidently , this deviation from the convention is inevitable if axial obstacles should not be omitted from the CIC model . This difference in terminology can be rectified as described blow . The relation between Ri , RC and non-conductive cross-sections ( N ) along the cable becomes:where RC is the axial intracellular resistivity , specific for a cytoplasm without non-conductive cross-sections . Accordingly , N is incorporated in the conventional space-constant ( λN ) as:Thus , when the internal cable collapses to zero ( E = 0 ) and axial obstacles are allowed {0≤N<1} , the system collapses to the conventional cable equation with space-constant λN . Namely , , C1→1 , C2→0 , C3→1 , {C4 , C5 are not defined} which makes Eq . H13 . 1 collapses into the traditional solution [40] , formulated in Eq . I1:orwhere . In Figure 2B we compared the potential along the external cable ( VmP ( X ) ) predicted by the classic theory and the VmP ( X ) predicted by the CIC model . In that calculation we followed an empirical definition and defined the classic-model's space constant by fitting a single exponent to two points along the CIC prediction for VmP ( X ) . The first point was X = 0 ( VmP ( X ) = VmP ( 0 ) ) and the second point was arbitrarily chosen as the point where VmE ( X ) = 0 . Nevertheless , we also tested a second approach for defining a single space constant to the CIC system using λN ( as described above ) . Under both approaches the difference between the two predictions is too small to be detected experimentally ( within range of few percentages of the initial potential , VmP ( 0 ) ) . Explicit solution for finite CIC at steady-state with arbitrary boundary conditions . Boundary conditions: VmP ( 0 ) , VmER ( 0 ) Initial potentials at: X = 0 VmP ( L ) , VmER ( L ) Ending potentials at: X = L The explicit solution:where a is an index that takes values 0 or L in the expressions aboveWhen {L→∞} , the above explicit solution for finite CIC gives the CIC solution for semi-finite CIC ( provided in Eq . H13 . 1–H14 . 8 ) at steady state: where Within the classic cable-theory the conventional definition for input resistance ( namely the ratio between potential and current at the point where X = 0 ) provides a constant parameter , which is solely determined by structural cable properties . Applying that definition for input resistance to the semi-finite CIC system , produces an expression which , in addition to structural cable properties , also includes the ratio between the initial potentials ( or currents ) at the ER lumen and the cytosolic compartment . Accordingly , at identical position and CIC structure , different synaptic signals ( i . e . different I parameters ) are subjected to different input resistance:where all the definitions follow the definition given in the main text ( see Eq . H13 . 1–H14 . 8 ) . Similarly , the conventional definition of resistance at the finite CIC , depends on the ratio between the potentials of ER lumen and the cytosolic compartment at the initial point and at the ending point , as well as the electrotonic length of the specific finite CIC . For simplicity , the calculation of successive CIC systems , in Figure 4 , approximated the input resistance at each finite CIC system to be determined only by the ratio of the initial potentials . In the interest of completeness we also provide a more detailed expression of the input resistance in a finite CIC system without employing the approximation of the input resistance at each finite CIC system by being determined only by the ratio of the initial potentials . The explicit solution for the steady-state input resistance of finite CIC with arbitrary boundary condition:
Our study incorporates the fact that the endoplasmic reticulum ( ER ) forms a complete continuum from the spine head to the nuclear envelope and suggests that electrical current flow in a neuron may be better described by a cable-within-a-cable system , where synaptic current flows simultaneously in the medium between the cell membrane and the ER , and within the ER ( the internal cable ) . Our paper provides a novel extension to the classical cable theory ( namely , cable-within-cable theory ) and presents several interesting predictions . We show that some of these predictions are supported by recent experiments , whereas the principal hypothesis may shed new light on some puzzling observations related to signaling from synapse-to-nucleus . Overall , we show that intracellular-level electrophysiology may introduce principles that appear counter-intuitive with views originating from conventional cellular-level electrophysiology .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "cell", "biology/nuclear", "structure", "and", "function", "computational", "biology/transcriptional", "regulation", "cell", "biology/cell", "signaling", "physiology/neuronal", "signaling", "mechanisms", "biophysics/theory", "and", "simulation", "cell", "biology/neuronal", "signaling", "mechanisms", "physiology/cell", "signaling", "neuroscience/neuronal", "signaling", "mechanisms", "neuroscience/theoretical", "neuroscience" ]
2008
Electrotonic Signals along Intracellular Membranes May Interconnect Dendritic Spines and Nucleus
The enzymatic control of the setting and maintenance of symmetric and non-symmetric DNA methylation patterns in a particular genome context is not well understood . Here , we describe a comprehensive analysis of DNA methylation patterns generated by high resolution sequencing of hairpin-bisulfite amplicons of selected single copy genes and repetitive elements ( LINE1 , B1 , IAP-LTR-retrotransposons , and major satellites ) . The analysis unambiguously identifies a substantial amount of regional incomplete methylation maintenance , i . e . hemimethylated CpG positions , with variant degrees among cell types . Moreover , non-CpG cytosine methylation is confined to ESCs and exclusively catalysed by Dnmt3a and Dnmt3b . This sequence position– , cell type– , and region-dependent non-CpG methylation is strongly linked to neighboring CpG methylation and requires the presence of Dnmt3L . The generation of a comprehensive data set of 146 , 000 CpG dyads was used to apply and develop parameter estimated hidden Markov models ( HMM ) to calculate the relative contribution of DNA methyltransferases ( Dnmts ) for de novo and maintenance DNA methylation . The comparative modelling included wild-type ESCs and mutant ESCs deficient for Dnmt1 , Dnmt3a , Dnmt3b , or Dnmt3a/3b , respectively . The HMM analysis identifies a considerable de novo methylation activity for Dnmt1 at certain repetitive elements and single copy sequences . Dnmt3a and Dnmt3b contribute de novo function . However , both enzymes are also essential to maintain symmetrical CpG methylation at distinct repetitive and single copy sequences in ESCs . DNA methylation at the C-5 positions of cytosine ( 5mC ) is a key epigenetic modification in mammals essential for normal development [1] , [2] . Cytosine methylation is predominantly found in CpG dinucleotide context and about 70 to 80% of all CpGs are methylated . These methylated CpGs are usually located in CpG poor regions and often in repetitive sequences [3]–[5] . About 40% of the genome consists of repetitive elements . Four main groups of repetitive elements can be discriminated: long interspersed nuclear elements ( LINEs ) , short interspersed nuclear elements ( SINEs ) , long-terminal repeat ( LTR ) retrotransposons and ( peri- ) centromeric satellites . For these elements , the maintenance of DNA methylation during development and aging is important for transcriptional silencing and genome stability [6] , [7] . The establishment and maintenance of methylation patterns at palindromic CpG sequences ( CpG dyads ) is performed by three catalytically active DNA methyltransferases ( Dnmts ) . In vitro experiments suggest that Dnmt1 prefers hemimethylated CpG ( hemi-mCpG ) dyads and maintains the methylation pattern on the newly synthesized strand after replication ( maintenance methylation ) . In vitro , Dnmt1 shows a low activity on unmethylated CpG dyads . Dnmt3a and Dnmt3b methylate DNA de novo , independent of the methylation status of the complementary CpG position [8] , [9] . In vitro analyses furthermore suggest that methylation by Dnmt3b and the maintenance function of Dnmt1 mostly occur in a processive manner , whereas Dnmt3a and the “de novo function” of Dnmt1 are distributive [9]–[12] . However , other groups observe a processive methylation activity for Dnmt3a [13] . In addition , Dnmt activities are modulated by Nuclear protein of 95 kDa ( Np95; also known as Uhrf1 ) and Dnmt3L . Dnmt3L , a cofactor for the de novo methyltransferases , is reported to stimulate Dnmt3a/3b activity , to be needed for de novo establishment for imprint methylation and furthermore to enhance the processive methylation activity of human Dnmt3a [13]–[15] . Np95 is recruiting Dnmt1 to hemimethylated DNA and is interacting with Dnmt3a/3b for gene silencing [16]–[18] . Despite of a lot of in vitro data on Dnmt specificities and interacting partners , relatively little is known about the concerted action in vivo in the genome context and at different types of repetitive elements . Data on ESCs with individual and combined Dnmt knockouts indicated preferences of Dnmts for specific repetitive elements [19] . Different mathematical models were developed to simulate the kinetics of DNA methylation [20]–[25] . However , these calculations were only theoretical or based on only scarce sequencing data . Moreover , most data sets used were based on the bisulfite analysis of only one DNA strand and/or did not discriminate between single Dnmt functions . In this paper , we present the first comprehensive high resolution methylation analysis for both DNA strands of distinct classes of repetitive elements and four single copy genes known to be methylated in ESCs . Using hairpin linker technology combined with 454 sequencing , we generated individual patterns from embryonic fibroblasts , liver cells , wt ESCs and ESCs depleted for Dnmt1 , Dnmt3a , Dnmt3b , Dnmt3a/b , Dnmt3L , Np95 and Suv39h . The Dnmt KO data sets were then used to calculate Dnmt efficiencies with improved hidden Markov models ( HMM ) , extending previous elegant approaches by Sontag et al . and Genereux et al . [20] , [25] . The comparative prediction/validation analysis documents a more differentiated view on the relative contributions of individual Dnmts for maintenance and de novo methylation of CpG positions . In addition , the comprehensive hairpin technology allowed us to unambiguously identify the presence and the patterns of non-CpG methylation . We designed specific hairpin linker protocols to amplify representative fragments of the four major classes of repetitive elements and four single copy genes from bisulfite treated mouse DNA to obtain the methylation pattern of complementary CpGs ( CpG dyads ) ( see for a general scheme Figure S1 and for details see Materials and Methods S1 ) . The repetitive elements selected were i ) major Satellites , ii ) IAPLTR1 , a class of LTR-retrotransposons , iii ) the 5′ untranslated region of L1Md_Tf , a long interspersed element ( LINE ) and iv ) B1 elements , representing a class of short interspersed elements ( SINEs ) ( see Figure S2 for locations and Table S1 for references ) . In this paper , we conveniently refer to the specific repetitive elements as mSat , IAP , L1 and B1 , respectively . In addition , we established assays for four single copy genes: alpha feto protein ( Afp ) , testis expressed gene 13 ( Tex13 ) , insulin growth factor 2 ( Igf2 ) and Small nuclear ribonucleoprotein-associated protein N ( Snrpn ) . Following amplification , PCR products were sequenced on a 454 GS-FLX sequencer with an average read length of 200–400 bp covering 3 to 12 CpG dyads of the respective amplicons . The addition of a hairpin linker containing several unmodified cytosines allowed us to directly monitor the bisulfite conversion rates per sequenced molecule . In the linker sequences , the conversion rates ranged from 97 , 9 to 99 , 9% , with only B1 showing conversion rates below 98 . 7% , probably due to the more degenerate sequence composition and occasional back-folding ( Table S2 ) . In contrast to conventional single strand bisulfite sequencing , hairpin bisulfite sequencing allows one to unambiguously distinguish between unmethylated and mutated CpG sites . We identify mutated CpGs in all repetitive elements to various extents ( see white positions in Figure 1 ) . A particular abundance of mutated CpGs was found in B1 elements with 44% of CpGs being mutated to TpG ( Figure S3a ) . Previous single strand bisulfite sequencing accounted such TpGs as unmethylated positions estimating the total methylation of B1 elements to be only 10% [26] . When correcting for mutated sites , we find B1 elements to be methylated up to 80% in wt cells ( Figure S3b ) . Following a precise alignment to reference sequences using BiQAnalyzerHT [27] and the back mapping of complementary CpG positions , we first compared the DNA methylation patterns between mouse wt ESC lines , mouse embryonic liver and cultured mouse embryonic fibroblasts ( MEFs ) ( Figure 1 and Figure 2 ) . In general , mSat , IAPs , B1 , Afp and Tex13 are highly methylated in all wt ESC and somatic cells ( 62–95% ) , whereas L1 is highly methylated in somatic cells , but only 30 to 52% in ESCs . Igf2 shows in all cell types an intermediate methylation level ( Figure S3b ) . The hairpin-bisulfite method allows to unambiguously discriminate between unmethylated , hemimethylated and fully methylated CpG dyads . Since it is believed that the maintenance of methylation is very stable and occurs semi-conservative , hemimethylated sites should occur very rarely . The analyses of human DNA showed that hemi-mCpGs occur between 4 . 8% ( sperm ) and 20 . 8% ( leukocytes ) at human LINE1 elements [24] , [28] and 7% hemi-mCpG at human Satellite 2 sequences in different tissues [29] . We found in the analysed mouse cells a range of 1 to 25% of all CpGs in a hemimethylated status across all amplicons ( Figure 1 and Figure 2 ) . In differentiated cells , hemimethylated sites occur equally distributed across the analysed sequences - MEFs show the lowest and least variable rate of hemi-mCpG ( 5 , 8 to 12% of all methylated CpG dyads ) among the analysed elements and in embryonic liver an overall high amount of hemi-mCpGs is detected ( 16 , 2 to 30 , 6% of all methylated CpG dyads ) ( Figure S3c ) . Contrarily , in ESCs the degree of hemimethylation is much more variable at the different types of repetitive elements . While hemimethylation levels are low for IAPs ( 9 , 3 to 12 , 5% ) Tex13 , Afp and Snrpn ( 3 , 8 to 7% ) , more than 35% of methylated CpGs in L1 and 22% at Igf2 are hemimethylated . Moreover , the extent of hemi-mCpGs at mSat and B1 greatly varied between the three wt ESC lines , but the general tendencies for particular elements are maintained . The almost exclusive fully or unmethylated patterns of the imprinted gene Snrpn ( and H19 , data not shown ) show the stable maintenance of two non-equilibrium states . The imprinted genes are very important internal controls showing i ) that the enzymes responsible for full maintenance are present and fully functional ii ) that the occurance of hemimethylated states in other genes/elements is not simple due to an increase of cells analysed in S-phase ( i . e . incompleted replications states ) in fast dividing ESCs . Next , we analysed the contributions of Dnmts and cofactors for the maintenance of the methylation pattern by comparing hairpin-bisulfite sequence data of ESCs mutated for Dnmt1 , Dnmt3a , Dnmt3b , Dnmt3a and 3b ( DKO ) , Dnmt3L and Np95 ( UHRF1 ) , respectively ( Figure 2 and Figure 3a ) . Deletion of Dnmt1 caused a substantial reduction of DNA methylation in all analysed elements ( mSat methylation was reduced by 65% , IAP by 72% , L1 by 76% and B1 by 75% , Tex13 by 82% , Afp by 75% , Igf2 by 82% and Snrpn by 99% , respectively ) . This tendency was also observed in previous low resolution data obtained for a subset of repetitive sequence elements [19] , [30] . Our deep sequencing data however clearly shows that a small subset of sequences maintain a considerable amount of hemi- and fully methylated sites . A triple knockout cell line ( TKO , data not shown ) does not show any signs of DNA methylation anymore . The effects of Np95 KO at repetitive elements were very similar but not identical to the Dnmt1 KO ( see also Bostick et al . [16] ) indicating that the major activity of Dnmt1 is indeed mediated by Np95 [16] , [17] . In contrast to a general hypomethylation at all elements in Dnmt1/Np95 KOs , the loss of Dnmt3 activities led to element and enzyme specific differences . While methylation at IAP , mSat , Tex13 and Afp did not greatly change in Dnmt3a or Dnmt3b single KOs , the double KO led to a clear decrease of CpG methylation at mSat ( 24% ) , IAPs ( 17% ) , Tex13 ( 41% ) and Afp ( 53% ) . Methylation at L1 and B1 did not change in the Dnmt3b single KO , but was strongly decreased in the Dnmt3a single KO by 64% for L1 and 37% for B1 . Igf2 shows decreased level for Dnmt3a and Dnmt3b single KOs ( 53% for Dnmt3a KO , 34% for Dnmt3b KO ) . For all three sequences ( L1 , B1 and Igf2 ) in the DKO , there is only minor methylation left . Hence , while either the loss of Dnmt3a or Dnmt3b , respectively , can be compensated by the other enzyme at IAPs , mSat , Afp and Tex13 sequences , the situation is more complex at B1 , L1 and Igf2 . Finally , Dnmt3L also contributes to maintain a high level of methylation . In the Dnmt3L KO the loss of methylation at all regions is less extensive than in the Dnmt3a/3b DKO , arguing for a stimulatory effect of Dnmt3L on both de novo Dnmts . Note that Dnmt3L KO cells were at passage 15 and underwent already almost twice the amount of replications than the Dnmt3a/b DKO ( passage 8 ) . For all sequences , we observe a strong increase in the relative amount of hemi-mCpGs ( in regard to total methylation ) in Dnmt1 KO and Np95 KO ( Figure 2 , Figure 3b ) , along with a huge loss of overall methylation . This observation highlights the important role of Dnmt1 in maintaining symmetrical CpG methylation . However , it is very intriguing that in both Dnmt1 and Np95 null backgrounds , we still find a considerable amount of sequences with fully methylated CpG dyads ( Figure 2 , Figure 3a and 3c ) . Chromosomal sequences with hemi-mCpG sites on only the upper or lower strand , respectively , were found frequently , compared to sequences with ( dispersed ) hemi-mCpG sites on both upper and lower strands . Such dispersed hemimethylation was found in WT ESCs in <2% of mSat , <3 , 4% of B1 , <4 , 5% of IAP and <7 , 2% of L1 reads , respectively ( see Figure 3c ) . Note that in Dnmt1KO and/or Np95KO ESCs dispersed hemi-mCpGs were enriched compared to WT . In contrast to the Dnmt1 KO and Np95 KO , respectively , the abundance of hemimethylated sites does not differ between WT and Dnmt3a/Dnmt3b single KOs and double KO . The double stranded hairpin sequencing data allowed to unambiguously assign cytosine methylation outside of CpGs . We identified clear non-CpG ( mostly CpA ) methylation in mSat sequences and the Afp gene in WT ESC lines ( Figure 4a and 4b , Figure 5a ) . This non-CpG methylation is much less pronounced , more sporadic , less position dependent or barely detectable at the other elements ( Figure S4 ) . In mSat and Afp amplicons , respectively , cytosines at five non-CpG positions showed a significant methylation ( in 6–12% of all reads ) clearly above the conversion background of 1 . 1% ( as defined by linker sequence conversion , see above ) . Most bisulfite unconverted ( methylated ) positions are found in the CpA sequence context . Interestingly , in most of the sequence reads only one single CpA methylated position was detected; such that 75% for mSat and 55% for Afp of J1 reads had clear single CpA methylation ( Figure S5 ) . Finally , our data confirm that methylated cytosines ( above technical background ) outside of the CpG context are not detectable in differentiated cells ( embryonic liver and MEFs ( Figure 4b , Figure 5a ) . By comparing the presence of methylated cytosines in non-CpG context between wt and the different KO ESC lines ( Figure 4b , Figure 5a ) , we found that in Dnmt1 KO the methylation at all non-CpG positions remained unchanged despite the greatly reduced CpG methylation level . Notably , we found enrichment in CpG methylation at sequences showing non-CpG methylation ( Figure 4c , 4d ) . Moreover , by correlating CpA methylation to CpG methylation in the Dnmt1 KO , we found that CpA methylation is highly linked to neighboured methylated CpG positions at mSat and Afp ( Figure 4e and Figure 5b ) In Dnmt3a/3b DKO , CpA methylation above background is completely absent and surprisingly for mSat Dnmt3a and Dnmt3b single KO showed different pattern of CpA methylation . Whereas CpA methylation at position 6 and 11 is greatly reduced in a Dnmt3a KO , the loss of Dnmt3b diminishes CpA methylation at position 4 , 22 and 28 . Interestingly , the loss of Dnmt3L greatly reduces the methylation at most positions . At the Afp gene , non-CpG methylation also strictly depends on Dnmt3a/3b in combination with Dnmt3L - although here Dnmt3b apparently plays a less important role . Together these findings clearly point towards a position specific exclusive Dnmt3a and 3b mediated CpA methylation guided by Dnmt3L . The Suv39h1/2 mediated modification of histone H3 at position 9 was reported to influence the targeting of DNA methylation . We therefore included ESCs and MEFs with KO for Suv39h1 and Suv39h2 ( Suv39dn ) in our analysis for the repetitive elements . Suv39dn ESCs were reported to lack H3K9 trimethylation and Dnmt3b localisation at pericentric heterochromatin . Lehnertz et al . reported reduced DNA methylation ( by southern blot ) at mSat in Suv39h KO but not at minor Satellites or a C-type retrovirus [31] . Our hairpin bisulfite analysis confirmed this finding on a sequencing basis . DNA methylation at major satellites is reduced by 20% in Suv39dn ESCs , but not at B1 , IAP and Line1 elements . Surprisingly , the effect on mSat methylation is almost absent in dnMEFs , which retain 95% of wt methylation ( Figure S6a ) . Finally , despite of the proposed interaction of Suv39h with Dnmt3b at mSat , we do not observe any influence of the Suv39h absence on CpA methylation , particularly not at the Dnmt3b specific positions 4 , 22 and 28 ( Figure S6b ) . The precise determination of fully methylated , hemimethylated and unmethylated CpG dyads in the comparative data set of some 28 . 000 sequences ( around 146 . 000 CpG dyads ) including wt ESCs and Dnmt KOs allowed us to calculate the element specific methylation efficiencies for the different catalytically active Dnmts in a modified version of the linear HMM proposed by Sontag et al . [20] . We computed maximum likelihood estimates for both methylation efficiencies on unmethylated and hemimethylated CpG dyads separately . As opposed to previous calculations [24] , [25] , we used the information of Dnmt KOs , to combine these in a single model to obtain Dnmt specific efficiencies at unmethylated and hemimethylated CpG dyads . Furthermore , we did not assume that steady-states are reached in the KO ESC lines . Instead , we estimated the amount of cell generations and inferred parameters during the transient phase of the system , since at least Dnmt3a/3b DKO shows a progressive loss of DNA methylation with increasing passage number [32] . The estimated efficiencies with standard deviations are given in Figure 6a and Table S3 . The approximated standard deviations showed that for Dnmt1 efficiencies were accurately estimated for all sequences . For Dnmt3a and Dnmt3b standard deviations are too high for a conclusion at L1 , B1 and Afp . To substantiate the appropriateness of our model and the accuracy of our estimated methylation efficiencies , we predicted the DNA methylation level for the parental wt ESC line ( Figure 6b and Table S4 ) . Indeed , we found good predictions for all elements , with maximum error rates of 1 . 7% ( mSat ) , 4 , 1% ( IAP ) , 3 . 9% ( Tex13 ) , 2 . 7% ( Afp ) , 4 , 1% ( L1 ) , 5 , 9% ( B1 ) and 7 , 1% ( Igf2 ) . Based on the HMM calculations , we find a high activity of Dnmt1 on hemimethylated CpG dyads . This is 90% or higher for mSat , IAP , Tex13 , Afp and B1 , but remarkably lower for L1 and Igf2 . Furthermore , we found clear evidence for de novo methylation activity of Dnmt1 in vivo . However , it differs for the classes of repetitive elements and single copy genes . While Dnmt1 does not show a remarkable de novo methylation activity ( <0 . 02 ) for L1 , B1 and Igf2 , this activity is apparent at IAP , mSat , Tex13 and Afp with calculated efficiencies of 0 . 36 , 0 . 32 , 0 . 12 and 0 . 06 , respectively ( Figure 6a , Table S3 ) . Interestingly , for the de novo methyltransferases Dnmt3a and Dnmt3b , we observe a higher efficiency at hemimethylated sites for some targets , which contrasts in vitro derived data [8] , [9] . According to the changed methylation pattern observed in our hairpin-bisulfite analysis and the methylation probabilities of Dnmts estimated with our HMM , the analysed elements can be grouped into three different classes: ( i ) The imprinted genes ( Snrpn and H19 ( data not shown ) ) , which exclusively depend on Dnmt1 for maintenance methylation . ( ii ) IAP , mSat , Tex13 and Afp , which are mainly dependent on Dnmt1 ( methylation activity at unmethylated and hemimethylated CpG positions ) and show minor effect in the Dnmt3a/3b DKO and ( iii ) L1 , B1 and Igf2 , which need Dnmt1 ( only methylation activity at hemimethylated CpG positions ) and Dnmt3a/3b to work cooperatively . Thus , the HMM model shows that the maintenance contribution for specific genomic regions is clearly distinct from the Dnmt ( s ) contributions for the de novo acquisition of methylation . Here , the methylation of IAP and L1 is reported to be dependent on either Dnmt3a or Dnmt3b , whereas mSat need Dnmt3b and B1 elements Dnmt3a [33] . Our HMM applied to estimate methylation efficiencies significantly extends previous modelling approaches and allows to draw functional conclusions . First , by separating the effects of all three Dnmts based on KO data , we could estimate probabilities to methylate unmethylated or hemimethylated CpG positions for each enzyme independently . Second , our experimental strategy allowed to precisely assign CpG dyads and to account for experimental measurement errors ( bisulfite conversion and mutation errors ) as well as the number of cell divisions ( passages ) . Third , we employed numerical techniques to infer optimal methylation efficiencies since analytic solutions of our more complex model are infeasible . By integrating all these parameters , we could functionally extend the previous models developed by Genereux et al . and Sontag et al . [20] , [25] . Moreover , beyond prediction , our validations ( see Figure 6 , Table S4 ) demonstrate the appropriateness of the model at least for mSat , IAP , Tex13 and Igf2 . For B1 , L1 and Afp the prediction is very accurate even though the efficiencies of Dnmt3a/3b are difficult to estimate . In contrast to our estimations based on biological Dnmt KO data , a recently published model discriminates between the Dnmts only using theoretical considerations for the Dnmts on WT methylation pattern [34] . However , in this model the authors estimate the processivity of the Dnmts . It will be interesting to adapt their model , using our biological Dnmt KO data . For Dnmt1 , our HMM indicates a significant methylation probability at unmethylated CpG dyads ( de novo methylation ) in ESCs ( up to 22% ) , depending on the repetitive element/sequence . In vitro experiments analysing the methylation activity of Dnmt1 show 2 to 50 fold higher preference for hemim-CpG dyads , dependent on the substrate or conditions [35] . In vivo , we find 2 . 5 to 90 fold higher preference for hemimethylated CpGs . Interestingly , pre-existing methylated sites in vitro were shown to enhance the de novo methylation efficiency of Dnmt1 [12] , [36]–[38] . Our data corroborate these observations in vivo , linking an increased methylation to a higher de novo methylation activity of Dnmt1 ( CpG methylation and methylation activity at unmethylated CpGs is higher at IAP , mSat , Tex13 , Afp than both at L1 , B1 and Igf2 ) . Differential regulation of the CXXC domain binding capacities at the different sequences could influence the de novo methylation activity of Dnmt1 [39] . The fidelity for Dnmt1 to methylate hemi-mCpG dyads was shown to be 95% to 96% in vitro [12] . Our HMM predicts fidelities of methylating hemi-mCpGs for IAP , mSat , B1 , Tex13 and Afp of 90 to 95% , which fits quite well with the in vitro data . However , at L1 and Igf2 , the fidelity decreases to less than 80% . This lower fidelity at hemim-CpGs might arise from the presence of 5hmC at L1 elements and Igf2 ( see discussion next chapter , reference [40] , Figures S7 and S8 ) . 5hmC could hereby not only influence maintenance methylation but also de novo methylation activity , which is enhanced by 5mC content but presumably not 5hmC . For Dnmt3a and Dnmt3b , we found significant “maintenance” methylation activity . However , the ratio of de novo and maintenance methylation contributions differs across sequence elements . Such context dependent effects were not addressed in former in situ and in vitro modelling studies and may become only evident in the native chromatin context . Since in vitro Dnmt3a and 3b appear to methylate independent of the methylation status of the CpG dyad , the high contribution of Dnmt3a and 3b to maintain full methylation at CpG dyads following replication might be attributed to targeted and enhanced de novo activity stimulated by the presence of CpG methylation density . Some studies show that Dnmt3a/3b can strongly bind to nucleosomes containing methylated DNA [41] , [42] . By this Dnmt3a/3b could be triggered to “de novo” methylate hemimethylated sites following replication to maintain full methylation in the absence of Dnmt1 . Our experimental approach allowed us to unambiguously assign DNA methylation in total at about 280 . 000 CpG dyads at 4 repetitive elements and 4 single copy genes on both DNA strands . Besides a general prevalence for symmetrical methylation , we found a substantial portion of hemimethylated CpG dyads in all cell types analysed . The presence of such hemimethylated CpGs can be explained by three different mechanisms: i ) the improper recognition of modified cytosines and/or impaired maintenance activity , ii ) the selective de novo methylation or iii ) active DNA demethylation . In MEFs and embryonic liver , we find different global tendencies for the occurrence of hemimethylated sites at all analysed elements . However , all three Dnmts are expressed in both cell types ( Figure S9 ) . This suggests that in embryonic liver the maintenance fidelity of Dnmts is less pronounced or alternatively DNA demethylation is more pronounced . In ESCs , we observe only at L1 sequences and Igf2 a high level of hemimethylated sites . Apparently , in ESCs , the maintenance methylation machinery is less accurate only at specific sequences and from our data we see that a strong cooperativity of Dnmt1 , Dnmt3a and Dnmt3b is needed to maintain methylation at these sequences . The analyzed cell types show strong cell cycle differences . These might be regarded as reasons for methylation differences . Cultured and fast growing ESCs , for example have been shown to be almost 5 times more likely to be in S-Phase as compared to MEFs [43] , [44] . However , in our analysis ESCs show some sequences , which have the same amount of hemimethylated sites as MEFs . Furthermore , in fast growing embryonic liver we observe strong increases of reads showing hemimethylated sites next to fully methylated sites ( Figure S10 , fraction in dark green ) . We therefore regard it as unlikely that incomplete methylation can be reduced to the varying number of incomplete S-Phases in the different cell types . 5-hydroxymethylcytosine ( 5hmC ) might contribute to the increase of hemimethylated sites either by impairing maintenance methylation or inducing active DNA demethylation [45]–[48] . 5hmC was reported to be abundant in ESCs , but less so in cultured cells [49]–[51] . Indeed , there is a tendency that 5hmC enrichment is linked to the presence of hemimethylated CpG positions . While Igf2 and L1 regions have an increased level of hemimethylated CpGs and are enriched for 5hmC in ESCs , no ESC specific 5hmC enrichment is found at the Tex13 , Afp nor IAP loci , which only show few hemimethylated sites ( Figures S7 and S8 ) . Our HMM calculations indicate that in ESCs sequences enriched for 5hmC do not exhibit de novo methylation activity of Dnmt1 in contrast to 5hmC depleted sequences . Hence , 5hmC might not only impair maintenance methylation but also de novo methylation activity by Dnmt1 . However , whether 5hmC indeed blocks Dnmt1 mediated methylation remains to be resolved . Unfortunately , 5hmC profiles cannot be distinguished from 5mC by our bisulfite based sequencing [46] , [52] , [53] such that the influence of 5hmC on 5mC methylation cannot clearly be assigned . Moreover , the role of 5hmC may not be of importance in some cases , since Np95 apparently recognizes and binds to 5hmC containing DNA and may moderate an effect of 5hmC on Dnmt1 recognition [54] . Finally , a selective conversion of 5mC into 5hmC at individual CpGs could cause mosaic hemimethylated situations by inducing local ( hemi- ) demethylation . Two general mechanisms , a direct demethylation by further oxidation to carboxylcytosine and subsequent decarboxylation as well as DNA repair coupled processes have been discussed in this respect [46]–[48] . Indeed , the intriguing presence of 5hmC at Line1 and Igf2 regions analyzed might explain the extreme mosaic pictures at these elements . If this is true the estimated de novo methylation rates for both elements may be completely underestimated . To test if hemimethylated CpG positions are coupled to 5hmC , we analysed the methylation pattern of repetitive elements in the Tet1 KO ESCs . However , the Tet1 KO cells only show a 30% reduction of genome wide 5hmC [55] . We indeed see changed methylation patterns in L1 elements with a slightly increased amount of fully methylated CpG dyads ( Figure S11 ) . A combined analysis of Tet KO's ( i . e . Tet1+Tet2 ) might further substantiate the possible link between 5hmC and the increased occurrence of hemimethylated CpG dyads . DNA methylation outside of the CpG context was initially detected in mESCs using nearest neighbour analysis . This analysis revealed a strong prevalence for the CpA context and pointed towards a Dnmt3a dependency [56] . Recent genome wide single stranded bisulfite sequencing using Illumina short reads identified non-CpG methylation at various sequence contexts in human ESCs at rather high rates of 13–25% of all methylated Cs , mainly in CpA context [57]–[59] . In our data set covering a total of 280 . 000 individual CpG positions and up to 108 bases , we detect non-CpG methylation at specific positions mainly in a CpA context especially confined to mSat sequences and Afp . It is possible that the primer based amplification of our analysis caused some selection against non-CpG methylation and we therefore underestimate the amount of non-CpG methylation . Still , the position dependent non-CpG methylation remains outstanding . We found that non-CpG methylation is exclusively dependent on Dnmts 3a and 3b , in concordance with recent observation in human [59] . However , we can show that both methylate non-CpG positions only in combination with Dnmt3L . Neither the absence of Dnmt1 nor Np95 altered the non-CpG methylation . Moreover , the unchanged non-CpG methylation in Suv39hdn cells reveals that the proposed protective function of H3K9 trimethylation for non-CpG methylation may not be true for mSat [60] . The sequence analysis of Dnmt1 KOs unambiguously shows that non-CpG methylation is linked to Dnmt3a and Dnmt3b mediated CpG methylation . Along this line non-CpG positions are highly co-methylated with some neighbouring CpG positions ( Figure 4e , Figure 5b ) . A recent publication discusses a widespread unspecific non-conserved non-CpG pattern in human pluripotent cells [59] . This contrasts our findings in mouse ESCs , which suggests that non-CpG methylation is mostly locally confined to specific regions such as mSat and Afp and specific non-CpG positions . It will be important to substantiate non-symmetric methylation distribution in human by deep sequencing . Genome wide sequencing approaches at relative low coverage may easily overlook specific patterns as observed in our analysis . Our data lets us speculate that CpA methylation results from a position specific “side reaction” of Dnmt3a and Dnmt3b stimulated by Dnmt3L . In line with this , Holz-Schietinger et al . show that Dnmt3L increases the processivity of Dnmt3a [13] . Finally , Dnmt3L is much more expressed in ESCs compared to somatic cells , where we do not find any evidence for CpA methylation [61] . Comprehensive hairpin-bisulfite sequencing in Dnmt KO ESCs reveals a complex scenario of sequence , element and cell specific control of DNA methylation pattern at CpG dyads . Based on the sequencing data , we construct a greatly improved HMM , which reveals enzyme , cell type and genome position dependent de novo and maintenance methylation functions for all three Dnmts . This strongly supports previous conclusions by Fatemi et al 2002 and others , that in vivo neither de novo methylation can be exclusively assigned to Dnmt3a/3b nor maintenance methylation exclusively to Dnmt1 [62] . Position dependent non-CpG methylation , mainly in CpA context , occurs at major satellites and the Afp gene exclusively in ESCs . This non-CpG methylation is mediated by Dnmt3a and 3b , depends on the presence of Dnmt3L and is strongly correlated to the methylation of flanking CpG positions . The complete protocol is provided in the SI ( Materials and Methods S1 ) . Briefly , genomic DNA was digested with an element specific restriction enzyme and the upper strand and lower strand were linked with a hairpinoligonucleotide . After bisulfite treatment an element specific PCR was performed and the resulting product was sequenced with the 454 sequencing technique . We used CpG dyad methylation data on WT and DnmtKO ESCs in a hidden Markov model to estimate the Dnmt methylation efficiencies by the maximum likelihood method . A detailed description of the model is provided in the SI ( Materials and Methods S1 ) .
DNA methylation is a stable covalent epigenetic modification of cytosines mostly confined to CpG-dinucleotides in mammals . In general , it is associated with silencing of genomic DNA regions . Three catalytically active DNA methyltransferases ( Dnmts ) set and maintain CpG methylation in cooperation with other ( co- ) factors . The in vivo contribution of the Dnmts to maintain CpG and non-CpG methylation following rounds of DNA replication are not well understood , particularly since in vivo DNA methylation patterns can be highly dynamic . In our work , we use ultradeep sequencing to determine the methylation status of both DNA strands in ESCs depleted for Dnmts 1 , 3a , 3b , and 3L , respectively . Using hidden Markov models , we calculate the relative contribution of each of the enzymes for the maintenance of DNA methylation patterns using parameter estimated fitting . While in general the modelling supports a classification of Dnmts into maintenance and de novo functions , it argues against a strict enzyme specific functional categorisation . We observe evidence for a context-dependent contribution of Dnmts to set and maintain CpG and non-CpG methylation at distinct classes of repetitive elements and selected single copy genes . We furthermore unambiguously identify Dnmt3a/3b and 3L dependent non-CpG methylation at specific sequence positions and confined to ESCs .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genomics", "functional", "genomics", "genetics", "epigenetics", "biology", "dna", "modification", "genetics", "and", "genomics" ]
2012
In Vivo Control of CpG and Non-CpG DNA Methylation by DNA Methyltransferases
In species with large effective population sizes , highly expressed genes tend to be encoded by codons with highly abundant cognate tRNAs to maximize translation rate . However , there has been little evidence for a similar bias of synonymous codons in highly expressed human genes . Here , we ask instead whether there is evidence for the selection for codons associated with low abundance tRNAs . Rather than averaging the codon usage of complete genes , we scan the genes for windows with deviating codon usage . We show that there is a significant over representation of human genes that contain clusters of codons with low abundance cognate tRNAs . We name these regions , which on average have a 50% reduction in the amount of cognate tRNA available compared to the remainder of the gene , RTS ( rare tRNA score ) clusters . We observed a significant reduction in the substitution rate between the human RTS clusters and their orthologous chimp sequence , when compared to non–RTS cluster sequences . Overall , the genes with an RTS cluster have higher tissue specificity than the non–RTS cluster genes . Furthermore , these genes are functionally enriched for transcription regulation . As genes that regulate transcription in lower eukaryotes are known to be involved in translation on demand , this suggests that the mechanism of translation level expression regulation also exists within the human genome . Codon usage bias is abundant in every sequenced genome and several theories have been put forward to explain it , depending on the genome or the gene . In many organisms , including bacteria , yeast and Drosophila species , the strongest factor determining codon bias is selection for maximizing translation speed and accuracy [1]–[6] . Those genes that are the most highly expressed exhibit a bias towards codons that have the most abundant cognate tRNAs . It is not the case , however , that a maximal rate of translation always results in optimal protein production . In a handful of cases the synonymous mutation of a codon to the most translationally optimal will cause a phenotype [7] , [8] . In bacteria and yeast there are several well-studied mechanisms by which local variations in translation rate are an essential regulator of protein production [9]–[11] . Protein secondary structure is known to be influenced by the local rate of translation and translational pausing [see 12] . The stalling of translating ribosomes can allow nascent proteins the freedom to fold , or facilitate the interaction of chaperones/regulatory proteins , without the interference from the physiochemical properties of the downstream protein sequence [see 8] . Furthermore , different protein secondary structures are associated with codons with different translation rates . For example , in Escherichia coli , beta strands are more commonly associated with codons with low levels of cognate tRNAs , whereas alpha helices associate with codons with abundant cognate tRNAs [12] . More generally , rare codons are found near the boundaries of protein domains [12]–[14] in E . coli . Variable local translation rate is used in several species as an extension of expression level regulation . This is especially so in the case of trypanosomatids , which have little regulation of gene transcription and instead have been suggested to rely on mechanisms that influence the rate of translation to fine-tune protein levels [15] . The expression of genes can be down regulated at the translation level by a process called no-go decay ( NGD ) . This system is thought to be a safety mechanism to clear blocked mRNAs and is characterized by the dissociation of the stalled ribosome from the mRNA , followed by the degradation of both the nascent protein product and the mRNA [see 16] . NGD allows the translation at low levels of those genes that are highly transcribed . The presence of NGD , in turn , opens up the possibility for translation on demand , a mechanism thought to occur in Saccharomyces cerevisiae to minimize the reaction time to a stress stimulus . If , under normal conditions , translation is limited by ribosomes that stall at a specific mRNA position , then protein production can be rapidly up regulated in response to a stress factor by resuming translation . Regulating a response to stress via this path will elicit a faster response than if the control was solely at the level of transcription [17] . The genes most commonly regulated by translation on demand are transcription factors and those related to gene processing [18]: genes that can go on to alter the expression profile of other genes . In humans , there has been much contradictory and inconclusive evidence for the presence of selection for translation optimization [4] , [19]–[21] . There are several reasons for this lack of certainty . It is thought that selection for the purging of weakly deleterious mutations is relatively inefficient in mammals due to a limited effective population size [22] . In addition , a large component of codon bias in mammals can be explained by variations in the local GC content . There may also be a conflicting effect by purifying selection acting on exonic splicing regulatory elements , a mechanism not as prevalent in lower eukaryotes , with the potential ability to out compete any translation level selection [23] , [24] . More recently however , strong evidence has been provided that optimal codons ( those codons with the most abundant tRNAs ) associate with conserved sites within human genes [25] , prompting the proposal that there is selection to limit errors in translation of human genes . Further recent investigations by Kimchi-Sarfaty highlighted that synonymous changes for “slow” codons can have a detrimental effect in human genes [7] . In the specific case of MDR1 the disease phenotype is observed when a haplotype of SNPs for rare codons occur [7] . Kimchi-Sarfaty proposed that this is due to the effect of the rare codons on the translation rate , which compromises the folding of the nascent protein , thus diminishing the function of the mature protein . Regions of genes that may regulate the folding of mature proteins , by means of rare codon clusters , have been identified in two studies [26] , [27] . Widmann et al . assessed the usage of rare codons in genes from two families of α/β proteins and found that synonymous mutations in these clusters induce protein mis-folding [27] . The protein families investigated were those most likely to undergo co-translational protein folding , and thus , these results do not represent the incidence of any genome-wide phenomena . Clarke and Clark proposed a large-scale method for identifying gene segments of highly biased codons ( when compared to their potential maximum bias ) [26] . Both these studies ( mentioned above ) attributed the clustering of rare codons to constraints on protein folding . However , these two investigations may suffer from the assumptions that they have made . Firstly , both groups assume that the codons used most infrequently in the genome are those that will be the least translationally optimal . There is no evidence for this . If we take the number of cognate tRNA gene copies as a proxy for the rate of translation of the codon , then codons with the fewest tRNAs , and thus the lowest rate of translation , do not have the lowest genome frequency ( Figure 1 ) . Secondly , both groups identify codon bias within the genes relative to the whole genome codon usage , and ignore the variations in local GC content across the human genome . This approach may fall foul of isochore effects in mammalian genomes . We propose an alternate method to identify clusters of translation rate-limiting codons that may be of functional importance in human genes . This method is free from local nucleotide biases and assumptions about the usage of codons throughout the genome . Further , we assume that the largest factor determining the rate of translation of a codon is the number of cognate tRNA genes . With this approach we determine the prevalence of translation rate-limiting clusters in human genes and , without prior assumptions about their function , assess genic properties to infer the potential role of these clusters . To identify regions of genes that have the greatest potential to minimize the translation rate , we devised a measurement of corresponding tRNA abundance ( the anti-codon abundance score ) . This score assumes that there is a direct correlation between tRNA abundance and the number of tRNA genes; an assumption that previous investigations have shown is justified [2] , [28] , [29] . This scoring method allows us to directly compare the different amino acids within the same gene . We employed a sliding window analysis across 13 , 793 human genes and calculated the average anti-codon abundance score ( ACA score ) for each window ( see Methods and Figure 2 ) . The region of the gene with the lowest score was deemed to have the greatest putative role in the reduction of translation rate . This classification differs from other methods that found the regions of the greatest codon bias when compared to the codon usage of the whole genome , a method that does not guarantee that the region identified limits the translation rate . Our method identifies the absolute rate-limiting position within the gene , the region most likely to cause translation related regulatory effects . To test if the window with the lowest ACA score was expected given the underlying nucleotide content of the gene , or whether it occurred due to factors other than chance alone , we implemented a randomization analysis . For each gene , the existing codons were shuffled 1 , 000 times , maintaining the underlying gene codon usage and nucleotide biases , and the sliding window analysis was repeated . We identified 1703 genes with an original ACA score that was lower than at least 95% of the randomizations for that gene and 148 genes with an ACA score that was lower than 99 . 9% of the randomizations ( Figure 3 ) . Of course , in any large dataset of genes one would expect to find a number of genes with a low ACA score . To determine our false discovery rate , we employed the QVALUE software [30] , [31] . Provided with the distribution of p-values for all the genes , whether they were deemed significant or not , QVALUE will calculate the proportion of false positives that would be expected if a p-value was to be used as the significance cut-off . At our chosen significance threshold p-value of 5% , we had a false discovery rate of 23% . Thus , of our initial 1703 clusters that were found to have significantly low scores , 391 may have been falsely identified . Nevertheless , this leaves 1306 genes that are likely to be true positives . Thus , we find that up to 10% of the genes in the entire human gene set contain a region with a significantly low score . To the regions of the genes that we found to have significantly low scores we allocate the term RTS ( Rare tRNA Score ) clusters . It is possible that some amino acids are encoded by a set of synonymous codons that all have a relatively low number of tRNA genes . If these amino acids occur together in a protein domain , we could see significant RTS clusters due to constraints at the protein level . To evaluate the impact of protein level interference , we employed a second randomization . In order to control for local nucleotide biases and isochore effects , we binned the genes into 138 groups of 100 genes of similar G/C content at third codon positions ( GC3 ) . For each randomized iteration the amino acid sequence of the RTS cluster was maintained and the codons were randomly selected , weighted by the synonymous codon usage within the GC-bin . The new ACA score was calculated and compared to the original . The cluster was deemed free of protein level interference if less than 5% of the randomizations produced a lower score , indicating that the RTS clusters are not the result of the amino acid sequence . Under these criteria , 601 genes were further purged , leaving 1102 putative translation pausing sites with a false discovery rate of 2 . 6% [31] . It is these genes that have a significantly low ACA score , after controlling for local nucleotide biases and interference from the amino acid sequence , for which we implemented the remaining analyses . If the RTS clusters we have identified are functionally important , we expect that there should be conservation of the cluster region . To this end , we calculated the number of synonymous substitutions between human and chimp orthologues . As synonymous substitutions between human and chimp orthologues are not common , the number of substitutions in concatenated RTS cluster regions were compared to those of concatenated non-cluster regions of the genes , after controlling for the potential influence of splicing effects . Since the evolution rate near splice sites is reduced due to the conservation of exonic splicing enhancer elements [24] , [32] , [33] , we need to control for this within gene variation in the rate of evolution . We therefore focused our analysis on sequences distal to intron-exon boundaries . The orthologous human-chimp sequences were purged to contain only coding sequence that fell outside 70 nucleotides of a splice site . This cut-off has been used previously in the literature and it has been shown to contain the large majority of the regulatory elements; thus we assume that analyzing sequence outside this cut-off will control for a large amount of confounding effects [24] , [34] . The expected values of synonymous substitutions between RTS clusters and non-cluster regions were calculated under the assumption that within the splice site distal sequence the substitutions should be evenly distributed . Fisher's exact test of these expected values against the number of observed substitutions reveals that RTS cluster regions show a significant decrease in the number of synonymous substitutions ( 57% of the expected value , 24 observed versus 42 expected synonymous substitutions , p = 0 . 01 ) , indicating that the RTS clusters are conserved and are likely to be functionally important . Due to the relatively small effective population size of mammalian species , in addition to a lack of evidence for selection to purge weakly deleterious mutations in higher eukaryotes , it has been assumed that selection for a mechanism of gene regulation programmed within the coding sequence of mammals does not occur [43] , [44] . In this investigation , we show that clusters of codons with low cognate tRNA gene copy numbers are more common than expected given local codon usage and constraints from the amino acid sequence . The potential importance of these RTS clusters is highlighted by the significant reduction in synonymous substitutions in chimp orthologues at the RTS cluster regions . Further , these observations cannot be explained by confounding factors such as CpG islands or the presence of splicing regulatory elements . Opposed to observations in other species that beta sheet structures and the boundaries of protein domains are associated with the use of codons with low abundance cognate tRNAs [see 12] , [13] , [14 and also 8] , we observed no evidence to suggest that this occurs in humans . In fact , our RTS cluster genes are significantly underrepresented for α/β proteins , which evidence suggests are those most likely to undergo co-translational protein folding [41] . This may indicate that reduced translation rate has a negative impact on protein folding in humans , as observed in the case of MDR1 [7] . Intriguingly , we observed two skews in RTS cluster positions within the gene: those skewed to the 5′ region and those skewed to the 3′ gene region . We also found that RTS cluster genes have higher tissue specific expression profiles than the remaining RTS cluster–free genes . Additional evidence from the Gene Ontology analysis revealed a strong over-representation of genes involved in transcription , in-keeping with those known to undergo translation on demand in prokaryotes [18] . When we take these results together , it is feasible that RTS cluster genes are subject to a process similar to NGD , a mechanism that limits the level of protein production . This potential is indicated by the fact that some clusters are skewed toward the 5′ region [see 16] , a feature used to minimize the cost of employing NGD . One alternative theory explaining the clustering of codons corresponding to rare tRNAs is one we refer to as the “recruitment delay minimization” hypothesis . The theory posits that if one rare codon is used then subsequent synonymous codons will be biased towards this codon . The reasoning is that once the tRNA has been recruited to the mRNA it will be in position to translate the proximal cognate codons without imposing a recruitment delay , and thus any impact on translation rate is minimized . As this mechanism acts to maximize the translation rate of a restricted sequence , we would expect that this bias would only be necessary in a handful of cases . If a reduction in the translation rate is costly to fitness , then selection should favor the use of synonymous codons with abundant tRNAs . The only instance where the clustering of the same slow codon to minimize recruitment delay would occur is if all the synonymous codons for an amino acid are rare . Our results are independent of this phenomenon as those RTS clusters due to amino acids with only low scoring codons were purged from our analyses . In addition , this selective force should be restricted to highly transcribed genes; a feature not enriched in our RTS cluster genes . For the most significant RTS clusters ( Table S1 ) , site directed mutagenesis studies , which modify the nucleotide sequence to maximize translation rate , may reveal in which capacity these RTS clusters are necessary .
The degeneracy of the genetic code means that many amino acids are encoded by not one , but a range of codons . In bacteria and yeast , it is known that the choice of codons used can be beneficial ( or detrimental ) to the gene function . As humans have a relatively small effective population size , and the efficiency of selection to purge mutations of mild deleterious effect decreases as population size decreases , it has been assumed that the benefit/cost of codons is not large enough to have a measurable effect on codon choice . Here we show that codons with the lowest amount of tRNA are clustered in gene sequences more often than anticipated . The genes containing these clusters were found to have specific functions in gene expression . Comparisons to known bacterial and yeast processes suggest a translation level mechanism for the regulation of protein expression in human genes . Thus , our investigation highlights the potential for the presence of a novel regulatory mechanism in human genes .
[ "Abstract", "Introduction", "Results", "Discussion" ]
[ "genetics", "and", "genomics/genomics", "genetics", "and", "genomics/comparative", "genomics", "evolutionary", "biology/evolutionary", "and", "comparative", "genetics", "evolutionary", "biology/human", "evolution", "genetics", "and", "genomics/gene", "expression", "evolutionary", "biology/genomics", "evolutionary", "biology/bioinformatics", "computational", "biology/genomics", "computational", "biology", "genetics", "and", "genomics/bioinformatics" ]
2009
Clustering of Codons with Rare Cognate tRNAs in Human Genes Suggests an Extra Level of Expression Regulation
Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states . The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse , and to compare the biomarkers extracted from different biofluids ( plasma , stool , and urine ) in terms of characterizing acute and chronic stages of this intestinal fluke infection . Twelve female NMRI mice were infected with 30 E . caproni metacercariae each . Plasma , stool , and urine samples were collected at 7 time points up to day 33 post-infection . Samples were also obtained from non-infected control mice at the same time points and measured using 1H nuclear magnetic resonance ( NMR ) spectroscopy . Spectral data were subjected to multivariate statistical analyses . In plasma and urine , an altered metabolic profile was already evident 1 day post-infection , characterized by reduced levels of plasma choline , acetate , formate , and lactate , coupled with increased levels of plasma glucose , and relatively lower concentrations of urinary creatine . The main changes in the urine metabolic profile started at day 8 post-infection , characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection . The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery . In the case of E . caproni , a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection . For practical purposes , however , future diagnosis might aim at a single biofluid , in which case urine would be chosen for further investigation , based on quantity of biomarkers , ease of sampling , and the degree of differentiation from the non-infected control group . An estimated 40 million individuals are infected with food-borne trematodes and , in many parts of the world , the diseases caused by these infections are emerging [1] . Yet , food-borne trematodiases are so-called neglected tropical diseases [2] . An infection with food-borne trematodes is acquired by the consumption of the larval stage of the parasite , present in aquatic food products ( e . g . , freshwater fish , crustacean , and water plants ) . Adult flukes reside either in the intestine ( e . g . , Echinostoma spp . ) , the lung ( e . g . , Paragonimus spp . ) , or the liver ( e . g . , Clonorchis sinensis , Fasciola spp . , Opisthorchis spp . ) and can lead to various forms of pathology [2] , [3] . A light infection with the intestinal fluke Echinostoma spp . in humans causes no marked deviation from the healthy state in the majority of cases , whereas the clinical symptoms due to a heavy infection include abdominal pain , violent diarrhea , anorexia , easy fatigue , and changes in the intestinal architecture , such as intestinal erosions , damage of intestinal mucosa , and catarrhal inflammation [4] . Histopathological investigations in mice and humans infected with Echinostoma spp . have revealed atrophied , fused and eroded villi , and a crypt hyperplasia in both lightly and heavily infected subjects [5]–[7] . At present , the most widely used diagnosis for infections with Echinostoma spp . and other food-borne trematodes , is by means of microscopic examination of stool samples for the presence of parasite eggs . However , light infection intensities , particularly at the onset of disease are often missed by this diagnostic approach . In addition , the detection of echinostome eggs in stool samples varies greatly due to species-dependent differences in egg laying capacity . Other means for diagnosis of food-borne trematode infections include immunological and molecular tests , such as the enzyme-linked immunosorbent assay ( ELISA ) [8] or polymerase chain reaction ( PCR ) [9] , which depend on specificity of antigens and primers , respectively . In the current study we applied a combination of 1H nuclear magnetic resonance ( NMR ) spectroscopy and multivariate statistical analysis to identify candidate biomarkers of an E . caproni infection and disease states in the mouse , by metabolic profiling of blood plasma , stool , and urine samples . E . caproni is a suitable trematode model that has been widely and effectively used in the laboratory for drug screening , and to deepen our understanding of the immunology and pathology of echinostomes and other food-borne trematodes in the vertebrate host [10]–[12] . NMR spectroscopy delivers a snapshot of the metabolite composition of biofluids , tissues and even bone , and has found a large array of applications in biology and medicine , such as the detection and differentiation of coronary heart disease [13] , and biomarker identification in schizophrenia patients [14] . The systemic metabolic profile of a biological sample is of special interest , because it can be characteristic of the entire organism , and hence finds increasing application in systems biology [15] . The use of multivariate statistical methods to analyze and interpret complex spectral datasets makes it possible to deal with large sample data banks , and to detect differences between physiologically or pathologically distinct states . Candidate biomarkers can be identified from these models , taking into consideration intra-group variations , sample preparation methods , and spectral data acquisition . Thus far , we have characterized the global metabolic responses to several parasitic infections in rodents , namely ( i ) Schistosoma mansoni in the mouse [16] , ( ii ) Schistosoma japonicum in the hamster [17] , ( iii ) Trichinella spiralis in the mouse [18] , ( iv ) Trypanosoma brucei brucei in the mouse [19] , and ( v ) Plasmodium berghei in the mouse [56] mainly based on the urine and/or blood plasma metabolite profiles . Here we extend these initial host-parasite models to consider the relative merit of using biomarkers derived from a combined biological sample profile , and apply a metabolic profiling strategy for the first time to a food-borne trematode . Our experiments were carried out in accordance with Swiss cantonal and national regulations on animal welfare ( permission no . 2081 ) . Female NMRI mice ( n = 24 ) were purchased from RCC ( Itingen , Switzerland ) , and housed in groups of 4 in macrolon cages under environmentally-controlled conditions ( temperature: ∼25°C; humidity: ∼70%; light-dark cycle: 12–12 h ) . Mice had free access to commercially available rodent food from Nafag ( Gossau , Switzerland ) and community tap water supply . Mice were 5 to 6-week-old at the onset of the experiments and had an average weight of 25 . 5 g ( standard deviation ( SD ) = 0 . 9 g ) . Half of the mice remained uninfected throughout the study and served as controls . The other 12 mice were orally infected with 30 E . caproni metacercariae each ( provided by B . Fried; Lafayette College , Easton , PA , United States of America ) [20] on designated study day 0 , which took place 1 week after arrival of animals to provide sufficient acclimatization time , and hence minimize stress-related impact on the metabolic profiles . Upon dissection of mice at the end of the experiment , however it was found that no infection had been established in 4 animals . Therefore these 4 mice were excluded from any further analysis . Blood plasma , stool and urine samples were collected over a 33-day time course at 7 distinct sampling points ( days 1 , 5 , 8 , 12 , 19 , 26 , and 33 post-infection ) , representative of different stages in the life of the E . caproni fluke , including acute and chronic infection stages . Collection was carried out between 08:00 and 10:00 hours in order to avoid potential variation of metabolite concentrations due to diurnal fluctuations . Stool and urine samples were collected into Petri dishes by gently rubbing the abdomen of the mice , and were immediately transferred into separate Eppendorf tubes and kept at −40°C . Blood samples ( 40–50 μl ) were collected from the tail tip of each mouse into haematocrit tubes with sodium [Na] heparin-coat . Tubes were placed in a centrifuge ( model 1–15 , Sigma; Osterode am Harz , Germany ) operated at 4 , 000 g for 4 min in order to separate plasma from red blood cells . The packed cell volume ( PCV ) , i . e . , length of red blood cells column in the microcapillary versus total length of blood sample column , was determined and expressed as percentage . Subsequently , the plasma fraction ( ∼20 μl ) was transferred into a separate Eppendorf tube and kept at −40°C . Animals were weighed at each sampling point , using a Mettler balance ( model K7T; Greifensee , Switzerland ) . Mice were killed 36 days post-infection , using CO2 . The small intestine was removed , and adult worms recovered from the ileum and jejunum and counted . Biological samples and an E . caproni specimen were forwarded to Imperial College London ( United Kingdom ) on dry ice and stored at −40°C prior to processing for 1H NMR spectroscopic data acquisition . Urine samples were prepared with a phosphate buffer ( pH 7 . 4 ) containing 50% D2O ( Goss Scientific Instruments; Chelmsford , United Kingdom ) as a field frequency lock and 0 . 01% sodium 3- ( trimethylsilyl ) [2 , 2 , 3 , 3-2H4] propionate ( TSP ) ( Cambridge Isotope Laboratories Inc . ; Andover , MA , United States of America ) , as a chemical shift reference ( δ 0 . 0 ) . An aliquot of 25 μl of urine was added to 25 μl phosphate buffer . Plasma samples were prepared by adding 30 μl of 0 . 9% saline made up in 50% D2O into the Eppendorf tubes containing ∼20 μl of plasma . Because of the limited volumes of urine and plasma , samples were transferred into 1 . 7 mm diameter micro NMR-tubes ( CortecNet; Paris , France ) using a micro-syringe . Stool samples were prepared with the same buffer as for urine but using 90% D2O to reduce the water content . Two pellets of stool were mashed with 700 μl buffer and sonicated for 30 min to inactivate gut bacteria and achieve biochemical stability in the sample . The samples were then centrifuged at 10 , 000 g for 2 min , and 550–600 μl of the supernatant was transferred into a new Eppendorf tube and stored at −40°C . Shortly before data acquisition , the stool supernatant was defrosted , centrifuged and transferred into NMR tubes of 5 mm outer diameter . A tissue extraction was performed on the E . caproni specimen for 1H NMR spectroscopic analysis . The adult E . caproni fluke was mashed in 1 ml of chloroform with a glass mortar and pestle . A total of 1 ml of methanol and 1 ml of water were added , and this mixture was transferred into a glass tube . Another 0 . 5 ml of each liquid was used to rinse the mortar and transferred into the same glass tube . The mixture was centrifuged at 2 , 500 g for 30 min . The aqueous and the chloroform phases were transferred into a new glass tube each , chloroform was evaporated over night and the aqueous phase was lyophilized . Prior to 1H NMR data acquisition , the powder obtained from the aqueous phase was resolved in 550 μl phosphate buffer ( 90% D2O ) , whereas the dry mass of the chloroform fraction was dissolved in deuterated chloroform ( CDCl3 ) . 1H NMR spectra from plasma , stool , and urine samples , and the E . caproni extract were recorded on a Bruker DRX 600 NMR spectrometer , operating at 600 . 13 MHz for proton frequency ( Bruker; Rheinstetten , Germany ) . A Bruker 5 mm triple resonance probe with inverse detection was used , employing a standard NMR 1-dimensional ( 1D ) experiment with pulse sequence [recycle delay ( RD ) -90°-t1-90°-tm-90°-ACQ] , setting t1 to 3 μs , and using a mixing time ( tm ) of 150 ms . Water suppression was achieved with irradiation of the water peak during the RD set to 2 s and mixing time . The 90° pulse length was adjusted to ∼10 μs . A total of 256 transients were collected into ∼32 , 000 data points for each spectrum with a spectral width of 20 ppm . For plasma , two additional pulse programs were applied , namely Carr-Purcell-Meiboom-Gill ( CPMG ) , and diffusion edited spectroscopy [21] to focus on the low and high molecular weight components of the plasma profile , respectively . All free induction decays ( FIDs ) were multiplied by an exponential function equivalent to a 0 . 3 Hz line-broadening factor prior to Fourier transformation . Assignments of the spectral peaks were made from literature values [22]–[25] and confirmed via statistical total correlation spectroscopy ( STOCSY ) in MATLAB [26] and via standard 2-dimensional ( 2D ) NMR experiments conducted on selected samples , including correlation spectroscopy ( COSY ) , total correlation spectroscopy ( TOCSY ) , and J-resolved NMR spectra [27] , [28] . Data processing was as follows . First , spectra were corrected for phase and baseline distortions with an in-house developed MATLAB script . Second , the region containing the water/urea resonances ( i . e . , δ 4 . 2–6 . 3 in urine , δ 4 . 4–5 . 2 in plasma , and δ 4 . 7–5 . 5 in stool extracts ) was excluded . Third , the spectra were normalized over the total sum of the remaining spectral area . Analysis of the spectral data was performed with principal component analysis ( PCA ) [29] , projection to latent structure discriminant analysis ( PLS-DA ) and orthogonal ( O ) -PLS-DA [30] . PCA was used to explore any intrinsic similarity between samples . PCA models cannot be over-fitted since no prior information on infection status is included in the model . PLS-DA was then used to apply knowledge of infection status to optimize separation of classes and recovery of candidate biomarkers [30] . O-PLS-DA includes an orthogonal data filter in the PLS-DA and was used to further improve the extraction of infection-related biomarkers by removing the influence of systematic variation not related to infection status . The weight of contribution of the peaks is indicated by the color scale , whereby red symbolizes relatively high correlation with infection and blue indicates relatively low or no correlation . The metabolites which contributed the greatest weight to the O-PLS-DA coefficient plot were identified ( Tables 1–3 ) . The NMR spectral data were used as the X-matrix and class information ( infected or non-infected control ) as the Y-matrix to build the O-PLS-DA models . A model consisting of one PLS component and one orthogonal component was generated using 7-fold cross validation . Finally , in order to more accurately profile the temporal behavior of the discriminatory metabolites characterizing an E . caproni infection , computational integration was performed on selected resonances . Resonances from several of the metabolites in each sample , which showed infection-dependent variations , were integrated using an automated curve fitting program . The relative concentration in relation to the total spectral integral , subsequent to removal of the water resonance , was determined . This was performed in MATLAB using a previously published method [31] , and further modified by a colleague ( K . Veselkov; Imperial College London , UK ) . The p-values for the metabolites were assessed using a non-parametric 1-way analysis of variance ( Mann-Whitney U ) test in MATLAB . E . caproni-infected mice showed no visible sign of ill-health over the course of the experiment . The mean weight and mean PCV of E . caproni-infected ( n = 8 ) and non-infected control mice ( n = 12 ) did not differ at any of the time points investigated . The PCV values maintained a constant level throughout the experiment ( 49 . 6–55 . 1% ) . Upon dissection and worm count , an infection was confirmed in 8 out of the 12 mice ( average worm count 26 . 5 , SD = 12 . 0 , range: 10–44 worms ) . The 4 animals with no established infection were excluded from further analyses . Prior to assessing the metabolic effects of an E . caproni infection , the 1H NMR spectra of plasma , stool , and urine samples obtained from non-infected mice were characterized and found to be inherently different in composition . All three types of biofluids contained lactate , alanine , glucose , and acetate . Unique to the urine metabolic profile was the presence of hippurate , indoxylsulfate , urocanate , taurine , trimethylamine-N-oxide ( TMAO ) , 2-oxoglutarate , ureidopropanoate , and 2-ketoisocaproate , amongst others ( Figure 1A , Figure 2A and Table 1 ) . The plasma spectral profiles were characterized by the predominance of various lipids and lipoprotein fractions , along with resonances from creatine , and several amino and organic acids ( Figure 1B , Figure 2B and Table 2 ) . Apart from the standard 1D acquisition , applied on all biofluids , a CPMG and diffusion edited pulse sequence was used in plasma profiling , to represent low and high molecular weight metabolites , respectively . Characteristic metabolic features of the stool extracts were bile acids and short chain fatty acids ( SCFAs ) , such as butyrate , and propionate . In addition , other amino acids , such as tryptophan , lysine , arginine , and glutamine were more visible in stool spectra , compared to urine and plasma ( Figure 1C , Figure 2C and Table 3 ) . In order to establish whether excretory products of the parasite itself were likely to contribute to any of the biofluids analyzed , a standard 1D spectrum of an adult E . caproni was acquired . The spectrum of the parasite differed from the biofluids obtained from the mouse host in content of homocarnosine , histidinol , uridine , pipecolate , and betaine ( Figure 1D , Figure 2D ) , although betaine has been observed in 1H NMR spectra of rodent urine in previous studies [32] . Tables 1–4 summarize key metabolites found in urine , plasma , and stool extracts of mice , and in the E . caproni homogenate , respectively . In both PCA and PLS-DA scores plots of the urinary metabolite profiles , a clear separation of E . caproni-infected and non-infected control mice was already visible 1 day post-infection . This separation was maintained in all later time points except day 5 . Metabolic trajectories were constructed for each type of biofluid by taking the mean position in the principal component ( PC ) scores plot for each group of mice ( E . caproni-infected and non-infected controls ) separately , and connecting the coordinates chronologically to establish any systematic change in metabolic composition over the time course of the experiment . The control group showed no significant movement over the study duration ( data not shown ) , whereas in the infected group , day 19 was significantly separated from all other days post-infection , and the whole time course of infection showed a shift from the upper left to the lower right quadrant ( Figure 3A ) , whereby days 1 and 5 post-infection differed significantly from the sampling end point ( day 33 ) . The plasma spectra of E . caproni-infected mice showed marked differences at days 1 , 12 , 26 , and 33 post-infection , with the best discriminatory model at day 12 post-infection ( goodness of prediction ( Q2 ) according to PCA = 0 . 97; Q2Y ( PLS-DA ) = 0 . 89 ) . Comparing the 3 different pulse programs applied , plasma time trajectories , showed similar behavior . The control trajectories were generally clustered , indicating stability of the metabolite composition over the study period . However , the standard 1D trajectory showed a slight difference between early and late time points ( e . g . , day 1 was separated in space from days 19 to 33 ) . In contrast , for the E . caproni-infected animals , there was a significant metabolic movement from early ( day 1 ) to intermediate time points post-infection ( days 5 and 12 ) in the first component and finally to late time points ( days 26 and 33 ) in the third component ( Figure 3B ) . This movement pattern was consistent across the datasets acquired by all three pulse programs . With regard to the 1H NMR spectra obtained from stool samples , a clear separation was found at day 5 post-infection in both the PCA and PLS-DA scores plot between E . caproni-infected and non-infected control mice , with maximum model fit for the PLS-DA model at day 26 post-infection ( Q2 = 0 . 79 ) . At the final time point ( day 33 ) , the two groups were metabolically similar; there was no separation between infected and non-infected mice using PCA , and the PLS-DA model revealed a lower , but still significant Q2 value than all previous time points . By comparing the time trajectories of the non-infected control with the E . caproni-infected group of mice , the controls were more tightly clustered , but showed a significant movement from day 8 post-infection onwards along PC1 . In the 2D time trajectory plot of the E . caproni-infected mice , all time points were tightly clustered with the exception of days 8 and 12 post-infection , which comprised a separate cluster ( Figure 3C ) . Introducing an additional PC brought about clear differentiation of the late time points ( days 19 , 26 , and 33 ) from day 1 post-infection caused by more subtle systematic variation in metabolic levels . O-PLS-DA was used to extract information on specific metabolic changes induced by an E . caproni infection over the duration of the study . Changes in urinary , plasma and fecal metabolites are presented in Figures 4–6 for selected time points and the complete set are summarized in Figure 7 . Amongst the most significantly changed urinary metabolites were hippurate ( decreased at day 33 ) , 2-ketoisocaproate ( decreased from day 8 onwards ) , trimethylamine ( TMA; increased at days 8 , 12 , 19 , and 33 ) , taurine ( decreased at days 8 , 12 , and 19 ) , p-cresol glucuronide ( increased at days 8 , 12 , 19 , and 26 ) , mannitol ( increased from day 5 onwards ) , TMAO ( increased at days 8 , and 12 ) , phenylacetylglycine ( increased from day 12 onwards ) , acetate ( decreased at days 8 , and 19 ) and creatine ( decreased at days 1 , 5 , 8 , and 12 ) . Plasma from infected mice showed changes in the relative concentration of acetate ( increased at all time points except day 5 ) , creatine ( decreased from day 8 onwards ) , lipids ( increased from day 8 onwards ) , formate ( decreased at days 1 , 8 , 12 , and 19 , but increased at day 33 ) , lactate ( decreased at days 1 , 8 , 12 , 19 , and 26 ) , glucose ( increased at days 1 , and 33 , but decreased at days 12 , 19 , and 26 ) , glycerophosphorylcholine ( GPC; decreased at days 12 , 26 , and 33 ) , choline ( decreased at days 1 , 12 , 26 , and 33 ) and branched chain amino acids ( BCAAs; decreased at days 12 , 26 , and 33 ) . The changes in stool samples from infected animals included the BCAAs ( increased at days 8 , and 26 ) , uracil ( increased at day 8 ) , butyrate ( decreased at days 12 , 19 , and 26 ) , propionate ( decreased at days 12 , 19 , and 26 ) and 5-aminovalerate ( increased from day 5 onwards ) . Figure 8 shows the relative concentration of some of these metabolites both for control ( blue ) and infected mice ( colored according to biofluid ) . The error bars signify 2 SDs of the mean . According to this 3×3 diagram , the selected plasma and urine metabolites showed a more robust pattern of group separation over time when compared to fecal water extracts . Whereas some overlap was observed in the scores plot relating to the fecal water samples , there was a tendency toward increasing discrimination of urinary metabolites with time over the course of an E . caproni infection , whereas the discrimination became smaller toward the end of the experiment in the selected plasma metabolites . The time trajectories allow the influence of growth and maturation of either host or parasite to be considered . Since very few of the metabolites observed in the E . caproni fluke appeared in any biofluid , infection-related changes are unlikely to correlate with maturation of the parasite . Additionally , since the urinary time trajectories were very different , comparing the control with the infected group , whereas the control trajectory did not show any significant movement over time; this would indicate that the maturation of the host organism did not markedly influence the metabolic profile over the 33-day time course . Hence , the systemic movement over time observed in the infected group is most likely to be related to the establishment and progression of the E . caproni infection . In stool and plasma , the time trajectories of the infected animals demonstrated a markedly greater magnitude from the baseline position than the non-infected animals . The greatest differentiation between E . caproni-infected mice and non-infected control animals was found in the PC scores plots based on the urine spectral profiles . The smallest differentiation was observed in the stool . From the scale of the PC scores plot axes the trajectory of the infected group occupied a 1 . 5 and 50 times larger space for stool and plasma , respectively than the non-infected group , whereas in urine , the control trajectory occupied a 106 times bigger space , compared to the trajectory of infection . The magnitude of infection-induced metabolic disturbance in the urine profile again clearly points to the greater suitability of urine as a diagnostic biological matrix . The considerable increase in concentration of lipids in the plasma , e . g . , fatty acids , triaglycerols , and lipoproteins , reflects the action of the parasite in the hosts gut . In mice harboring a 2-week-old E . caproni-infection , an increased breakdown of membrane lipids in the host intestinal tissue has been observed [35] , which is consistent with the present findings of a maximum lipid increase on day 12 post-infection [36] . The excretory products of E . caproni in the intestinal mucosa are primarily free sterols , triaglycerols , and free fatty acids [37] , but it is unlikely that the amounts excreted by the parasite make a substantial contribution to the host metabolic profile , given that the total parasite mass to host weight ration is ∼1:300 . Whilst the simple diffusion of lipid micelles into mucosal cells seems unaffected by the parasite , the Na+-dependent active transport of amino acids could be impaired as the increase of the BCAAs in stool as the subsequent decrease in plasma supports . Depletion of the carrier molecules at the brush border of the mucosal cells , or a change of the electrochemical gradient for Na+ might explain the selective impact on trans-luminal gut transport [38] . The observed decrease of leucine in plasma , in turn , might induce the significant reduction in levels of 2-ketoisocaproate in urine , which is a transamination product of the former [39] . Taurine is mainly conjugated with cholic acid and chenodeoxycholic acid in the liver to form primary bile salts , and is excreted via the urine after deconjugation from the bile salt or it leads into the sulphur- or pyruvate metabolism . Once the taurine conjugated bile salt has transformed the lipids into a micellar form , which is necessary to cross the intestinal wall , taurine is deconjugated by gut bacterial species and reabsorbed into the liver via blood circulation [40] . The decreased levels of excreted taurine in the urine of the infected mice may result from the higher demand for increased lipid digestion , resulting from the action of E . caproni in the gut . The changes in hippurate , phenylacetylglycine , p-cresol-glucuronide , and TMA in urine , and 5-aminovalerate , and the SCFA levels in stool , are associated with a change in gut microbiotal presence or activity , as all of these metabolites undergo modification via gut microbial species before excretion . For instance , 5-aminovalerate is formed by several different Clostridium species which utilize ornithine and proline as substrates , but to our knowledge , only C . aminovalericum degrades 5-aminovalerate further to form mainly propionate and acetate [41]–[43] . This may imply that the presence of E . caproni in the gut disturbs the microbial balance resulting in depleted or inactivated C . aminovalericum . The formation of p-cresol is likewise known to be performed by a Clostridium subspecies ( i . e . , C . difficile and C . scatologenes ) [44] , [45] , with the bacterium-specific enzyme p-hydroxyphenylacetate . It is then conceivable that p-cresol is taken up by the bloodstream , bound to serum proteins and glucuronidated in the kidney prior to excretion [46] . Increased excretion of p-cresol-glucuronide might be coupled with a higher activity or higher presence of this bacterial strain as the kidney function does not seem to be impaired in infected animals . PCR analyses on several different Clostridium sub-strains are ongoing and will be discussed in forthcoming publications . The decrease of the SCFAs in stool may also be indicative of an unbalanced microbiota , as dietary carbohydrates ( e . g . , starches and fibres ) are fermented by colonic bacteria to mainly acetate , propionate , and butyrate . Whilst butyrate serves as main energy source for colonocytes , acetate and propionate pass through the intestinal wall and move via peripheral blood to the liver where they have antagonistic functions on the cholesterol synthesis . Whilst the former increases cholesterol synthesis , the latter was shown to act as an inhibitor . The uptake from colon by the blood system is four times higher in the case of acetate , than propionate , which is a possible explanation for depletion of the SCFA , also reflected by the observed decrease in levels of acetate in both urine and plasma [47] , [48] . The increased concentration of TMA and phenylacetylglycine , and the decrease of hippurate in urine , observed at the later time points of our experiment , are concomitant phenomena of the changed gut microbiota [49] , [50] . Trimethylammonium compounds like choline and carnitine , which are ingested in the normal diet , are degraded by intestinal bacteria to TMA , and then oxidized in the liver to TMAO in a second step [51] , [52] . A microbial shift toward choline degrading bacteria might explain the choline/GPC depletion in plasma and the subsequent increase of TMAO in urine . An infection with E . caproni induces changes in the concentration of a range of metabolites in urine , plasma , and stool . To be useful as a ‘real’ biomarker , the metabolic candidate must be reproducible , robust , specific and , ideally , easy to measure [53] . From the current analyses an anomalous increase in urinary mannitol was noted in infected animals . Mannitol is likely to derive from the diet , since it is not synthesized by vertebrates . However , the higher amounts of urinary mannitol in E . caproni-infected mice , may reflect the higher intestinal permeability , compared to the control group [54] . To assess the specificity of the biomarkers identified for potential diagnosis of infection , the obtained E . caproni fingerprint was compared to altered metabolite patterns , associated with other parasite-rodent models [16]–[18] . Interestingly , E . caproni seems to alter the gut microbiota in a similar way to the biologically-related blood flukes , i . e . , S . mansoni [16] , and S . japonicum [17] . Hippurate , phenylacetylglycine , and TMA are modified by several gut microbial species before excretion in urine . In the 3 disease models , hippurate was found to decrease significantly , whereas phenylacetylglycine , p-cresol-glucuronide and TMA showed increased levels in infections with all 3 parasites , which suggests a common trematode-inherent influence on gut microbial composition . The change in 2-ketoisocaproate in urine was unique to the infection with E . caproni and 5-aminovalerate in stool may also deliver an E . caproni-specific marker but , at the time being , cannot be compared to other disease models , as the metabonomic assessment of stool was applied only in the present parasite-rodent model . The metabolic effect of a nematode infection ( T . spiralis ) in NIH Swiss mice has also been reported by Martin and colleagues [18] . T . spiralis has a similar initial mechanism of pathogenicity and also induces a state of inflammation of the gut before it migrates from the intestine to muscle tissue and induces hypercontractility [55] . While comparison between the study conducted by Martin et al . [18] and the current study revealed a number of biomarkers , which were the same in both models , the directionality of these metabolites was different . For example , a decrease in choline and creatine concentrations was observed in E . caproni-infected mice , whereas the same metabolites were reported to be increased in T . spiralis-infected mice compared to non-infected controls . Furthermore , the lipids ( e . g . , triaglycerides , saturated and unsaturated fatty acids ) which undergo a marked increase in E . caproni-infected animals , showed a significant decrease in the mice infected with T . spiralis . Future studies evaluating additional laboratory host-parasite models , and applying complementary metabolic profiling methods , such as ultra performance liquid chromatography ( UPLC ) , in combination with mass spectrometry ( MS ) , will help to confirm the specificity of the metabolic perturbations associated with an E . caproni infection . In conclusion , we have shown that metabolic profiling of plasma , urine , and stool delivers a comprehensive fingerprint of an E . caproni infection , composed of general as well as highly specific biomarkers ( e . g . , 2-ketoisocaproate and 5-aminovalerate ) . Keeping in mind the long-term objective of developing novel diagnostic assays for trematode-borne diseases , one would emphasize the value of further development , particularly based on the urine profiles .
Consumption of raw fish and other freshwater products can lead to unpleasant worm infections . Indeed , such worm infections are of growing public health and veterinary concern , but they are often neglected , partially explained by the difficulty of accurate diagnosis . In the present study we infected 12 mice with an intestinal worm ( i . e . , Echinostoma caproni ) and collected blood , stool , and urine samples 7 times between 1 and 33 days after the infection . At the same time points , blood , stool , and urine were also sampled from 12 uninfected mice . These biofluid samples were examined with a spectrometer and data were analyzed with a multivariate approach . We observed important differences between the infected and the uninfected control animals . For example , we found an increased level of branched chain amino acids in the stool of infected mice and subsequent depletion in blood plasma . Additionally , we observed changes related to a disturbed intestinal bacterial composition , particularly in urine and stool . The combination of results from the three types of biofluids gave the most comprehensive characterization of an E . caproni infection in the mouse . Urine would be the biofluid of choice for diagnosis of an infection because the ease of sample collection and the high number and extent of changed metabolites .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[ "biochemistry", "infectious", "diseases" ]
2008
Metabolic Profiling of an Echinostoma caproni Infection in the Mouse for Biomarker Discovery
The replication of many RNA viruses involves the translation of polyproteins , whose processing by endopeptidases is a critical step for the release of functional subunits . P1 is the first protease encoded in plant potyvirus genomes; once activated by an as-yet-unknown host factor , it acts in cis on its own C-terminal end , hydrolyzing the P1-HCPro junction . Earlier research suggests that P1 cooperates with HCPro to inhibit host RNA silencing defenses . Using Plum pox virus as a model , we show that although P1 does not have a major direct role in RNA silencing suppression , it can indeed modulate HCPro function by its self-cleavage activity . To study P1 protease regulation , we used bioinformatic analysis and in vitro activity experiments to map the core C-terminal catalytic domain . We present evidence that the hypervariable region that precedes the protease domain is predicted as intrinsically disordered , and that it behaves as a negative regulator of P1 proteolytic activity in in vitro cleavage assays . In viral infections , removal of the P1 protease antagonistic regulator is associated with greater symptom severity , induction of salicylate-dependent pathogenesis-related proteins , and reduced viral loads . We suggest that fine modulation of a viral protease activity has evolved to keep viral amplification below host-detrimental levels , and thus to maintain higher long-term replicative capacity . Viruses are obligate parasite pathogens that hijack host factors to assure their own survival and propagation . Due to the limited coding capacity of their genome , viruses undertake distinct translational strategies [1]; one of most widely employed by RNA viruses involves polyprotein synthesis [2] . A full-length polyprotein is theoretically derived from a single translational event , compromising the timely expression of the individual viral cistrons . To overcome this possible drawback and successfully regulate replication , assembly and spreading stages , various post-translational mechanisms have evolved to modulate the spatial-temporal availability of functional viral subunits . For instance , it is not uncommon that the same polyprotein is hydrolyzed by several endopeptidases; cleavage kinetics are thus linked to enzyme processivity and , in trans-acting proteases , to the different affinity with the specific cleavage sites [3] , [4] . Activation of viral proteases might depend on the availability of defined cell- or pathogen-encoded cofactors [5]–[7] and structural rearrangements that modulate substrate accessibility , as shown for the hepatitis C virus NS3 protease domain [8] . Zymogen activation and allostery are key regulatory mechanisms of trypsin-like proteases [9] , a group of enzymes that is widespread in positive strand RNA viruses [10] and that includes P1 proteins of potyviruses [11] . Members of the genus Potyvirus ( family Potyviridae ) belong to the picorna-like supergroup and represent one of the largest groups of plant-infecting RNA viruses [12] , [13] . Their single-stranded RNA genome is ≈10 kb in size and encodes a large polyprotein comprising ( from N- to C-terminus ) P1 , HCPro , P3 , 6K1 , CI , 6K2 , VPg , NIa-Pro , Nlb , and the coat protein ( CP ) . An additional protein , P3N-PIPO , is originated by a frameshift in the P3 cistron [14] , [15] . The cysteine protease NIa-Pro processes the C-terminal part of the polyprotein by seven cleavage events , while P1 and HCPro are responsible for their own release by a cis cleavage at their respective C-termini [16]–[18] . Once released , the mature P1 and HCPro C-terminal extremities are thought to be trapped in the active cleft , leading to autoinhibition of trans cleavage activity [18] , [19] . Located at the beginning of the polyprotein , P1 was the last potyviral endopeptidase identified; inactivating mutations of its catalytic domain preclude virus viability [20] , making P1 an attractive target for the development of antiviral tools . In contrast to the two other genome-encoded proteases , P1 relies on a still unidentified host factor for its activation [18] . Computational analysis of P1 potyviral proteins showed its great variability both in length and in amino acid sequence , and its diversification in potyviral species was thus associated with host specialization [21] . Although P1 involvement in the definition of virus host range was highlighted [22] , [23] , its specific contribution to potyviral infection is still unclear . Many functions were attributed to P1 , such as cell-to-cell movement , systemic spread , and viral genome replication enhancement [reviewed in 24]; P1 was later shown to strengthen the RNA silencing suppressor activity of HCPro [25]–[28] . Here we used Plum pox virus ( PPV ) as a model system to study potyviral P1 . Our results indicate that P1 and its protease domain have a positive role in potyvirus infection , independent of silencing suppression . Moreover , the in vitro and in planta data presented here suggest that host-dependent regulation of P1 self-cleavage activity has evolved to modulate the efficiency of viral infection and escape plant defense responses . Genetic rescue of a Turnip mosaic potyvirus ( TuMV ) defective in RNA silencing suppression activity was reported in the Arabidopsis thaliana triple mutant line dcl2-1 dcl3-1 dcl4-2 ( dcl2/3/4 ) [29] . A PPV isolate adapted to Nicotiana clevelandii and able to infect herbaceous hosts [30] , as well as its infectious cDNA clone encoding a green fluorescent protein ( GFP ) reporter gene , were described [31] . To study the P1 contribution in silencing suppression , we generated a viral clone that lacks the entire P1 sequence ( ΔP1 , Figure 1A ) , which we used to challenge Arabidopsis mutant plants with defective antiviral silencing pathways . At 15 days post-agro-inoculation ( dpi ) , ΔP1-infected Col-0 and dcl2/3/4 plants were almost symptomless , whereas PPV-infected Col-0 plants showed leaf chlorosis , which was stronger in the dcl2/3/4 mutant line ( Figure 1B ) . The presence of ΔP1 and wild-type PPV in systemic leaves was evidenced by GFP fluorescence detection ( Figure 1B ) . Anti-PPV CP western blot analysis of systemically infected leaves showed that , in both host genotypes , viral accumulation was significantly higher in wild-type PPV than in ΔP1-infected plants ( Figure 1C and D ) . The results confirmed that lack of P1 sequence did not compromise virus ability to replicate or to move systemically , as also shown for another potyvirus , Tobacco etch virus ( TEV ) [32] . Although ΔP1 appears to replicate better in the silencing deficient plants than in wild-type Col-0 , the dcl2/3/4 line did not restore the ΔP1 phenotype and viral accumulation to wild-type PPV levels ( Figure 1B and D ) . Based on these results , the main role of P1 in viral amplification appears unrelated to RNA silencing suppression . To further analyze possible P1 functions , we coupled multiple sequence alignment and structural predictors for bioinformatic analysis of its sequence . Intrinsic protein disorder was estimated using DISOPRED2 [33] and MetaDisorderMD2 [34] . From the in silico analysis of P1 proteins from different potyviral species groups ( Table S1 , in Text S1 ) , we identified FxxLE as a conserved motif in the P1 N-terminal region ( Figure 2 ) , in conjunction with the reported IxFG and ISI motifs [21] . The relatively well-conserved C-terminal regions of the proteins , which correspond to the protease domain ( defined below ) and include the VELI motif , are predicted mainly as structured . The residues from N-terminal sequence patches with least conservation are generally predicted to be intrinsically unstructured ( Figure 2 ) , suggesting that final protein conformation is the main evolutionary target , rather than maintenance of the primary sequence , as proposed [35] . The disorder predictions were further supported by P1 sequence analysis of Scallion mosaic virus and the monocotyledon-infecting Sugarcane mosaic virus group ( Figure S1 ) , which comprise the smallest known P1 sequences and are suggested to be at the base of the potyviral evolutionary tree [13] . To study the relevance of P1 motifs in protease activity , we mutated selected PPV P1 conserved amino acids to alanine ( Figure 3A ) . The viral cDNA constructs were transcribed and in vitro-translated using the wheat germ extract ( WGE ) system . Replacement of catalytic S259 ( S ) and P2 and P1 cleavage site residues HY-307 , 308 ( HY ) with alanine impaired P1 protease self-cleavage , precluding release of the mature 35 . 3 kDa P1 protein and the 11 . 1 kDa HCPro fragment ( HC-97 ) ( Figure 3B ) . No proteolytic processing was detected in the construct bearing the VE-189 , 190-AA ( VE ) substitution in the VELI motif , indicating that it indeed belongs to the minimal protease domain , consistent with the disorder predictions . We found no appreciable differences between the wild-type P1 ( WT ) construct and those with FG-6 , 7-AA ( FG ) substitution in the IxFG motif or W63A E67A ( WE ) substitution in the FxxLE motif ( Figure 3B ) , in accordance with the finding that the N-terminal region is dispensable for potyvirus P1 processing [18] . We tested whether the Thosea asigna virus 2A ( T2A ) “self-cleaving” peptide [36] could overcome P1 protease defects and restore P1-HCPro separation . We confirmed that T2A insertion between P1 S259A and HCPro ( ST2A ) restored precursor processing , which , considering the barely detectable level of the predicted 48 . 9 kDa uncleaved product , was more efficient than with the wild-type P1 construct . To test their effect on viral infectivity , the P1 alanine substitutions used in in vitro translation were introduced into binary vectors bearing the full-length PPV cDNA . N . clevelandii plants were agro-infiltrated with Agrobacterium strains harboring pSN-PPV , pSN-PPV ΔP1 , or pSN-PPV plasmids with point mutations in P1 , and GFP fluorescence was monitored to follow the infection process of the derived viral clones . Infectious clones with full deletion ( ΔP1 ) or point mutations in the P1 sequence ( FG and WE ) had characteristic ring-shaped GFP foci with no detectable fluorescence in the center compared to the wild-type virus ( PPV ) ( Figure 4A ) . A similar phenotype was observed in a Potato virus A ( PVA ) clone with the GFP gene inserted into the P1 region [37] , suggesting that in this recombinant potyvirus , P1 function was also affected . Plants challenged with clones harboring the S or the HY mutations , which had no proteolytic activity in the in vitro translation assays , did not show GFP fluorescence , infection symptoms or CP accumulation ( Figure 4A–C and not shown ) . Although P1 VE-189 , 190-AA replacement led to no detectable cleavage in WGE experiments ( Figure 3 ) , a faint CP accumulation signal ( compared to wild-type PPV ) was visible in leaves agro-infiltrated with the VE clone harboring the same mutations , and the CP signal was greatly enhanced in systemically infected leaves ( Figure 4B and C ) . These leaves showed the characteristic ring-shaped GFP foci typical of the other infectious P1 mutants ( Figure 4A ) . The results led us to hypothesize that partial reversion might occur , restoring P1 protease activity . Western blot performed using anti-PPV HCPro antibody confirmed correct P1-HCPro processing in the upper non-inoculated leaves of plants agro-inoculated with the VE mutant clone ( Figure S2A ) . Samples of systemically infected leaves from these plants were further subjected to RT-PCR amplification of a PPV genome fragment spanning the mutations introduced . Though the E190A mutation was maintained , we detected reversion of V189A to the wild-type residue at 22 dpi ( Figure S2B ) . It is likely that , in contrast to clones S and HY , clone VE maintained minimal P1 self-processing activity sufficient to initiate viral replication and to select viral mutant progeny with improved cleavage efficiency . This is consistent with a report of a TEV clone in which disruption of the ( at that time undescribed ) VELI motif appeared to preclude P1 self-processing in vitro . A virus harboring the same mutation was infectious , however , and able to move systemically , with a marked delay compared to the parental virus [20] . At the same time point at which P1 VE-189 , 190-AA reversion was detected ( 22 dpi ) , the rest of the mutations introduced were stably maintained in both FG and WE infectious clones ( verified by RT-PCR and sequencing , not shown ) , confirming that mutations of N-terminal motifs are less detrimental than protease defects . Viability of the TEV clones altered by mutations in the P1 protease can be restored by insertion of a surrogate cleavage site recognized by the TEV NIa protease [20] , or in transgenic plants expressing the P1-HCPro cistron [32] . To test whether these rescue strategies complement defects in HCPro function rather than in P1 , we performed a transient RNA silencing assay in N . benthamiana . Leaves were co-infiltrated with an Agrobacterium strain bearing p35S:GFP as a silencing reporter and Agrobacterium strains containing the PPV silencing suppressor HCPro preceded by the wild-type P1 ( pWT ) , by P1 with an alanine replacement of the catalytic S259 ( pS ) or by P1 S259A plus T2A ( pST2A ) . GFP fluorescence was visible in all agroinfiltrated patches at 3 days post-agro-infiltration ( dpa ) ( not shown ) . At 6 dpa , there were no differences between the empty control and the S construct . In contrast , bright fluorescence as a result of silencing suppression was maintained when HCPro was effectively released by P1 protease activity or by the ribosome skipping mechanism of T2A ( Figure 5A ) . PPV viral clone ST2A , into which we inserted the T2A peptide sequence between P1 S259A and HCPro , was able to initiate viral replication ( 6 dpi; Figure 5B ) and move systemically despite the P1 protease-inactivating mutation ( Figure S2C; maintenance of P1 S259A substitution was verified by RT-PCR and sequencing , not shown ) . The presence of T2A was nevertheless insufficient to fully complement viral defects , since the ST2A GFP fluorescence phenotype and CP accumulation levels differed considerably from wild-type PPV ( Figure 5B , Figure S2C and D ) . To further validate these results , A . thaliana Col-0 and the RNA silencing-defective dcl2/3/4 line were agro-inoculated with the PPV S259A mutant ( S ) , using wild-type PPV as control . As predicted , wild-type PPV infected 16 of 16 challenged plants of both the mutant line and its wild-type background , at 23 dpi . Although we could not detect replication of the S mutant in Col-0 by GFP fluorescence or western blot analysis , GFP fluorescence was observed in 11 of 16 dcl2/3/4 plants ( Figure 5C ) . In spite of the cleavage-disturbing mutation in the S cDNA clone , P1-HCPro proteolytic separation was rescued in dcl2/3/4 plants inoculated with PPV S259A , as verified by western blot assay of HCPro ( Figure 5D ) . RT-PCR analysis of samples collected at 23 dpi confirmed that the original serine and the protease activity were restored in the viral progeny , since the wild-type serine 259 codon AGC , which was mutated to alanine GCC in the PPV S259A cDNA clone , was further mutated to serine UCC ( Figure 5E ) . The fact that viral reversion mutations are promptly selected in PPV S259A-infected plants suggests that P1 , in addition to the release of an active silencing suppressor , has further function ( s ) . According to MEROPS classification [38] , potyviral P1 serine protease belongs to subclan PA ( S ) , whose representative member , trypsin , is synthesized as the inactive precursor trypsinogen , with a disordered loop partially obstructing the substrate-binding cleft [39] . Supported by the intrinsic disorder prediction of the P1 N-terminal region and since a non-viral factor is needed for P1 protease activation [18] , we tested whether P1 also fits the trypsin model . Previous studies on TEV [40] , sequence alignment , secondary structure predictions , intrinsic disorder confidence , as well as the finding that in PPV , the VE-189 , 190-AA substitution disturbed P1 self-processing , were considered in choosing PPV P1 residues T162 and S170 as truncation points for a preliminary trial ( Figure 6A ) . N-terminal deletion constructs were made by removing the P1 sequence upstream of the codon for each amino acid selected , except for the initial methionine . To test P1 protease activity , we used in vitro translation in WGE and rabbit reticulocyte lysate ( RRL ) systems . The full-length P1 ( WT ) construct released the mature 35 . 3 kDa P1 protein in WGE but not in the RRL system ( Figure 6B , single asterisk ) , as anticipated [18] . Nonetheless , the T162 deletion construct successfully self-cleaved in both WGE and RRL systems , as shown by release of the 16 . 7 kDa P1 processed fragment ( Figure 6B , double asterisks ) . The S170 construct lacked activity in both in vitro translation systems , and only its uncleaved 27 . 0 kDa precursor was detectable ( Figure 6B ) , suggesting that the P1 residue delimiting the N-terminal minimal protease domain is located between positions 162 and 169 . To fine-map this boundary , additional single amino acid deletions were engineered , transcribed , and tested by in vitro translation . As a further control , the catalytic S259A mutation was included in the T162 construct to rule out misleading non-specific protein degradation . Efficient cleavage activity was maintained in both WGE and RRL after deletion of P1 N-terminal amino acids 2-164 ( Figure 6C , R165 construct ) , confirmed by release of the ≈16 kDa P1 mature fragment . Further truncations of the protease domain led to the drastic disappearance of protease activity in RRL , and gradually decreasing efficiency in WGE . The control protease catalytic mutant T162-S showed only a band corresponding to the unprocessed 27 . 8 kDa precursor . The results indicate that the protease catalytic domain is correctly folded even in RRL , and that the first 164 N-terminal residues are not only dispensable for this activity , but show an antagonistic effect on P1 self-processing in RRL . The PPV cDNA clone pSN-PPV P1Pro[V164] , lacking P1 amino acids 2-163 ( P1Pro , Figure 7A ) , was engineered to evaluate how a P1 protease free of its antagonistic N-terminal region affects viral replication . We deleted P1 residues upstream of position 164 , since the in vitro cleavage assays showed that the V164 construct was the most efficient P1 truncation tested ( Figure 6C , star ) . Various reporter genes cloned into viral infectious cDNAs were used to quantify potyviral genome replication rates [41] , [42] . Taking advantage of the GFP marker inserted in our PPV clones , fluorescence intensity ( FI ) signals were used to monitor viral amplification kinetics . Compared to the wild-type PPV , FI levels were significantly higher in leaves agro-inoculated with P1Pro clone at 46 h post-agro-inoculation ( hpi ) and 54 hpi ( 3 . 6- and 3 . 1-fold , respectively ) . At later time points , while the FI of wild-type PPV continued to increase over the 6-day time course , that of P1Pro slowed at 3 dpi and dropped to 0 . 4 times the level of parental PPV at 148 hpi ( Figure 7B ) . To support the GFP FI results , growth dynamics were analyzed in viral RNA by RT-qPCR ( Figure 7C and D ) . Fluorescence quantification values correlated positively with the amounts of PPV ( + ) RNA and ( − ) RNA ( Spearman's RS = 0 . 857 and RS = 0 . 976 , respectively ) . Viral amount at the end of the growth curve was further assessed by anti-PPV CP western blot , and confirmed that significantly less P1Pro virus accumulated than wild-type PPV at 148 hpi ( Figure 7E ) . These data demonstrate that initiation of PPV amplification is delayed transiently in the presence of the P1 N-terminal end , which is necessary to maintain higher viral accumulation rates in the long term . To test whether the PPV P1Pro viral decline depends on defects in RNA silencing suppression , we performed a transient agro-infiltration assay in N . benthamiana and N . clevelandii plants . GFP was used as silencing reporter , and was stably maintained in leaf patches co-expressing HCPro preceded either by the wild-type P1 ( pWT ) or by the P1 lacking amino acids 2–163 ( pP1Pro ) , as evaluated by GFP FI and western blot analysis ( Figure S3 ) . This suggests that deletion of the P1 N-terminal region does not impair HCPro silencing suppressor activity . To confirm and complement the early growth kinetics , we agro-inoculated N . clevelandii plants with PPV P1Pro and evaluated systemic infection . Symptoms in these plants , which were soon much more severe than those of plants inoculated with wild-type PPV , included marked stunting and necrotic lesions in the center of the larger chlorotic spots . As for the ΔP1 and P1 mutants ( Figure 4 ) , GFP fluorescence faded with progressing focus expansion in P1Pro-infected leaves , with no detectable signal in the center , and showing the characteristic ring shape before the appearance of necrosis ( Figure 8A ) . RT-qPCR analysis confirmed that in systemically infected leaves ( 21 dpi ) , despite more severe symptoms , less viral RNA accumulated in P1Pro-infected plants than in wild-type PPV samples ( Figure 8B ) . The identity of infecting viruses was confirmed by RT-PCR that encompassed the deletion , and by sequencing ( not shown ) . At the protein level , P1Pro-infected plant extracts were characterized by a specific band migrating at ≈35-37 kDa , which was unappreciable in wild-type PPV protein extracts and was thus analyzed by mass spectrometry ( MS ) ( Figure 8C ) . In the MALDI-TOF retrieved spectrum , the P1Pro band showed six prominent peaks ( Figure 8C ) , which were analyzed by MS/MS to obtain their peptide fragmentation fingerprint . Database searching allowed assignment of the m/z 1203 . 59 fragment to residues 326–335 of N . tabacum acidic PR-2 isoform GI9 ( GenBank accession no . P23547 . 1 ) . After removal of the signal peptide , this protein has a reported molecular weight of 34 . 8 kDa [43] , in good agreement with the electrophoretic mobility of the P1Pro-specific band . Sequence of the other five major peaks was defined de novo ( Figure S4A ) , since database identification of was unsuccessful due to unavailability of the host genome sequence ( N . clevelandii ) . Based on MS/MS spectra , we verified that all five matched a glucan endo-1 , 3-β-D-glucosidase , EC 3 . 2 . 1 . 39 , belonging to class II of the PR-2 family [44] , [45] , and that the minor amino acid changes identified were consistent with acidic PR-2 sequence variability in Solanaceae species ( Figure S4B ) . PR proteins of different families overaccumulate in tobacco plants that show hypersensitivity to Tobacco mosaic virus ( TMV ) [46]–[49] , but also after bacterial and fungal infection and in response to abiotic stress [50] . We first confirmed the MS results by western blot analysis for PR-2; next , to test whether PR-2 induction is a specific P1-associated defense mechanism or part of a broader stress response , we assessed class II PR-3 protein expression in infected N . clevelandii plants ( Figure 8D ) . We found that , despite the lower viral CP levels , PR-2 and PR-3 accumulation was significantly higher in P1Pro- compared to wild-type PPV-infected plants ( Figure 8E ) . In tobacco plants , exogenous salicylic acid ( SA ) treatment induces class II PR-2 and class II PR-3 transcription [48] , [51] , [52] , and activates the resistance responses associated to TMV-induced hypersensitivity [53] , [54] . Downregulation of SA accumulation and systemic acquired resistance was reported in transgenic plants that express the bacterial salicylate-hydroxylase gene nahG [55] . In N . benthamiana , while wild-type PPV-infected plants appeared almost symptomless , PPV P1Pro-infected plants showed extended chlorosis and necrotic lesions , similar to those observed in N . clevelandii ( Figure 9A ) . We therefore used transgenic N . benthamiana NahG plants [56] to evaluate the SA contribution in the PPV P1Pro host immune response . In accordance with previous studies [56] , downregulation of SA signaling had no appreciable effect on the wild-type PPV phenotype . In contrast , in P1Pro-infected NahG plants , systemic symptom severity was attenuated ( 10 dpi; Figure 9A and B ) . This result was supported by a sharp reduction in PR-2 protein accumulation in P1Pro-infected NahG plants and a weak increase in viral load , estimated by anti-PPV CP western blot analysis ( 12 dpi; Figure 9C and D ) . These data suggest that although SA-mediated antiviral pathways have only a minor role in wild-type PPV infection , they take part in P1Pro immune responses . In NahG-expressing plants ( i ) P1Pro-induced chlorosis was more accentuated than in wild-type PPV-infected plants ( Figure 9A ) , ( ii ) although lower than the wild-type host , PR-2 abundance in P1Pro samples was significantly higher than in wild-type PPV , and ( iii ) PR-2 reduction was insufficient to fully restore P1Pro viral accumulation to parental PPV levels ( Figure 9D ) . These findings prompted us to further investigate P1Pro-related defense responses after downregulation of SA signaling . To identify proteins whose abundance was significantly changed in P1Pro-infected NahG plants relative to wild-type PPV-infected NahG plants , we performed quantitative proteomic analysis using isobaric tag labeling ( iTRAQ ) and liquid chromatography ( LC ) -MS/MS [57] . A draft sequence of the N . benthamiana genome was released [58] , [59] , and a search against its predicted protein database enabled us to identify more than a thousand non-redundant proteins . Of these , 23 were considered to accumulate differentially in P1Pro versus wild-type PPV-infected plant samples , since they were found in both P1Pro biological replicates #A and #B , with a false discovery rate <5% as statistical cut-off ( Figure 10A ) . Gene ontology term enrichment analysis showed that , according to plant symptoms , the 23 dysregulated proteins associated significantly with the GO term “response to stress” ( GO ID: 6950 , p<0 . 0001; Figure 10B ) . In Figure 10C , we present a heat map of these quantified P1Pro proteins with their average iTRAQ ratios ( expressed in LOG2 ) relative to wild-type PPV biological replica #A . As predicted , P1Pro biological replicates #A and #B are grouped in the same hierarchical cluster , which differs from PPV biological replica #B . In P1Pro samples , several proteins from different PR families were more abundant than in wild-type PPV . These include a class II PR-2 ( in accordance with the western blot result; Figure 9C ) and other acidic members , which are regulated in tobacco mainly by SA [50] , [52] , and basic counterparts such as the basic PR-1 , whose transcription is effectively activated by ethylene [60]–[64] . Abscisic acid and osmotic stress are reported to induce expression of basic PR-5 [50] , [65] , as well as of dehydrin-like proteins [66] . The contribution of oxidative stress in the SA-dependent response to P1Pro is underlined by the detection of a peroxidase and a catalase; the tobacco homologue of the latter was initially identified as a SA-binding protein [67] . Only three of the 23 differentially accumulated host proteins were downregulated in P1Pro; these include two plastocyanins and a CP12-like accession , proteins essential for photosynthesis [68] , [69] . These data suggest that in the transgenic host , an important component of SA signaling is maintained and/or that its downregulation is partially compensated by alternative defense components . Besides the self-cleavage activity intrinsic to its C-terminal end , other activities of potyviral P1 and its real contributions to viral replication remained vague , so much so that P1 earned the appellative “mysterious protein” in a recent review [24] . In concomitance with the discovery that HCPro inhibits posttranscriptional gene silencing , it was suggested that P1 could act in conjunction with and strengthen the silencing suppressor activity of HCPro [25] , [26] . A characteristic ring-shaped GFP focus phenotype was related in tobamovirus infections with deficiency in RNA silencing suppression [70] , [71] . The same GFP phenotype was distinctive of all our PPV infectious clones with P1 sequence deletions and point mutations . In contrast , our Arabidopsis dcl2/3/4 complementation data demonstrate a major function for P1 independent of RNA silencing suppression . The ring GFP phenotype of P1 mutants might thus be related not only to a silencing suppression defect , but also to other altered functions . Recently , the silencing suppressor-enhancing effect of P1 was attributed to cis elements that improve translation efficiency , rather than to complementary activity of the P1 protein [72] . Our results nonetheless show that P1 is unquestionably involved in RNA silencing by limiting HCPro function . Deficiencies in polyprotein processing at the P1-HCPro junction abrogated PPV infectivity in wild-type plants , as also reported for TEV [20] , and were partially complemented by insertion of the T2A “self-cleaving” peptide . To further define the nature of this viral weakness , we used a transient RNA silencing assay to show that for correct silencing suppression , P1 must be effectively separated from HCPro , whether mediated by its own protease domain or by the ribosome skipping mechanism of T2A . In plants with impaired antiviral RNA silencing machineries the PPV S259A clone , with a cleavage-inactive P1 protease , recovered infectivity . The selection of viral revertant progeny demonstrated that strong evolutionary pressure for proteolytic competence of P1 was maintained , despite the host mutant background . The lack of separation between P1 and HCPro probably impairs not only the RNA silencing suppressor activity , but also other important viral functions . Of the mature proteins encoded by the potyviral genome , P1 presents the greatest variability in length and in amino acid sequence [73] . In silico analysis showed that the limited primary sequence conservation of the P1 N-terminal region is associated with residues predicted to be part of intrinsically disordered loops . The relevance of unfolded regions in the proteolytic maturation of viral polyproteins has been shown [6] , [7] , and flexible loops in peptidase precursors act in many cases as protease activation switches [39] . Previous results and those reported here show successful self-cleavage activity of potyviral P1 after in vitro translation only in the WGE system , but not in RRL . In consequence , it was suggested that a non-viral factor , present in WGE and absent in RRL , might be involved in correct folding of the protease domain or presentation of the cleavage site [18] . Our evaluation of the cleavage performance of P1 N-terminal end truncations demonstrates that the P1 minimal protease domain is active in WGE but also in RRL , suggesting that both eukaryotic translation systems support correct folding and activity of the P1 protease domain . Hence , the P1 N-terminal residues are not only dispensable for HCPro release , but also act as a negative regulator of P1 self-processing . In the context of viral infection , removal of the P1 protease antagonistic extension accelerated early viral replication and was followed by enhancement of symptom severity , with the appearance of plant stunting and necrotic lesions that did not characterize wild-type PPV . The greater aggressiveness did not parallel viral loads , however , as viral RNA and CP levels in plants systemically infected with the deletion mutant were lower than in wild-type PPV-infected plants . Lack of positive correlation between symptom severity and fitness is reported for several viral systems , including potyviral infections [74]–[76] . This can be justified by the crossing of a virulence threshold , which would result in higher induction of immune responses or excessive host debilitation [77] , [78] . Accordingly , the necrotic phenotype that characterizes PPV P1Pro was associated with overaccumulation of class II PR-2 and PR-3 proteins . Acidic PR-2 and PR-3 family members are indicators of SA-mediated responses to biotic stress and are hallmarks of systemic acquired resistance [48] , [50] , [79] . In a transgenic NahG-expressing plants , a decrease in SA signaling attenuated PPV P1Pro symptom severity . P1Pro-induced chlorosis was nonetheless more pronounced than in wild-type PPV-infected plants . Complex hormone crosstalk follows plant infection [80] , and compounds other than SA operate in the defense against pathogens [81]–[83] . Quantitative proteomic analysis of NahG plants infected with the P1Pro viral clone allowed us to identify a large set of stress response-associated proteins whose abundance was significantly altered compared to wild-type PPV . This includes upregulation of members of different PR families whose transcription is reported to be activated by SA but also by ethylene , and further modulated by abscisic acid [50] , as well as rearrangement of the antioxidant system , and downregulation of photosynthetic components , similar to other studies [84]–[86] . Coordinated action of both SA-dependent and -independent pathways probably contributes to the immune response activated by PPV P1Pro . In turn , the N-terminal extremity of the P1 protease , absent in P1Pro but maintained in wild-type PPV , helps to bypass induction of host defense responses . Several plant viruses interfere with salicylate pathways [87]–[89] , and it would be of interest to determine whether P1 also has an active role in suppressing basal host defenses independent of its HCPro activity-modulating effect . Considering that ( i ) defects in P1 self-cleavage preclude viral viability , ( ii ) viral RNA silencing suppression is impaired by the lack of separation between P1 and HCPro , ( iii ) P1 residues 1–164 are predicted to be mainly disordered , and negatively affect P1-HCPro processing in RRL , ( iv ) PPV early amplification dynamics are enhanced by removal of the P1 N-terminal end , ( v ) increased defense responses are associated with deletion of the P1 N-terminus , and ( vi ) removal of the P1 N-terminus reduces viral accumulation , we propose a model by which P1 acts to fine-tune potyviral replication by sensing specific host effectors . The presence of these cofactors leads to activation of the P1 protease domain and release of the silencing suppressor HCPro . The virus can thus effectively counteract host antiviral RNA silencing defenses and replicate successfully , but it can also stimulate additional defense responses . In an alternative scenario in which the cofactor is limited , P1-HCPro separation is restricted , RNA silencing suppression activity is disturbed , and some decrease in viral replication can therefore be predicted . We speculate that this mechanism holds viral replication below a level that would be detrimental to the host cell and reduces triggering of host immune responses , thus maintaining higher long-term replicative capacity . An example of restriction in a virus infection step to avoid host defense responses is the regulation of autoprocessing of the NS2 protein of the pestivirus Bovine viral diarrhea virus ( BVDV ) , which is dependent on the host chaperone Jiv [90] . Limiting amounts of Jiv cofactor result in accumulation of uncleaved NS2-3 and RNA replication arrest . Like the necrogenic interaction of PPV P1Pro , the disengagement of NS2 self-cleavage from cellular Jiv leads to a switch from a non-cytopathogenic to a cytopathogenic biotype , underlining the importance of the temporal modulation of NS2-3 processing [91] , [92] . To understand the regulation of P1-HCPro processing , identification of the P1 activating host effector will be a priority for future studies . Moreover , P1 protease multifunctionality was postulated [20] , [93] and indications that leader proteases retain activities independent of proteolytic processing can be found in several viruses [94]–[96] . Given the limited infection efficiency of the PPV ΔP1 viral mutant and the effects of mutagenesis of P1 conserved motifs , it is likely that P1 protein or its RNA coding sequence has additional unrevealed roles in potyviral replication . Potyviral P1 sequences were visualized and analyzed using Jalview [97] . Multiple sequence alignments were made using MUSCLE [98] . Protein disorder predictions were made with DISOPRED2 [33] , setting a false positive rate threshold of 10% , and MetaDisorderMD2 [34] . Secondary structure predictions used the JNet algorithm [99] included in the Jalview package , PsiPred [100] and SSpro [101] . Nicotiana clevelandii , N . benthamiana , N . benthamiana NahG [56] ( kindly provided by Prof . H . S . Guo , Chinese Academy of Sciences , Beijing , China , and Dr . F . Tenllado , CIB-CSIC , Madrid , Spain ) , Arabidopsis thaliana Col-0 and its triple mutant line dcl2-1 dcl3-1 dcl4-2 [102] ( kindly provided by Prof . J . C . Carrington , CGRB , Oregon State University , Corvallis , OR , USA ) were used . Nicotiana plants were grown in a greenhouse maintained at a 16 h light/8 h dark photoperiod , temperature range 19–23°C . Arabidopsis plants were grown in the greenhouse or in vitro ( see conditions below ) . A full-length cDNA copy of a PPV isolate [30] , tagged with sGFP ( S65T ) [103] and inserted in the pBINPPV-NK-GFP binary plasmid , was reported [104] . Cloning in binary vectors is often constrained by the availability of unique restriction sites or , in the case of the Gateway technology [105] , the maintenance of λ integrase recombination sites in the final constructs . To overcome these limitations , pBINPPV-NK-GFP was engineered to obtain the pSN-ccdB plasmid . Once linearized , pSN-ccdB is suitable for one-step seamless replacement of the PPV 5′UTR and the P1 cDNA sequence by Gibson assembly [106]; it was therefore used as a backbone for all the viral cDNA clones in this study . A detailed description of the viral vectors , together with in vitro translation and agro-infiltration constructs , can be found in Text S1 of the Supporting Information . In vitro transcription reactions were performed with the T7-Scribe Standard RNA IVT kit ( CELLSCRIPT ) , including final DNase I digestion . RNA was purified by organic extraction/ammonium acetate precipitation . Quality was assessed by NanoDrop ( Thermo Fisher Scientific ) and by gel electrophoresis , with final concentration adjusted to 1 µg/µL . In vitro translation was carried out in the presence of L-[35S]methionine and L-[35S]cysteine ( PerkinElmer ) using the WGE or the RRL translation system ( Promega ) , according to manufacturer's instructions . Samples were resolved in 12% tricine-SDS-PAGE [107] and the signal detected by PhosphoImager or autoradiography . Arabidopsis seeds were surface sterilized , kept at 4°C for three days , and sown in vitro on Murashige and Skoog medium [108] with MES and vitamins ( Duchefa ) , adjusted to pH 5 . 7 with KOH and supplemented with 1% ( w/v ) sucrose and 0 . 7% ( w/v ) Bacto Agar ( Difco ) . Six days after germination , plants were transferred to half-strength Murashige and Skoog medium with MES and vitamins , adjusted to pH 5 . 7 with KOH and supplemented with 1% ( w/v ) sucrose and 0 . 8% ( w/v ) Bacto Agar . At 9–10 days post-germination , agro-infection was performed as follows . Agrobacterium cultures were induced as described [28] , the final OD600 was adjusted to 1 . 5 , forceps were dipped into the culture , and the two youngest plantlet leaves were pierced . Forceps were flame-sterilized between cultures of different bacterial clones . Plates were sealed with gas-permeable tape ( Millipore ) and maintained in a growth chamber at 16 h light/8 h dark photoperiod , temperature 21±1°C , 60% relative humidity . The transient RNA silencing assay and agro-infiltration of N . benthamiana and N . clevelandii plants with A . tumefaciens strain C58C1 bearing the indicated plasmids , were as described [28] . The viral replication assay was conducted in three-week-old N . clevelandii plants following reported agroinfiltration and sampling guidelines [109] , with the exception that a saturating concentration of Agrobacterium was used . GFP fluorescence was monitored under long-wavelength UV light ( Black Ray , model B 100 AP ) and photographed using a Nikon D1X digital camera with a 62E 022 filter . Alternatively , images were acquired under a MZ FLIII epifluorescence microscope ( Leica ) using a GFP3 filter ( excitation and barrier filters at 470/40 nm and 525/50 nm , respectively ) and photographed with an Olympus DP70 digital camera . When indicated , GFP fluorescence was acquired by laser scanning ( Typhoon 9400 , GE Healthcare; laser 488 nm , intensity 450 V; 526 nm short-pass emission filter ) . GFP fluorescent intensity quantification was carried out placing individual 5 . 0 mm-diameter leaf discs in a black 96-well plate . Signals were acquired in an Appliskan ( Thermo Fisher Scientific ) or Victor X2 ( PerkinElmer ) plate readers with the following settings: measurement time 500 ms , excitation and emission wavelengths of 485/10 nm and 535/20 nm , respectively . Plant tissue was ground in a mortar in liquid nitrogen or homogenized in a TissueLyzer bead mill ( Qiagen ) . Total proteins were extracted in 150 mM Tris-HCl pH 7 . 5 , 6 M urea , 2% ( w/v ) SDS , 5% ( v/v ) glycerol and 5% ( v/v ) β-mercaptoethanol; heat denatured ( 96°C , 5 min ) and centrifuged ( 14000 rpm , 10 min ) to remove cell debris . Protein samples were separated by glycine-SDS-PAGE and electroblotted onto a nitrocellulose membrane . Ponceau red staining was used to control protein loading equivalence . Proteins were detected using anti-PPV CP and anti-PPV HCPro rabbit sera , and anti-GFP monoclonal antibody ( clones 7 . 1 and 13 . 1 , Roche ) as primary antibodies . Antibodies raised against tobacco class II PR-2 [44] and class II PR-3 proteins [47] were kindly provided by Dr . T . Heitz ( IBMP-CNRS , Strasbourg , France ) . Horseradish peroxidase-conjugated goat anti-rabbit IgG ( Jackson ) or sheep anti-mouse IgG ( GE Healthcare ) were used as secondary antibody . Immunostained proteins were visualized by enhanced chemiluminescence detection with a LiteABlot kit ( Euroclone ) . For signal quantification , chemioluminescence was acquired in a ChemiDoc XRS imager ( BioRad ) and analyzed with ImageJ software [110] . Total RNA was extracted with the FavorPrep Plant Total RNA Mini kit ( Favorgen ) . Fragments spanning the PPV 5′UTR , and the coding sequences of P1 and the HCPro N-terminus were amplified with the Titan One Tube RT-PCR kit ( Roche ) using primers 1595_F/1597_R ( Table S2 , in Text S1 ) . When indicated , fragments were purified using the FavorPrep Gel/PCR Purification kit ( Favorgen ) and DNA was sequenced . Strand-specific quantification of PPV RNA was done for at least three biological replicates per condition using tagged cDNA primers in the RT step [111]–[113] , and will be detailed elsewhere ( in preparation ) . Briefly , equal amounts of DNAseI-treated total RNA were used for cDNA synthesis using Superscript III ( Invitrogen ) and primer Q26_R or Q29_F to transcribe cDNA from positive and negative PPV genomes , respectively . Technical triplicate qPCR reactions were prepared using HOT FIREPol EvaGreen qPCR Mix Plus ( Solis BioDyne ) in 384-well optical plates and run in a 7900HT Fast Real-Time PCR System ( Applied Biosystems ) . Primer pairs Q27_F/Q28_R and Q30_F/Q31_R were used for positive and negative genome quantifications , respectively . The amount of target RNA in the analyzed samples was estimated by absolute quantification using an external DNA standard curve [114] . Plant total protein extracts were separated by glycine-SDS-PAGE and stained with Coomassie blue . Gel bands of interest were excised manually , reduced , alkylated and in-gel digested . The tryptic-eluted peptides were subjected to MALDI-TOF/TOF analysis . Data were automatically acquired in an ABi 4800 MALDI TOF/TOF mass spectrometer ( AB Sciex ) and searched against NCBI non-redundant protein database , NCBInr_20121116 . Mass tolerance for precursors was set to ±50 ppm and for MS/MS fragment ions to ±0 . 3 Da . The confidence interval for protein identification was set to ≥95% ( p<0 . 05 ) and only peptides with an individual ion score above the identity threshold were considered correctly identified . Manual peptide de novo sequencing was performed according Ma and Johnson [115] . Residues with near/isobaric masses were bona fide assigned according alignment consensus . Confidence of retrieved results was further tested with Peaks Studio software ( BSI ) [116] . N . benthamiana NahG plants were agro-inoculated with two independent bacteria cultures per each viral cDNA clone ( n = 2 biological replicates ) ; upper non-inoculated leaves were collected from 8 plants per culture ( 12 dpi ) . Total protein extracts were prepared as described for western blot assays and further purified by methanol/chloroform precipitation . Protein pellets were resuspended in 6 M guanidine hydrochloride and 100 mM HEPES , pH 7 . 5 , and concentration was determined by RC DC assay ( BioRad ) . Equal amounts of protein for each condition were trypsin-digested and labeled with iTRAQ Reagent Multi-plex kit ( AB Sciex ) . Tags 114 and 116 were used for P1Pro biological replicates and 115 and 117 for wild-type PPV biological replicates . Labeled peptide samples were combined and subjected to LC-MS/MS analysis ( three technical replicates ) using a nano liquid chromatography system ( Eksigent Technologies ) coupled to a Triple TOF 5600 mass spectrometer ( AB Sciex ) . MS and MS/MS data were processed using Analyst TF 1 . 5 . 1 software ( AB Sciex ) and searched using the Mascot Server v . 2 . 3 . 02 ( Matrix Science ) against a customized database represented by N . benthamiana genome-predicted proteins ( available at Sol Genomics Network [59] ) plus their corresponding reversed entries . Peptide mass tolerance was set to ±20 ppm for precursors and 0 . 05 Da for fragment masses . The confidence interval for protein identification was set to ≥95% ( p<0 . 05 ) , and only peptides with an individual ion score above the identity threshold were maintained in quantification analysis . Proteins were considered differentially expressed if they had at least two quantified peptides and they were present in both P1Pro biological replicates with a false discovery rate <5% . LOG2 ratios relative to PPV biological replica #A ( iTRAQ tag 115 ) were visualized by MultiExperiment Viewer [117] . Hierarchical clustering analysis with Pearson correlation distance metric was used to build the sample tree [118] . Sequences of reliably quantified N . benthamiana proteins were used as query in a WU-BLAST2 search against the TAIR10 protein dataset , to generate a list of homologous A . thaliana gene IDs . This was used as input in gene ontology term enrichment analysis using BinGO [119] . The following GenBank ( http://www . ncbi . nlm . nih . gov ) accessions were used in the viral sequence analysis: YMV ( YP_022752 . 1 ) ; PVV ( NP_734369 . 1 ) ; PVY ( NP_734243 . 1 ) ; VVY ( YP_001931974 . 1 ) ; CaYSV ( YP_003208051 . 1 ) ; JGMV ( NP_734408 . 1 ) ; MDMV ( NP_734143 . 1 ) ; SCMV ( NP_734133 . 1 ) ; SrMV ( CAC84438 . 1 ) ; PVA ( NP_734359 . 1 ) ; TEV ( NP_734207 . 1 ) ; ScaMV ( NP_734123 . 1 ) ; TuMV ( BAC02772 . 1 ) . Plant GenBank accessions considered: N . tabacum class II PR-2 ( P23547 . 1 ) ; N . tabacum class I PR-2 ( AAA63541 . 1 ) ; S . tuberosum class II PR-2 ( CAE52322 . 1 ) ; S . lycopersicum class II PR-2 ( NP_001234798 . 1 ) . N . benthamiana accessions can be found at Sol Genomics Network ( ftp://ftp . solgenomics . net/genomes/Nicotiana_benthamiana/annotation/ ) .
RNA viruses are ideal systems for the study of population dynamics , relationships among pathogen traits such as fitness and virulence , and of host immune responses to pathogen attacks . Based on experimental evolution studies , early models equated parasite virulence with fitness . Some reports showed that viral virulence and fitness can be unlinked . Here we present evidence that the highly disordered N-terminal region of a potyviral P1 protein negatively regulates its self-cleavage activity . Removal of this regulator domain greatly affects viral infection , which is characterized by accelerated early replication and enhanced symptom severity . These properties are nonetheless associated with low viral accumulation and high induction of antiviral resistance markers . Finally , we propose that host-dependent regulation of P1 processing efficiency modulates viral virulence and alleviates the host antiviral responses .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "plant", "science", "virulence", "factors", "and", "mechanisms", "virology", "plant", "pathogens", "plant", "pathology", "biology", "microbiology" ]
2014
The Hypervariable Amino-Terminus of P1 Protease Modulates Potyviral Replication and Host Defense Responses
Leprosy is an infectious disease caused by the obligate intracellular pathogen Mycobacterium leprae and remains endemic in many parts of the world . Despite several major studies on susceptibility to leprosy , few genomic loci have been replicated independently . We have conducted an association analysis of more than 1 , 500 individuals from different case-control and family studies , and observed consistent associations between genetic variants in both TLR1 and the HLA-DRB1/DQA1 regions with susceptibility to leprosy ( TLR1 I602S , case-control P = 5 . 7×10−8 , OR = 0 . 31 , 95% CI = 0 . 20–0 . 48 , and HLA-DQA1 rs1071630 , case-control P = 4 . 9×10−14 , OR = 0 . 43 , 95% CI = 0 . 35–0 . 54 ) . The effect sizes of these associations suggest that TLR1 and HLA-DRB1/DQA1 are major susceptibility genes in susceptibility to leprosy . Further population differentiation analysis shows that the TLR1 locus is extremely differentiated . The protective dysfunctional 602S allele is rare in Africa but expands to become the dominant allele among individuals of European descent . This supports the hypothesis that this locus may be under selection from mycobacteria or other pathogens that are recognized by TLR1 and its co-receptors . These observations provide insight into the long standing host-pathogen relationship between human and mycobacteria and highlight the key role of the TLR pathway in infectious diseases . Leprosy is a chronic granulomatous disease affecting the skin and peripheral nerves and caused by Mycobacterium leprae . Despite its being the first identified pathogen in humans , leprosy remains endemic in central Africa , Southeast Asia and South America with more than 200 , 000 new cases per year globally . Our understanding of the bacterial pathogenesis and interaction with the human host is limited , because of the inability to culture the bacterium in vitro . Nevertheless , twin studies [1] , familial clustering [2] and segregation analyses [3] studies have suggested that host genetics play an important role in susceptibility to this infectious disease with the heritability estimated up to 57% [4] . This allows genetic research to help understand the immunity against M . leprae and provide insight into the host-pathogen relationship . Although several genetic loci have been reported to associate with susceptibility to leprosy , candidates showing independent replications are scanty , and the vast majority of the phenotypic variation remains unexplained . To identify the genetic variants affecting susceptibility to leprosy , we conducted a population based case-control association study using a gene-centric 50 K microarray covering variants in 2 , 092 genes throughout the genome [5] , and found TLR1 and HLA-DRB1/DQA1 as major determinants of leprosy susceptibility . We also observe a high degree of population differentiation at the TLR1 gene , suggesting that mycobacterial diseases may have contributed to the evolution of this locus . These observations refine our understanding of the long interaction between human and mycobacteria and suggest that modulation of the TLR1 pathway may be valuable in future treatment of mycobacterial diseases . We genotyped 258 leprosy cases and 300 controls recruited from New Delhi , India where the disease is prevalent . Diagnosis of leprosy was made by at least two independent leprologists with standard histopathological examination of affected skin lesions . After quality control filtering , the genotype rate was 99 . 5% with separate multi-dimensional scaling ( MDS ) and principal component analysis ( PCA ) showing minimal population substructure in the 448 individuals ( 209 cases and 239 controls ) carried forward for analysis ( Figures S1 and S2 , Tables S1 and S2 ) . The strongest association was observed at the human leukocyte antigen ( HLA ) class II locus at chromosome 6p21 ( Figure 1 ) , with two SNPs showing genome-wide level of association ( rs9270650 P = 6 . 4×10−10 and rs1071630 P = 8 . 5×10−10 , Table 1 , Table S3 ) . We genotyped variants with P<1×10−4 in the primary association analysis , using the Sequenom MassArray primer extension assay in an independent case-control cohort recruited from Kolkata ( 220 cases and 162 controls ) , West Bengal as part of the replication study . To further minimise the possibility of population stratification resulting in spurious association , we undertook a family-based study recruited from Kumbakonam ( N = 941 with 161 families ) , Tamil Nadu in south India which is robust to population substructure [6] . These results provide further support for the HLA associations , with rs1071630 located in HLA-DQA1 showing convincing evidence of association across these populations ( case-control P = 4 . 9×10−14 , OR = 0 . 43 , 95% CI = 0 . 35–0 . 54 , Table 1 , Figure 2 , Figure S3 and Table S4 ) . Strong evidence of association was also observed with rs9270650 in HLA-DRB1 ( case-control P = 3 . 1×10−11 , OR = 2 . 24 , 95% CI = 1 . 76–2 . 86 , Table 1 , Figure S3 and Table S4 ) . Despite the more significant associations observed in the recessive models as compared to the dominant models , the allelic tests remained most significant suggesting that the alleles may be acting with a multiplicative effect ( Table S5 ) . The associations remained highly significant after corrections for age and gender in logistic regression models ( Table S5 ) . Statistical tests of heterogeneity showed similar effect sizes between the multibacillary and paucibacillary subtypes ( Table S6 ) . These results are consistent with a recently published study conducted in the Han Chinese population , showing association at the same locus with a similar effect size [7] . Conditional logistic regression analysis suggested that neither of these two variants can alone account for the observed association ( Table S7 ) , but instead form bi-variate haplotypes highly associated with disease states ( haplotype TC , case-control P = 7 . 3×10−15 , OR = 0 . 41 , 95% CI = 0 . 33–0 . 52; haplotype CT , case-control P = 5 . 2×10−12 , OR = 2 . 20 , 95% CI = 1 . 75–2 . 76 , Table S8 ) . Individuals homozygous for the risk alleles at both loci are more than eight times more susceptible to leprosy than their homozygous protective counterparts ( Figure S4 and Table S9 ) . Consistent direction of effect was also observed at the Toll-like receptor ( TLR ) gene cluster at chromosome 4p14 . The association peaks at a non-synonymous variant rs5743618 ( TLR1 I602S/T1805G ) , which affects receptor translocation to the cell surface [8] , with a significant protective association against leprosy in both New Delhi ( P = 1 . 3×10−6 , OR = 0 . 27 , 95% CI = 0 . 15−0 . 47 ) and Kolkata ( P = 0 . 012 , OR = 0 . 40 , 95% CI = 0 . 20–0 . 83 , Table 1 , Table S5 ) . The combined statistic from these two case-control populations showed strong evidence of association ( P = 5 . 7×10−8 , OR = 0 . 31 , 95% CI = 0 . 20–0 . 48 ) . The Kumbakonam family study showed a consistent direction of effect ( P = 0 . 090 , OR = 0 . 61 , 95% CI = 0 . 35–1 . 09 ) . Analyzed together with a small reported set of 57 cases and 90 controls in Turkey [8] , the best estimate of risk for the 602S allele is OR = 0 . 37 ( 95% CI = 0 . 26–0 . 51 ) with an overall P = 1 . 7×10−9 for the case-control studies ( Table 1 , Figure 2 and Table S5 ) . This association is the strongest among all 75 SNPs genotyped in the 80 kb flanking region , and accounts for the observed association in the locus ( Table S10 ) . The associations remained significant after corrections for age and gender ( Table S5 ) , with similar effect sizes between the multibacillary and paucibacillary subtypes ( Table S6 ) . Haplotypic analysis identified a haplotype containing the 602S variant that associated significantly with leprosy susceptibility ( CTTTCT , P = 1 . 3×10−6 , OR = 0 . 29 , 95% CI = 0 . 18–0 . 48 , Figures S5 and S6 , Table S11 ) , although this magnitude of effect is similar to the single locus association suggesting this effect is mainly driven by the 602S association . In fact , this TLR1 variant shows the most consistent association after HLA among the 2 , 092 genes tested in our microarray . However , this association was not observed in the recent GWA study [7] , likely due to the absence of this SNP on the array utilized by the Zhang et al , and the low power to detect the association by proxy SNPs due to the low allele frequency ( 1 . 7% ) in the Han Chinese population . The gene-centric microarray allows genic SNPs to be interrogated at a high density including putative leprosy susceptibility candidates ( Table 2 ) . Notably , evidence of association was observed at SNPs flanking MICA ( rs12660741 , P = 9 . 9×10−5 ) and TNF ( rs3093662 , P = 3 . 2×10−4 ) , both located on chromosome 6 . These associations remained nominally significant after correcting for the HLA variants rs9270650 and rs1071630 . These data suggest that these genes may be involved in immunity against M . leprae . However , we did not replicate the reported association with the LTA promoter variant [9] ( rs2239704/LTA +80 , P = 0 . 20 ) , or with the regulatory variants in PARK2/PACRG within the New Delhi case-control study as previously described [10] . Despite consistent replication at the Chromosome 13 locus ( C13orf31 and CCDC122 ) , we did not observe any significant association with variants in NOD2 , TNFSF15 or RIPK2 [11] that were identified in the recent GWA study [7] . The differences may be due to population specific effects which have been described in other diseases [12] or differences in allele frequencies . Infectious diseases have been a major selective force during human evolution [13] , [14] and have contributed to the diversity of the mammalian HLA genes [15] . Several studies have shown that this TLR gene cluster is highly differentiated between populations [16] , [17] , [18] . To further investigate the geographic distribution of this locus , we genotyped 12 SNPs in this region in 1 , 463 individuals from 6 populations ( New Delhi , Kolkata and Kumbakonam from India , Malawi , Gambia and United Kingdom , Table S1 ) . We observed a high degree of population differentiation at this locus [16] ( Figure S7 ) , which peaks at the I602S variant with a FST value higher than any other variants in this locus ( Table S12 ) . To compare the degree of differentiation with the rest of the genome , we genotyped I602S in the CEU , CHB and YRI populations [19] and observed extreme differentiation ( FST = 0 . 55 ) among over 3 million polymorphic SNPs in the genome ( >99th percentile ) . Mapping the global frequency of the I602S mutation in 15 different populations reveals that the protective serine allele is derived and rare in Africa , but expands in frequency to become the dominant allele in Europe ( Figure 3 and Figure S8 ) . Today , more than 40% of individuals of European descent are homozygous for this mutation . The ancestral isoleucine allele is crucial for protein translocation to the cell membrane , which is abrogated by the hydrophilic serine substitution resulting in a hypo-functional phenotype [8] , [20] , [21] that associates with protection against an important pathogen . Together with a recent study showing signature of selection at this locus [22] , these suggest that mycobacteria may have contributed to the extreme population differentiation at this locus . This provides insight into the host-pathogen relationship between human and M . leprae . Despite the long history of leprosy and medical advances , leprosy remains a scourge in many parts of the world . Our understanding of the pathogenesis of M . leprae and its interaction with humans is limited , in part due to the inability to culture the bacterium in vitro . For this reason , there is greater reliance on genetics to understand the disease and its causative pathogen . Some progress has been made to identify genetic loci which associate with susceptibility to leprosy; however the numbers of candidates showing consistent replication across populations are few . We here conduct a population based case-control association study , surveying genetic variants in more than 2 , 000 genes throughout the genome . Our gene-centric study identified genetic variants at TLR1 and HLA-DRB1/DQA1 as major determinants of leprosy susceptibility . These associations showed a consistent direction of effect across the populations under study , including the family samples from Kumbakonam in South India although the two-sided association statistic was borderline for the TLR1 variant ( Table 1 ) . These results minimize the chance that the associations are spurious , because the transmission disequilibrium test is known to be robust to population stratification . The human TLR1 has been previously shown to mediate immune response to M . leprae [21] . Our results advance our understanding of human immunity to M . leprae . Firstly , this present study is the first to show the consistent effect of TLR1 on leprosy susceptibility , at a significance level exceeding a genome-wide threshold . Secondly , the TLR1 association is the most significant after the HLA class II locus , of the greater than 2 , 000 loci surveyed . Although this result does not exclude the possibility of other genes involved in leprosy , it does support that the innate immune system , activated by the TLR receptors , plays a significant role in the defence against M . leprae in humans . Thirdly , the hydrophilic serine substation ( TLR1 I602S ) has been shown to result in a functional knockout phenotype [8] , [23] . Although this mutation is rare in Africa and Asia , our data suggest that a significant proportion of individuals of European descent are homozygous for this knockout variant . These functional TLR1 knockout individuals have a normal immunological phenotype and are protected against leprosy , suggesting that M . leprae may have utilized TLR1 as part of its pathogenesis mechanisms , as certain bacteria are known to produce homologues of the TLR1 signaling domain to subvert the innate immune responses [24] . Collectively , these results suggest that modulation of the TLR1 pathway may be valuable in future treatment of mycobacterial diseases without significant side effects . When we compare these results to the recently published GWA study [7] , we observed both consistent and discrepant results with the different genetic loci . Reassuringly , both studies confirm the class II HLA locus as a major leprosy susceptibility locus , a finding consistent with early studies reporting association of HLA with leprosy [25] , [26] . Consistent findings were also observed for genetic variants at C13orf31 and CCDC122 [27] . However , separate genotyping of the reported SNPs did not replicate the associations at the NOD2 , TNFSF15 or RIPK2 genes [27]; nor did the Zhang et al . study report any notable association at the TLR1 locus [7] . The disparity at the TLR1 locus is likely due to the low allele frequency of TLR1 I602S , and that the haplotype carrying this variant would have low power to detect the association . For the other associated genes ( NOD2 , TNFSF15 and RIPK2 ) there could be a number of reasons for the non-replication . The reported effect sizes of variants in these genes are moderate compared to the HLA and chromosome 13 locus . Assuming these effect estimates are real , the present study will have less power to detect these associations . Another possibility is a population specific effect whereby variants in these genes confer susceptibility in the Chinese population but not in the Indians . Given the significant differences in the genetic composition between the Indian and Chinese [28] , this may have contributed to the heterogeneous signals between the studies . Previous studies have described population specific genetic effects for other diseases [12] . Furthermore , despite the relative homogenous population of M . leprae , the 16 mycobacterial subtypes highly correlated with the geography can be readily identified [29] . Given the highly specialized nature of the immune system , these mycobacterial strains may activate the host immune response in slightly different ways , accounting for overlapping yet some discordant results between the studies . Finally , we cannot exclude the possibility that NOD2 , TNFSF15 and RIPK2 are not true leprosy susceptibility loci . This study provides insight into the host-pathogen relationship between human and M . leprae . Our data showed that the TLR1 locus is more highly differentiated as compared with the rest of the genome . Although the historical selective agents behind this differentiation are difficult to ascertain , our data suggests that mycobacterial infections may contribute to such a high degree of differentiation . Several studies have suggested that leprosy may be associated with reduced reproductive fitness [30] , [31] , and the all-cause mortality of lepromatous leprosy was reported to be at least 3 . 5 times of the general populations [32] , [33] . These factors , together with the long human co-existence with M . leprae [34] and intense social stigma associated with the disease [35] , suggest that leprosy may have contributed to the present global distribution of human TLR1 . Other infectious diseases especially tuberculosis could have also contributed , given the overlapping antigenic repertoire and immunogenicity of mycobacterial species , despite a lack of association in a Gambian case-control population due to low allele frequency ( Table S13 ) . However , given the lack of data on concurrent selective events , this hypothesis remains difficult to prove and other mechanisms are possible including genetic drift , population migration or bottlenecks , or a combined effect of two or more of these mechanisms . In conclusion , this study suggests that TLR1 and HLA-DRB1/DQA1 are important genetic determinants of susceptibility to leprosy . This study also shows a protective effect against an important pathogen with a hypo-functional TLR1 variant . These observations further highlight the key role of the TLRs in infectious diseases [36] , [37] and suggest that modulation of the TLR1 pathway may be valuable in future treatment of mycobacterial diseases . For the New Delhi cohort of samples , informed written consents following the Indian Council of Medical Research ( ICMR ) specification were obtained from all the individuals whose blood samples were collected . The study was approved by the Jawaharlal Nehru University ethics committee . For the Kolkata cohort of samples , approval was obtained from the ICMR and consent was obtained from the Tropical School of Calcutta and the Swasti Blood Donor Centre at Kolkata . For the Kumbakonam samples , ethical approval was obtained from the ICMR , New Delhi and Hindu Mission Hospital in Kumbakonam . We genotyped 258 leprosy patients and 300 controls from New Delhi [38] . After quality control filtering with call rates ( >95% for SNPs and >90% for samples ) , minor allele frequency ( >1% ) , Hardy-Weinberg equilibrium ( P>1×10−6 ) , relatedness ( <20% ) , heterozygosity ( 22–27% ) and outlying ancestry ( within 97 . 5th percentile ) , the genotype rate was 99 . 5% with separate multi-dimensional scaling ( MDS ) and principal component analysis ( PCA ) showing minimal population substructure in the 448 individuals ( 209 cases and 239 controls ) carried forward for analysis . The replication studies included 220 leprosy patients and 162 controls from Kolkata , and 941 individuals from 246 families from Kumbakonam [39] , with which 299 individuals ( 168 cases and 131 controls ) from Kolkata and 852 individuals from Kumbakonam were included after quality control filtering . Diagnosis and classification of leprosy was based on clinical and microscopic examination of the skin lesions . Patients were classified either as multibacillary ( MB , with bacterial index >0 ) , a group that included patients with lepromatous ( LL ) , borderline lepromatous ( BL ) and borderline ( BB ) leprosy , or as paucibacillary ( PB , with bacterial index of 0 ) which included patients with borderline tuberculoid ( BT ) and tuberculoid ( TT ) leprosy . Paucibacillary leprosy was characterized by the presence of large well-defined skin lesions which were less than five in number , dry and with almost 90–100% loss of sensation . Multibacillary leprosy was characterized by the presence of six or more skin lesions that were smaller in size , tending to be bilaterally symmetrical with about 10–40% loss of sensation . The study was approved by the relevant ethics committee . Informed consent was obtained from individuals whose blood samples were collected . In addition , we have also genotyped a total of 1 , 463 individuals from the Kumbakonam , India , Gambia , Malawi , United Kingdom , Tomsk and Tuva of Russia , and HapMap CEU , CHB and YRI populations [19] for the population differentiation study . All individuals in the New Delhi cohort were genotyped with the Illumina IBC gene-centric 50 K array [5] . The data quality control and analysis were performed using PLINK [40] . Multi-dimensional scaling ( MDS ) and principal component analysis ( PCA ) were carried out with PLINK and EIGENSTRAT to remove population outliers . The microarray genotypes more than 48 , 000 SNPs distributed in approximately 2 , 100 genes throughout the genome , including 3 , 470 non-synonymous markers . A total of 209 leprosy cases and 239 controls were carried forwarded for analysis . The SNPs in the replication studies and the population differentiation analysis were genotyped using the Sequenom MassArray primer extension assay . The TLR1 I602S polymorphism was additionally genotyped with a restriction enzyme digestion assay ( PstI ) , and the rs1071630 with a primer induced restriction assay ( MlyI ) . Separate MDS and PCA analyses were performed in PLINK to visualize the population structure in the New Delhi cohort ( Figure S1 ) , and individuals with outlying ancestry were removed . The analysis was performed in the resultant set of individuals . The primary test of association in the New Delhi and Kolkata cohorts was carried out with the Pearson's χ2 allelic test , Cochran-Armitage trend test and logistic regression ( Table S5 ) ; although the allelic test statistics were used in the main text and tables unless otherwise specified . The transmission-disequilibrium-test was used for the Kumbakonam family cohort . Both analyses were performed in PLINK . The primary association with the allelic test was performed without any correction . However , the associations at TLR1 and HLA-DRB1/DQA1 were further tested in a logistic regression model with correction for age , gender and the first MDS component ( Table S5 ) . As this study involves genotypes of genic instead of random SNPs , the quantile-quantile ( QQ ) plot was generated with comparison to the statistics of the same SNPs in the WTCCC Crohn's disease , rheumatoid arthritis and type 1 diabetes cohorts in addition to the expected values under the null hypothesis ( Figure S2 ) , which suggests that the statistics are not inflated by population substructure . The Mantel Haenszel statistics was used to combine data from case-control cohorts , but only when there was no significant heterogeneity in odds ratio between studies indicated by the Woolf's test . The haplotypic analysis was performed by Haploview , with the haplotypes reconstructed according to the confidence interval definition [41] . The fixation index FST was used for the population differentiation analysis . Let pi denote the allele frequency of the ith population and p-bar denote the mean allele frequency , the FST value is given bywhere n is the number of populations in comparison . The haplotype diversity analysis was performed with Haplosuite [42] .
Mycobacterium leprae is an obligate intracellular pathogen that causes leprosy , a disease that shares a long history with the human population but which remains endemic in many parts of the world . Despite the fact that the genome of M . leprae has been sequenced , our understanding of its pathogenesis and interaction with the human host is limited , in part due to the inability to culture the bacterium in vitro . In this gene-centric microarray study , we have genotyped SNPs in over 2 , 000 genes and identified TLR1 and HLA-DRB1/DQA1 as major leprosy susceptibility genes . Studying the geographical distribution of this hypo-functional TLR1 variant demonstrated extreme population differentiation at this locus . These results suggest that leprosy may have contributed to the evolution of this genomic region , and provide insight into the long history of the host-pathogen relationship between humans and M . leprae .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genetics", "and", "genomics/microbial", "evolution", "and", "genomics", "genetics", "and", "genomics/genetics", "of", "the", "immune", "system", "genetics", "and", "genomics/complex", "traits", "public", "health", "and", "epidemiology/epidemiology", "genetics", "and", "genomics/genetics", "of", "disease", "public", "health", "and", "epidemiology/infectious", "diseases", "infectious", "diseases/skin", "infections", "infectious", "diseases/bacterial", "infections", "genetics", "and", "genomics/bioinformatics", "genetics", "and", "genomics/medical", "genetics", "genetics", "and", "genomics/population", "genetics" ]
2010
Leprosy and the Adaptation of Human Toll-Like Receptor 1
Although evolutionary transitions from sexual to asexual reproduction are frequent in eukaryotes , the genetic bases of such shifts toward asexuality remain largely unknown . We addressed this issue in an aphid species where both sexual and obligate asexual lineages coexist in natural populations . These sexual and asexual lineages may occasionally interbreed because some asexual lineages maintain a residual production of males potentially able to mate with the females produced by sexual lineages . Hence , this species is an ideal model to study the genetic basis of the loss of sexual reproduction with quantitative genetic and population genomic approaches . Our analysis of the co-segregation of ∼300 molecular markers and reproductive phenotype in experimental crosses pinpointed an X-linked region controlling obligate asexuality , this state of character being recessive . A population genetic analysis ( >400-marker genome scan ) on wild sexual and asexual genotypes from geographically distant populations under divergent selection for reproductive strategies detected a strong signature of divergent selection in the genomic region identified by the experimental crosses . These population genetic data confirm the implication of the candidate region in the control of reproductive mode in wild populations originating from 700 km apart . Patterns of genetic differentiation along chromosomes suggest bidirectional gene flow between populations with distinct reproductive modes , supporting contagious asexuality as a prevailing route to permanent parthenogenesis in pea aphids . This genetic system provides new insights into the mechanisms of coexistence of sexual and asexual aphid lineages . While sexuality is the dominant reproductive mode in metazoans , parthenogenesis - the development of an embryo from an unfertilized egg - occurs in most branches of the animal kingdom ( e . g . molluscs , insects , crustaceans , nematodes , fish , reptiles ) [e . g . 1 , 2 , 3] . Cyclical parthenogenesis ( CP ) represents a mixed reproductive mode with an alternation of sexual reproduction and parthenogenesis , and is reported in many animal species [4] . The loss of the sexual phase in CP species - leading to permanently parthenogenetic taxa - have been shown to arise from diverse mechanisms , including microbial infection , hybridization , contagion via pre-existing parthenogenetic lineages or spontaneous mutations [5]–[9] . Nevertheless , in case of contagious or mutational origin , the precise genomic regions responsible for the transitions to obligate parthenogenesis ( OP ) remain largely unknown , mostly because dissecting the genetic bases of that trait using recombination-based approaches is not possible in strictly asexual species . However several species show coexisting CP and OP lineages , with OP lineages often retaining a residual production of males . Such species offer ideal systems to decipher the heredity and therefore the genetic basis of the loss of sexual reproduction . In the rare cases where it has been explored , genetic control of this trait has been shown to be rather simple , with the involvement of one to four loci , depending on the studied organisms [10]–[15] . However , the precise location and underlying function of these genetic factors have not been elucidated . The ancestral life-cycle of aphids is cyclical parthenogenesis [16] , which consists in an alternation of sexual and asexual generations . In spring and summer , CP lineages produce asexual females through apomictic parthenogenesis . In autumn , asexual females give birth to males and sexual females in response to photoperiodic cues ( note that CP lineages can also produce asexual females to some extent [e . g . 17] ) . Sexual females are strict clones of their asexual mothers , while one of the two X chromosomes is randomly lost to generate males [17] . Eggs produced by sexual females are the only frost-resistant stage in the aphid cycle . Hence , a CP life cycle is required to survive in regions with cold winters . In addition , many aphid species also encompass OP lineages which are characterized by an altered response to sex-inducing environmental cues as they produce only asexual females ( although they often produce some males [18] , [19] ) . These lineages are thus cold-sensitive because of their inability to lay eggs . Yet , OP lineages are favoured in regions with mild winters where they have a major demographic advantage over CP lineages [20] , [21] . Accordingly , CP lineages dominate in cold areas and OP lineages in warmer regions , and both coexist in regions with fluctuating winter temperatures [18]–[20] . Because male production by OP lineages is difficult to prove in the wild , it has been demonstrated in a single study which also showed that these males actually contribute to sexual reproduction with CP lineages [22] , [23] . While the switch from clonal to sexual reproduction in CP aphids is triggered by photoperiodic changes , the loss of sexual form production in OP aphids is genetically determined , changes in environmental conditions having little or no effect on their reproductive phenotype [10] , [19] . Here , we combined QTL and genome scan approaches to decipher the genetic bases of reproductive mode variation in the pea aphid Acyrthosiphon pisum . This species conveniently shows CP lineages ( here defined as those able to produce sexual females ) and OP lineages ( defined as those unable to produce sexual females ) , and these two types of lineages locally co-occur in regions with intermediate climate conditions [24] . These independent QTL and genome scan approaches outlined the same genomic region as controlling obligate parthenogenesis , this trait being recessive and determined by an X-linked locus . Our data also indicate that asexuality is transmitted in a contagious manner , leading to the conversion of sexual lineages into asexual ones . We produced F1 crosses between males of an obligate parthenogenetic lineage ( L21V1 ) and sexual females of two cyclically parthenogenetic lineages ( JML06 and LSR1 ) ( Fig . 1 ) . Five F2 crosses ( families 3 to 7 ) involving 6 F1 lineages were performed to obtain a genetic map and to locate QTL controlling the presence and proportion of sexual females by genotypes placed under sex-inducing conditions . A total of 305 microsatellite markers ( out of 394 ) was successfully ordered on the genetic maps . These loci clustered in four linkage groups that correspond to the four chromosomes of the pea aphid [25] . 45 loci locate on the X chromosome ( LG1 following notation in [26] ) , and 85 , 135 , and 40 on LG2 , LG3 and LG4 , respectively . Average map length ( over males and females ) was 113 , 95 , 79 and 59 cM for LG1 , LG2 , LG3 and LG4 , respectively ( Fig . 2 ) . Of the 89 unmapped loci ( out of 394 ) , 51 were monomorphic in the 3-generation pedigree , five were homozygous in all F1 females , and 33 showed null alleles at high frequencies or inconsistent genotypes ( presumably due to difficulties to score alleles ) . By contrast with the 61 F1 progeny which all produced sexual females ( hence were classified as CP ) segregation of reproductive phenotype was observed among the five F2 families ( Fig . 1 , families 3 to 7 ) . All five families ( 203 F2 genotypes ) comprised a mixture of genotypes expressing either an OP ( no sexual females produced at all ) or a CP ( sexual female production ranged from 22% to 77% ) phenotype . The percentage of OP F2 ranged from 7% to 35% depending on families ( Fig . 1 , see also S1 Figure ) . Contrastingly , 97% of F2 lineages produced males: only 5 out of 35 OP lineages , and 2 out of 168 CP lineages did not produce males ( S1 Figure ) . QTLs analyses on these five F2 families revealed one candidate genomic region located on the X chromosome ( LG1 ) for the control of reproductive mode variation ( measured as the proportion of sexual females or occurrence of sexual females ) , as evidenced by likelihood-ratio ( LR ) values for these traits above the LR thresholds corresponding to the null hypothesis of no QTL . The QTL for the proportion of sexual females produced locates at 38 . 0 cM on LG1 based on highest LR values . The 95% confidence interval [CI] for QTL position is 34 . 0–43 . 2 cM ( Fig . 2 ) . The QTL for presence/absence of sexual females locates at 37 . 6 cM on LG1 and the 95% CI is 34 . 8–43 . 6 cM ( Fig . 2 ) . We then accounted for the presence of a QTL at position ∼38 cM to test for a second QTL ( see Methods ) . No significant support for a second QTL was found for either traits , as LR values along the four chromosomes were largely below the LR thresholds corresponding to 5% significance at the genome level . We then focused on the genomic region pinpointed by the QTL analysis ( ∼38 cM on LG1 ) and looked at the alleles inherited by F2 individuals . In three F2 families ( families 3 , 4 and 6 , Table 1 ) , the 29 F2 lineages that expressed an OP phenotype had the same genotype as the OP lineage L21V1 ( F0 ) at all markers located on the X-chromosome between T_128012_2_G ( 34 . 8 cM ) and T_126075_3_Y ( 49 cM ) . For simplification , we refer to this multilocus genotype as “op1/op2” ( Table 1 , see also S1 Figure ) . Contrastingly , the 89 CP F2 individuals from families 3 , 4 and 6 all possessed at least one allele inherited from their CP grandmothers in this genomic region ( the four possible alleles from the two CP grandmothers are collectively referred to as “CP” ) . Hence these individuals were either op1/CP , op2/CP or CP/CP ( Table 1 , S1 Figure ) . In these three F2 families , the op1 allele was transmitted through the F1 fathers from the OP grandfather ( L21V1 , of genotype op1/op2 ) . Since chromosomes in male pea aphids do not recombine [27] , the entire X-chromosome of grandfather L21V1 that carries the op1 allele was transmitted to its grandchildren . Conversely , the op2 allele was inherited from the F1 mothers , which themselves inherited the whole op2-bearing X-chromosome from their OP grandfather . Recombination of the op2-bearing X-chromosome in the F1 mothers allowed reducing the region controlling reproductive modes between markers T_128012_2_G ( 34 . 8 cM ) and T_126075_3_Y ( 49 cM ) on the op2-bearing X chromosome ( S1 Figure ) . Based on the results from QTL analyses , we performed two additional crosses . Here only a subset of individuals per cross were phenotyped ( 24 and 27 , respectively ) , chosen according to their genotype at 8 microsatellite markers in the genomic region of interest . A F3 cross ( cross 9 , see Fig . 1 and Table 1 ) confirmed the location of the QTL and allowed further narrowing down its upper boundaries to marker 111865_3 [48 . 5 cM] ( see S1 Figure ) . We finally crossed op1/CP2 females with op2/CP3 males in order to recombine the op1-bearing X-chromosome ( cross 8 , Table 1 ) . All the 11 lineages that harboured the op1 allele in combination with the op2-bearing X-chromosome were OP , and recombination in the op1-bearing X-chromosome showed that the region controlling reproductive phenotype lies between markers 116879_10 ( 39 . 1 cM ) and D_111865_3 ( 48 . 5 cM ) on the op1-bearing X copy ( see S1 Figure ) . These different crosses revealed that op1 and op2 alleles are recessive over CP alleles ( since the 76 op1/CP and the 41 op2/CP lineages are CP , and the 12 op2/op2 and 43 op1/op2 lineages are OP , Table 1 ) . Noteworthy we observed that op1/op1 genotypes can have either a CP ( 11 lineages ) or an OP ( 6 lineages ) phenotype ( Table 1 ) , suggesting that other genetic or environmental factors mitigate the control of reproductive phenotype in lineages op1/op1 at the major candidate locus . A 436-marker genome scan performed on 109 individuals from wild populations collected in environments selecting for different reproductive modes ( OP or CP ) revealed four loci having excessive genetic differentiation ( FCT ) at the α = 0 . 01 threshold ( ARLEQUIN 3 . 5 analysis , Table 2 , S2 Figure ) . FCT between populations under selection for different reproductive modes ranged from 0 . 14 to 0 . 31 at these four outlier loci , while the median FCT value estimated over the 436 markers was 0 . 014 ( average 0 . 025 ) . Among these four outliers , T_111491_2 was also identified as outlier under balancing selection in the populations from CP-selecting environment ( FST among CP populations was 0 . 0003 , and He 0 . 56 ) when ARLEQUIN analyses were performed among populations assumed to share the same reproductive mode ( Table 2 ) . This locus was not successfully genotyped in the families so its genomic location remains unknown . Interestingly , the three other outliers co-locate on the X-chromosome and within the same genomic region identified with the experimental ( QTL ) approach ( Fig . 2 ) . Accordingly , FCT values along the genetic map of the four chromosomes show a clear peak of genetic differentiation in the QTL region ( Fig . 2 ) . In this region , expected heterozygosity in OP populations was lower than in CP populations ( S3 Figure ) , while heterozygosity values of the three CP populations and the three OP populations were similar along other regions of the chromosomes . We have shown here that a key ecological trait – the variation in reproductive mode – was controlled by one main genomic region in the pea aphid . This ∼9 cM-wide X-linked region was identified by two independent and complementary approaches: the co-segregation of molecular markers and phenotypes in experimental crosses and a large scale population genomic survey ( genome scans ) . Interestingly , 100% of phenotypic variation was explained by the genotype at the candidate locus in five crosses ( crosses 3 , 4 , 6 , 8 , 9 , Table 1 ) . In the two remaining families ( crosses 5 and 7 ) , this genomic region was also strongly associated with reproductive phenotype ( as all six OP F2 were op1/op1 at this candidate region ) but linkage was not absolute ( as 11 op1/op1 individuals are nevertheless CP ) ( Table 1 ) . Two hypotheses can be invoked for this lack of association in some F2 genotypes . First , an additional locus with minor effects might contribute to the control of reproductive mode variation , its contribution being only visible in individuals op1/op1 at the major locus ( all 68 individuals from crosses 5 and 7 that are not op1/op1 are CP ) . A second hypothesis is that the production of sexual females depends on a threshold concentration of some unknown factor ( e . g . transcript , protein , hormone ) . Under this assumption , minor environmental variation could have drastic effect on reproductive phenotype determination around the concentration threshold . We tested for the presence of a second QTL ( first hypothesis ) , and found no statistical support for it . Yet , power to detect such an additional QTL was low ( due to the small sample size of op1/op1 genotypes ) so we cannot at the moment disentangle these two hypotheses . Nevertheless , the mostly single-locus recessive inheritance of obligate parthenogenesis in the pea aphid is in line with the few similar studies which showed that the transition from sexual to asexual reproduction is determined by a small number of loci [10]–[14] . Transitions from cyclical parthenogenesis ( CP , i . e . the alternation of asexual and sexual generations ) to obligate parthenogenesis ( OP ) in aphids probably occur through loss-of-function mutations leading to an inability of lineages to produce females in response to the environmental cues that normally trigger the sexual phase . Hence , any mutation ( i . e . point mutation , indel or rearrangements ) that disrupts the pathway leading to the production of sexual females might be responsible for this transition . In theory , these loss-of-function mutations could occur repeatedly in the same gene , or on different genes involved in the same molecular cascade , these genes being either neighbours or scattered on the genome . Herein , the OP grand-parent used for QTL mapping harbours two distinct alleles ( op1 and op2 ) at the identified QTL and the phenotype of homozygotes op2/op2 and op1/op1 significantly differs ( all 12 op2/op2 but only 6 of the 17 op1/op1 individuals are OP , test of proportion: p = 0 . 0016 ) . This indicates that at least two independent mutations in the same region are involved in the loss of sexual reproduction . Remarkably , the genome scan demonstrates that the region identified by the QTL approach also shows signatures of divergent selection between populations under different selective regimes for reproductive mode . This indicates that the QTL identified with three laboratory clones is also involved in the control of reproductive mode in wild populations originating from a large-scale geographic area ( populations were collected up to 700 km apart ) . These population genomic data give further insights into the transitions from CP to OP . In particular , the occurrence of outliers in the QTL region , combined with their low genetic diversity in OP- compared to CP-selecting environments , reveal that only one or a few mutations leading to the OP phenotype have reached high frequencies in OP-selecting environments ( otherwise this genomic region would not have been identified as FST-outlier ) . Outside the candidate region , populations from CP- and OP-selecting environments are weakly differentiated and show highly correlated levels of genetic diversity along chromosomes , suggesting important gene flow . The most likely scenario to explain these genomic patterns of differentiation involves bidirectional gene exchanges between CP and OP lineages: Let us consider that the rare males produced by OP lineages successfully mate with sexual females from CP ( as it is the case in laboratory conditions and presumably into the wild ) , producing CP offspring heterozygous at the candidate region ( op/CP ) . These heterozygous CP lineages may produce OP progenies ( those homozygote for the op alleles ) that would survive if they encounter mild winter environments . Some minimal amount of gene flow can maintain a low genetic differentiation between populations from OP- and CP-selecting environments at the scale of the genome since divergence for neutral loci at a migration drift equilibrium is prevented when Nm>1 , N being the effective population size and m the migration rate [28] , [29] . Such bi-directional gene flow between OP and CP lineages may occur in the geographical regions with intermediate winter conditions where both CP and OP lineages coexist [22] , [30] . Another scenario to consider relies on unidirectional gene flow from CP to OP . Under the hypothesis that recessive op alleles are relatively frequent in CP populations , CP lineages will regularly produce new OP lineages ( those homozygous at the op alleles ) . If such OP linages are generated frequently , low differentiation between populations from OP- and CP-selecting environments along the genome is expected , except at the candidate region . This scenario is however less parsimonious than the former . First , it requires very frequent production of OP lineages by CP ones in order to prevent genomic differentiation between these two compartments likely to result from the strong clonal fluctuations ( due to neutral factors and/or selection ) typical of asexual populations [31] , [32] . Second , in absence of reciprocal gene flow from OP to CP lineages , positive selection on op alleles in CP populations should be invoked to maintain these alleles . Yet , we know that op alleles are associated with a cost in CP selecting environments ( homozygous op/op individuals do not survive cold winters ) and therefore their frequencies are expected to decrease under these conditions . Our data are thus best explained by bidirectional gene flow between populations of distinct reproductive modes and support the hypothesis of contagious asexuality in wild pea aphid populations . Contagious asexuality has important consequences on the evolvability of the OP lineages . Indeed , the bi-directional gene flow between CP and OP lineages allows genomes and alleles evolved under an asexual regime to enter the “sexual” pool via the few males produced by OP clones . Once introgressed in a CP lineage , a genomic region evolved under an asexual regime will recombine , allowing the purging of deleterious alleles . Later , if some of the CP individuals produce OP progeny ( those homozygous at the op/op genomic region ) , some of the alleles evolved under the asexual regime might then reintegrate an OP lineage . Hence , contagious asexuality has the potential to combine the beneficial effects of sex ( purging of deleterious mutations and combination of beneficial mutations within the same genome [33] , [34] ) with the advantages of clonal reproduction that avoid the two-fold cost of sex [34] and can “freeze” a genome ( avoiding recombination load ) [35] . This genetic system could thus favour the regular emergence of well fit OP lineages , which would be so fit because they would reuse alleles that competed and evolved under an OP-selecting environment ( during their long stay within OP lineages ) and that would have been separated from linked deleterious mutations during their sojourn in CP lineages . The physical size of the ∼9 cM candidate region , that represents ∼2 . 6% of the whole genome in term of recombination units ( cM ) , is still unknown because scaffolds from the pea aphid genome sequence are not yet ordered on chromosomes [36] . Hence the exact number and nature of the genes that are comprised within the candidate region are not known . Nevertheless , already 66 genes encoding proteins have been identified in the three scaffolds covering part of the 9 cM genomic region of interest ( S1 Table ) . It is too early to designate candidate genes responsible for the CP/OP phenotypes , mostly because half of them have no predicted functions . However , recent works on the genetic programs involved in the seasonal switch from clonal to sexual reproduction in CP lineages allow highlighting in the candidate region three predicted genes putatively involved in photoperiod perception and brain signalling ( e . g . rhodopsin specific isomerase , insulin ) , two pathways identified as differentially expressed in aphids exposed to either clonal or sex induction regimes [37] . Two genes putatively involved in the melavonate pathway ( farnesyl-pyrophosphate synthase like and hydroxymetharyglutaryl-CoA synthase ) upstream of the juvenile hormone synthesis , which is known as being a key regulator of reproductive orientation in aphids [38] , [39] , also locate within the candidate region . To conclude , here we combined population genomics and quantitative genetics to identify the genetic bases of a key trait for aphid adaptation to climate - the loss or maintenance of sexual reproduction . We found this trait to be controlled by one main genomic region located on the X chromosome . The widespread geographical distribution of a few alleles associated with obligate asexuality suggests that these alleles might be particularly advantageous for OP lineages , and might have outcompeted previously established op alleles , a hypothesis that deserves further investigations . We crossed individuals from three genotypes ( clones LSR1 , L21V1 , JML06 ) that present contrasted reproductive phenotypes . These three F0 lineages were chosen based on their ability to produce or not sexual females under standard sex-inducing conditions ( i . e . short photoperiod with 12 h light ) [37] . All aphids were reared on Vicia faba ( broad bean ) because it is a universal host for all known host races of the pea aphid species complex [40] , [41] and also because this plant is easier to grow compared to Medicago ssp . LSR1 ( collected on Medicago sativa in New-York , USA in 1998 and used for complete genome sequencing [36] ) produces males ( 21% ) , sexual females ( 54% ) plus some parthenogenetic females ( 25% ) under standard sex-inducing conditions . Under the same inducing conditions , JML06 ( sampled on Medicago lupulina in Jena , Germany in 2006 ) produces only sexual individuals ( 70% males and 30% sexual females ) . Contrastingly , L21V1 ( sampled on M . sativa in Rennes , France in 2003 ) produces only parthenogenetic females ( 89% ) and a few males ( 11% ) . LSR1 and JML06 are therefore classified as cyclical parthenogens ( CP ) and L21V1 as obligate parthenogen ( OP ) . Crosses between males from the OP and ( sexual ) females from the CP lineages were performed . For this , one L4 larva from each of the three grandparent clones was moved to a new broad bean plant and transferred to a climatic chamber with a 12 h photoperiod ( 18°C ) to trigger the production of sexual females and males in CP lineages ( and males in the OP lineage ) [37] . Then , for each lineage , three larvae of the next clonal generation were isolated on three different broad bean plants . Once the larvae reached adulthood and started to give birth to nymphs , groups of 10 larvae of the next generation were isolated on new broad bean plants until the asexual female stopped reproducing and died . The morph of each individual of this second clonal generation ( i . e . male , sexual females , asexual females ) was determined at adult stage based on morphological characters ( males are slender than females , and the legs of sexual females are longer that those of asexuals ) . The few individuals that died before reaching the adult stage ( hence before being sexed ) were also counted . Then a total of 50 males from the clone L21V1 and 50 sexual females from the clone JML06 were put together on broad bean plants ( Vicia faba ) to generate a F1 family ( cross 1: JML06 ♀×L21V1 ♂ , Fig . 1 ) . The 50 sexual females used in the cross are clonal . However , males consist of two different genotypes because they inherit randomly one of the two X copies from their asexual mother ( approximately half of males are expected to bear the first X copy of their mother and the second half the other copy ) [17] . A second F1 family was generated similarly by crossing 50 L21V1 males with 50 LSR1 sexual females ( cross 2 , Fig . 1 ) . In Fig . 1 , dotted lines show lineages used as male and plain lines those used as female . Eggs were kept at 4°C ( 80% humidity ) for 85 days and were then transferred at 18°C for hatching . A few days after the first eggs hatched , 50 parthenogenetic larvae for each cross were isolated on new broad bean plants . Each F1 lineage was kept for 7 to 9 months under conditions sustaining clonal reproduction ( 16 h light , 18°C ) . Reproductive phenotype of the F1 lineages was then assessed similarly . Six F1 lineages ( three per cross ) were then chosen to produce the next F2 generation ( Fig . 1 ) . All F1 produced sexual females ( with from 27% to 71% and 28% to 64% sexual females for cross 1 and 2 , respectively ) , hence were CP . The 6 F1 clones were thus chosen to cover the diversity in terms of the production of males ( that ranged from 0–73% and 0–55% males for cross 1 and 2 , respectively ) and asexual females ( that ranged from 0–42% and 1–53% for cross 1 and 2 , respectively ) . Five F2 crosses ( crosses 3 to 7 in Fig . 1 ) were performed using the same protocol as for the F1 . 44 to 47 F2 lineages per family ( hence 229 F2 lineages in total ) were then isolated and kept for subsequent assessment of reproductive mode phenotype ( same protocol as for the F0 and F1 ) . Twenty-six F2 lineages ( out of 229 ) died before being phenotyped . The three grand-parents , the six F1 parents and the 229 F2 individuals from families 3 to 7 were typed at 401 microsatellite loci ( see S2 Table for loci used and [42]–[44] for primer sequences ) . We first checked for the presence of null alleles by looking at the inheritance of alleles in the 3-generation pedigree . Homozygous individuals originating from parents displaying a null allele were transformed into missing data . Loci located on the same chromosome were identified based on their complete linkage in males ( 2n = 8 in the pea aphid and chromosomes in males do not recombine ) [27] , [45] . Genetic maps were then constructed for each of the four chromosomes with Crimap 2 . 53 [46] using Kosambi mapping function . Linkage maps were drawn using MAPCHART v . 2 . 1 [47] . QTL detection was then performed with the interval mapping method implemented in QTLmap , using the LDLA approach [48] . The phenotypic traits analysed for each F2 lineage ( from crosses 3 to 7 ) were the occurrence ( binary variable ) and the percentage ( quantitative variable ) of sexual females in the parthenogenetically produced offspring . We focused on these traits because the production of sexual female is the most relevant variable to predict whether a population is able to reproduce sexually or not [10] , [49] . In our analyses , we set parameter ndmin to 200 so that no information from males meioses was used to locate QTLs ( since chromosomes do not recombine in males , males are not informative to locate QTLs within chromosomes ) . QTLs were detected based on likelihood-ratio ( LR ) along chromosomes . LR values corresponding to a significance level of 0 . 05 for each chromosome were empirically determined from 1 , 000 simulations under the null hypothesis of the test ( i . e . no QTL ) . Genome-wide significance levels ( i . e . LR values corresponding to adjusted p-values ) were computed to account for multiple testing ( i . e . four tests , corresponding to the four chromosomes ) . The drop-off method implemented in QTLmap was applied to obtain 95% confidence intervals of the QTL location . Similarly to the reduction of x-LOD when using LOD scores , the maximum LR value was reduced by 3 . 84 ( corresponding to a Chi2 distribution with one degree of freedom for p<0 . 05 ) to determine a threshold . Region boundaries were then defined by the LR locations crossing this threshold upstream and downstream of the peak LR [as described in 50] , [51] to identify the 95% CI of the QTL . After identifying the first QTL ( see Results ) , we tested for the presence of a second QTL . For this , genotype at locus T_121775_26 ( the closest marker from the peak of the QTL on LG1 ) was introduced as a fixed effect in the model . This marker is highly discriminative as each of the three grandparents possesses different alleles . LR for the presence of a QTLs against the hypothesis of no QTL was then compared to LR thresholds corresponding to a 5% significance determined by 1000 simulations in QTLmap . The QTL approach led to the identification of a single genomic region , located on the X chromosome , which controls reproductive mode ( see Results ) . Yet , in the three F2 crosses that were highly informative , all lineages used as mother inherited by chance the same X chromosome copy from their OP father ( remind that chromosomes do not recombine in male aphids ) . From these crosses and from recombination events , we determined that the gene ( s ) that control ( s ) reproductive mode locate ( s ) between markers T_128012_2_G ( 34 . 8 cM ) and T_126075_3_Y ( 49 cM ) on this X copy ( see Results ) . The segment of this X chromosome copy is referred to as “op2 allele” hereafter . However , we had little power to test whether the same region also controls this trait on the second X copy from the OP grandparent ( that we refer to as “op1 allele” ) . We therefore performed an additional F2 cross ( cross 8: X2_25♂×X1_3 ♀ ) to recombine the X-chromosome bearing the op1 allele ( the mother X1_3 ♀ bears one op1 allele ) . We also crossed X6_2♂×X3_4♀ ( that each possesses an op2 allele , cross 9 ) to produce homozygous individuals at this X chromosome region ( i . e . op2/op2 ) to assess the dominance status of the different alleles in the candidate region ( i . e . op1 , op2 , and those inherited from CP clones , referred to as CP1 , CP2 , CP3 and CP4 ) . Since these two crosses were performed after we had identified the genomic region controlling reproductive mode variation , only a subset of individuals were phenotyped ( 24 and 27 , respectively ) , chosen accordingly to their genotype at 8 microsatellite markers in the genomic region of interest ( see S1 Figure for markers used ) . Pea aphid individuals were collected in alfalfa fields from six sampling sites ( S3 Table ) . All A . pisum individuals were sampled from the same plant species ( Medicago sativa ) to prevent confounding effects of plant or reproductive mode specialization on genetic divergence [52] . Three of the sites locate in north-east France or Switzerland and correspond to regions with cold winters ( “temperate continental climate” as defined in [53] ) . In these areas , pea aphid populations consist mainly of CP lineages , because eggs are the only stage that survives cold winters [19] ( we thus consider these areas as CP-selecting environment ) . Individuals were collected in spring 2008 , a few weeks after egg hatching to maximize the probability to sample locally overwintering populations ( these samples have been used in [43] , [44] ) . The three other sampling sites locate in south-west France , and correspond to regions characterized by mild winters ( i . e . “temperate oceanic climate” as defined in [53] ) . These areas are considered as OP-selecting environment . Here , sampling took place in winter 2008–2009 because at this season , OP lineages can be discriminated from CP ones , since the former overwinter as parthenogenetic females while the latter spend winter as eggs . Parthenogenetic females were collected from the six populations ( see [43] for further details ) . To obtain sufficient amounts of DNA for genotyping hundreds of microsatellites , field-collected aphids were grown individually in controlled conditions ensuring continuous clonal reproduction ( 16 h light/day , 18°C ) . In each of the 6 geographic populations we then kept 20 individuals ( except for one population for which only 15 individuals successfully established in the lab to provide sufficient DNA ) on which all further analyses were conducted . These 115 individuals were genotyped at 443 microsatellite loci ( 301 of them were positioned in the genetic maps , see S2 Table ) . Six individuals ( out of 115 ) with more than 15% missing genotypes were removed as well as seven markers ( out of 443 ) with more than 30% missing data . To detect loci that depart from neutral expectation , and which are therefore potentially involved in reproductive mode variation , we used a hierarchical method [54] implemented in ARLEQUIN 3 . 5 [55] . The distribution of the genetic differentiation among populations characterized by different reproductive mode expected under neutrality was estimated by means of coalescent simulations . The among-reproductive mode differentiation was characterized by the parameter FCT , which accounts for the geographical structure within populations ( three populations originate from OP-selecting environments and the three other from CP-selecting environments ) . 100 000 coalescent simulations were performed conditionally on the multilocus estimate of FCT at the 436 microsatellite loci , assuming 50 groups and 100 demes per group . The observed data from each locus were compared with the simulated distribution , and a particular locus was classified as a significant outlier if it fell outside the 99% confidence envelope . We focused here on loci putatively involved in divergence between populations with contrasted reproductive mode; hence , we considered in this analysis only the loci falling above the upper confidence limit . As we were interested in identifying outlier loci involved in the variation of reproductive mode , and not in adaptation to local environmental conditions , we checked that the outliers identified from this global analysis ( in which the two types of populations were included simultaneously ) were not classified as outliers ( either under divergent or balanced selection ) among populations sharing the same reproductive phenotype . To that end , we ran two independent analyses for the detection of outliers within populations sharing the same reproductive mode . We also checked that the outcomes of genome scan analysis were not affected by the inclusion of markers with >10% missing data ( 58 loci ) . Since the confidence interval was similar when including or not markers with >10% missing data and because our aim was to screen the genome with the highest number of markers , we present only the analysis based on the whole dataset ( 436 markers ) .
Asexual lineages occur in most groups of organisms and arise from loss of sex in sexual species . Yet , the genomic bases of these transitions remain largely unknown . Here , we combined quantitative genetic and population genomic approaches to unravel the genetic control of shifts towards permanent asexuality in the pea aphid , which conveniently shows coexisting sexual and asexual lineages . We identified one main genomic region responsible for this transition located on the X chromosome . Also , our population genetic data indicated substantial gene exchange between these reproductively distinct lineages , potentially leading to the conversion of some sexual lineages into asexual ones in a contagious manner . This genetic system provides new insights into the mechanisms of coexistence of sexual and asexual lineages .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genomics", "reproductive", "system", "signatures", "of", "natural", "selection", "anatomy", "genome", "scans", "natural", "selection", "genome", "analysis", "genetics", "biology", "and", "life", "sciences", "population", "genetics", "computational", "biology", "evolutionary", "biology", "ecological", "selection", "evolutionary", "processes", "asexual", "reproduction" ]
2014
Genetic Control of Contagious Asexuality in the Pea Aphid
Enteric fever remains a major public health problem in low resource settings and antibiotic resistance is increasing . In Asia , an increasing proportion of infections is caused by Salmonella enterica serovar Paratyphi A , which for a long time was assumed to cause a milder clinical syndrome compared to Salmonella enterica serovar Typhi . A retrospective chart review study was conducted of 254 unique cases of blood culture confirmed enteric fever who presented at a referral adult hospital in Phnom Penh , Cambodia between 2008 and 2015 . Demographic , clinical and laboratory data were collected from clinical charts and antibiotic susceptibility testing was performed . Whole genome sequence analysis was performed on a subset of 121 isolates . One-hundred-and-ninety unique patients were diagnosed with Salmonella Paratyphi A and 64 with Salmonella Typhi . In the period 2008–2012 , Salmonella Paratyphi A comprised 25 . 5% of 47 enteric fever cases compared to 86 . 0% of 207 cases during 2013–2015 . Presenting symptoms were identical for both serovars but higher median leukocyte counts ( 6 . 8 x 109/L vs . 6 . 3 x 109/L; p = 0 . 035 ) and C-reactive protein ( CRP ) values ( 47 . 0 mg/L vs . 36 mg/L; p = 0 . 034 ) were observed for Salmonella Typhi infections . All but one of the Salmonella Typhi isolates belonged to haplotype H58 associated with multidrug resistance ( MDR ) ( i . e . resistance to ampicillin , chloramphenicol and co-trimoxazole ) . ;42 . 9% actually displayed MDR compared to none of the Salmonella Paratyphi A isolates . Decreased ciprofloxacin susceptibility ( DCS ) was observed in 96 . 9% ( 62/64 ) of Salmonella Typhi isolates versus 11 . 5% ( 21/183 ) of Salmonella Paratyphi A isolates ( all but one from 2015 ) . All isolates were susceptible to azithromycin and ceftriaxone . In Phnom Penh , Cambodia , Salmonella Paratyphi A now causes the majority of enteric fever cases and decreased susceptibility against ciprofloxacin is increasing . Overall , Salmonella Typhi was significantly more associated with MDR and DCS compared to Salmonella Paratyphi A . Salmonella enterica serovar Typhi ( Salmonella Typhi ) and Salmonella enterica serovars Paratyphi ( Salmonella Paratyphi ) A , B , and C are Gram-negative bacteria which can invade the bloodstream and cause typhoid and paratyphoid fever respectively ( also jointly known as ‘enteric fever’ ) . They are confined to the human host and are transmitted via the fecal-oral route . Enteric fever poses a serious disease burden in low resource settings where the infection is linked to poor sanitation and limited access to safe drinking water [1] . Although enteric fever has become rare in Western countries it continues to affect international travelers returning from endemic countries [2] . Patients with enteric fever typically present with acute fever and non-specific symptoms . For a long time , Salmonella Paratyphi A was thought to cause milder disease than Salmonella Typhi but several studies have contradicted this [1–4] . For both serovars , antibiotic resistance is increasingly reported and there is now widespread presence of co-resistance against the former first line treatment options of ampicillin , co-trimoxazole and chloramphenicol ( known as ‘multidrug resistance’ ) and decreased susceptibility to ciprofloxacin , the current first line drug [5 , 6] . Resistance to ciprofloxacin is also increasingly reported [7 , 8] . Worrisome are recent reports on emerging resistance against third-generation cephalosporins and azithromycin , the current alternative treatment options [9 , 10] . Although historically the majority of enteric fever cases were caused by Salmonella Typhi , the proportion of Salmonella Paratyphi A infections has been increasing steadily since the turn of the century , in particular on the Asian continent [11] . In 2013 , a significant increase in Salmonella Paratyphi A infections was also observed in Cambodia , a country where enteric fever remains one of the most common clinical and blood culture-confirmed diseases [12] . The increase was described in local residents as well as in travelers returning from Cambodia to Europe , New Zealand , Japan and the United States [13–16] . Surprisingly , little is known about the clinical and microbiological characteristics of Salmonella Typhi and Salmonella Paratyphi A infections in Cambodian adults . This study therefore aims to assess the clinical and microbiological aspects of enteric fever in patients attending an adult hospital in Phnom Penh , Cambodia , during 2008–2015 . More specifically it aims to assess differences between infections caused by Salmonella Typhi as compared to Salmonella Paratyphi A . Sihanouk Hospital Center of HOPE ( SHCH ) is a 40-bed non-governmental referral hospital for adults in Phnom Penh , Cambodia . Since July 2007 , SHCH and the Institute of Tropical Medicine ( ITM ) in Antwerp , Belgium , have been jointly organising the surveillance of bloodstream infections at this hospital and its associated clinics . For this study , all data collected between 2008–2015 were analyzed . Blood cultures were systematically sampled in all patients presenting at SHCH who were suspected of having sepsis according to the Systemic Inflammatory Response Syndrome ( SIRS ) criteria [17] . Recently , new definitions and criteria for sepsis have been proposed such as the Sequential [Sepsis-related] Organ Failure Assessment ( SOFA ) score [18] . Over the 8-year period , 18 , 927 blood cultures were sampled from mostly , but not exclusively , adults [19] . Of these cultures 1 , 654 ( 8 , 7% ) yielded clinically significant organisms . From all patients whose blood was drawn for culture , basic demographic and clinical data were registered in a surveillance logbook . A medical doctor verified missing data with patients during a routine phone call one week after discharge from the hospital which was part of standard care . In addition , for this study , the available medical charts of all patients with blood culture-confirmed enteric fever were reviewed retrospectively by a second medical doctor for additional symptoms and signs . Hematology parameters were analyzed using a Sysmex KX-21 and T-1800i analyzer ( Sysmex Corporation , Kobe , Japan ) and CRP values were measured using a TEMIS Linear Analyzer ( Linear Chemicals sl , Montgat , Spain ) . Blood cultures were sampled and worked-up as previously described [20] . Isolates biochemically identified as Salmonella spp . were stored at -70°C on porous beads in cryopreservative ( Microbank , Pro-Lab Diagnostics , Richmond Hill , Canada ) and eventually shipped to the ITM in Belgium . At ITM , the isolates were serotyped using commercial antisera ( Sifin , Berlin , Germany ) following the White-Kauffmann-Le Minor scheme . A selection of 91 isolates were sent to the Institut Pasteur in Paris for confirmation and whole genome sequencing . At the ITM , antibiotic susceptibility was determined for all available isolates by disk diffusion on Mueller-Hinton II agar in accordance with the CLSI 2016 guidelines [21] . The following antimicrobial drugs ( Neo-Sensitabs , Rosco , Taastrup , Denmark ) were tested: ampicillin , sulfamethoxazole-trimethoprim , chloramphenicol , nalidixic acid , pefloxacin , gentamicin , tetracycline , ceftriaxone , ceftazidime , meropenem and ertapenem . Nalidixic acid and pefloxacin served as predictors for ciprofloxacin non-susceptibility . In addition , for all available isolates , minimal inhibitory concentration ( MIC ) values for ciprofloxacin and azithromycin were determined by the E-test macro method ( bioMérieux , Marcy L'Etoile , France ) . Quality control was performed using Escherichia coli ( ATCC 25922 ) and Staphylococcus aureus ( ATCC 29213 ) . Multidrug resistance ( MDR ) was defined as co-resistance to ampicillin , chloramphenicol and trimethoprim-sulfamethoxazole [22] . For comparison with previously published literature , we used the superseded term ‘decreased ciprofloxacin susceptibility ( DCS ) ’ , defined as MIC-values of ≥0 . 12 mg/L and ≤0 . 5 mg/L , i . e . currently classified as ‘intermediate susceptibility' but associated with treatment failures or delayed treatment response [21] . Whole genome sequencing was carried out on all 65 Salmonella Typhi isolates and a selection of 26 Salmonella Paratyphi A isolates at the Plateforme de microbiologie mutualisée ( P2M ) from the Pasteur International Bioresources network ( PIBnet , Institut Pasteur , Paris , France ) . Short-read sequences from 30 previously published Salmonella Paratyphi A genomes were also included [23] . The run accession numbers and related metadata are detailed in S1 Table . Short-read sequences have been deposited to the European Nucleotide Archive ( ENA ) ( http://www . ebi . ac . uk/ena ) ( accession number PRJEB19906 ) . The MagNAPure 96 system ( Roche Diagnostics , Indianopolis , IN , USA ) was used for DNA extraction , libraries were prepared using the Nextera XT kit ( Illumina , San Diego , CA , USA ) and sequencing was done with the NextSeq 500 system ( Illumina ) . Read alignment , single nucleotide polymorphism ( SNP ) detection and maximum-likelihood phylogeny were carried out as described previously [23] . Sequence assembly was performed using SPAdes v . 3 . 6 . 0 [24] . Salmonella Typhi isolates were categorized as belonging to haplotype H58 based on the presence of the H58 specific single SNP ( T at nucleotide 252 on the gene glpA corresponding to STY2513 from GenBank accession no . AL513382 , Salmonella Typhi CT18 ) [25] . Genotyphi ( https://github . com/katholt/genotyphi ) was also used to classify Salmonella Typhi [26] . Salmonella Paratyphi A isolates were categorized as belonging to clade C5 ( the dominant clade in Cambodia ) based on the presence of the C5-specific SNP ( G to A at position 2 381 607 within the SPA_RS11495 gene ) [23] . The presence of antibiotic resistance genes was determined with ResFinder version 2 . 1 ( https://cge . cbs . dtu . dk/services/ResFinder/ ) [27] and plasmids with PlasmidFinder version 1 . 3 ( https://cge . cbs . dtu . dk/services/PlasmidFinder/ ) and pMLST version 1 . 4 ( https://cge . cbs . dtu . dk/services/pMLST-1 . 4/ ) [27 , 28] . The presence of mutations in the quinolone-resistance determining region of the DNA gyrase and topoisomerase IV genes ( gyrA , gyrB , parC and parE ) was assessed by the visual examination of sequences . Demographic , clinical and microbiological data were entered encoded into an Excel database that was created for this study ( Microsoft , Redmond , WA , USA ) . The code referring to the patient identity was only known by two medical doctors . Access to the database was restricted to these two medical doctors and patient identifiers were removed prior to analysis . Only the first isolate and associated clinical data for each unique patient was considered . Isolates recovered from a second blood culture drawn within two weeks after the initial one were considered as duplicates , whereas isolates recovered from a repeat blood culture more than two weeks after the initial one were considered as recurrences ( either relapse or repeat infections ) . Statistical analysis was done with Stata 12 ( Stata Corp . , College Station , TX , USA ) . Continuous variables are described by a median and interquartile range ( IQR ) . Comparisons between Salmonella Typhi and Salmonella Paratyphi were performed using a Mann-Whitney U test for continuous values and a Chi square test or Fisher exact test for proportions . A p-value of < 0 . 05 was considered significant . The study was conducted according to the principles expressed in the Declaration of Helsinki and involves use of information that was previously collected in the course of routine care . Ethical approval for the Microbiological Surveillance Study was granted by the Institutional Review Board of the ITM , the Ethics Committee of Antwerp University , and the National Ethics Committee for Health Research in Cambodia . This study and approval includes retrospective review of demographic and clinical data which are part of routine clinical history taking as recorded in the clinical chart . Between 1 January 2008 and 31 December 2015 193 Salmonella Paratyphi A isolates were retrieved from 190 patients and 65 Salmonella Typhi isolates from 64 patients . There were no Salmonella Paratyphi B or C isolates; sixty-two non-typhoidal Salmonella isolates were retrieved from 49 patients . The combined annual proportion of Salmonella Typhi and Salmonella Paratyphi A among all clinically significant organisms varied between 2 . 8% ( 2008 ) and 31 . 7% ( 2014 ) . During 2008–2012 , enteric fever was caused mostly by Salmonella Typhi ( 35 cases ) and only 12 cases of Salmonella Paratyphi A infection were identified ( Fig 1 ) . In 2013 however , a sharp increase in the number of Salmonella Paratyphi A cases was observed with a total of 72 unique cases . In 2014 and 2015 , the absolute annual number of Salmonella Paratyphi A cases decreased , but remained higher than for the period preceding 2013 . During this period , the number of Salmonella Typhi cases remained relatively stable . The majority of Salmonella Paratyphi A ( 64 . 7%; 123/190 ) and Salmonella Typhi infections ( 59 . 4%; 38/64 ) cases occurred during the dry season ( months November—April ) while there was an overall decreasing trend during the rainy season ( months June-October ) ( Fig 2 ) . Compared to the monthly percentage of total blood cultures sampled and clinically significant organisms found , the monthly combined percentage of Salmonella Typhi and Salmonella Paratyphi A was higher during the hot and dry season ( March—May ) and lower during the rainy season ( June-October ) . There were four cases of recurrent infections ( 37–48 days interval between first and recurrent infection ) , three with Salmonella Paratyphi A and one with Salmonella Typhi; whole genome sequence data was available for three of the four pairs . SNP analysis of the paired isolates revealed that they differed by only two or three SNPs and the isolate pairs formed discrete clusters within the trees ( S1 and S2 Figs ) . Available epidemiological , clinical and radiographic findings of all enteric fever patients are listed in Table 1 . Eleven out of 189 ( 5 . 8% ) Salmonella Paratyphi A patients had a known co-morbidity , i . e . HIV ( n = 7 ) , Diabetes Mellitus type 1 or 2 ( n = 3 ) and leukemia ( n = 1 ) . Of 63 Salmonella Typhi patients also nine ( 14 . 3% ) had a known co-morbidity , i . e . HIV ( n = 7 ) and Diabetes Mellitus type 1 ( n = 2 ) . All but one HIV patient were on antiretroviral therapy at time of presentation . There were 11 patients known to have hepatitis B-positive serology ( 8 Salmonella Paratyphi A , 3 Salmonella Typhi ) . At least five could be classified as inactive chronic carriers and two had signs of chronic liver disease on ultrasound . Patients with a Salmonella Paratyphi A infection were more likely to be living in Phnom Penh compared to Salmonella Typhi patients ( 81 . 5% ( 154/189 ) vs . 60 . 3% ( 38/63 ) ; p = 0 . 001 ) but the median duration of illness at presentation was the same ( four days ) . Eleven ( 17 . 5% ) patients with typhoid fever and 19 ( 10 . 1% ) with paratyphoid fever were hospitalized , with no statistically significant difference between the two groups ( p = 0 . 119 ) . Reasons for hospitalization included sepsis , persistent fever despite antibiotic therapy , dizziness due to low blood pressure , suspicion of dengue hemorrhagic fever ( thrombocytopenia ) and dysregulated diabetes mellitus . There were no deaths nor complications noted . The most frequently reported symptoms in all enteric fever patients together were fever in 229 patients ( 99 . 6% ) , headache in 138 ( 62 . 4% ) and abdominal pain in 143 ( 62 , 2% ) . Presence or absence of classic enteric fever signs such as a coated tongue and rose spots were infrequently mentioned in clinical files and therefore not evaluated . Despite the non-specific symptoms , physicians noted typhoid fever in their differential diagnosis upon admission in 67 . 7% ( 136/201 ) of the cases . There were no statistically significant differences in individual symptoms between typhoid and paratyphoid fever patients , but patients infected with Salmonella Typhi had a slightly but significantly lower median systolic blood pressure ( 107 mm Hg vs . 113 mm Hg; p = 0 . 036 ) . Treatment was not systematically recorded for all patients as many were lost to follow-up . Various antimicrobial regimens were used , but ceftriaxone ( 2g I . V . , once daily ) was given most frequently as empirical treatment and as monotherapy , normally for 10–14 days . In case of de-escalation to oral antibiotics , this concerned mostly ciprofloxacin ( 500 mg , twice daily ) and next amoxicillin/clavulanate ( 625 mg , three times a day ) . In case of persistent fever while awaiting blood culture results , amikacin was occasionally added to ceftriaxone . The laboratory parameters of enteric fever patients on admission are summarized in Table 2 . Common laboratory abnormalities for enteric fever patients included moderately risen transaminase levels in 133 patients ( 70 . 7% ) , an elevated CRP in 53 patients ( 94 . 6% ) and eosinopenia in 49 patients ( 90 . 7% ) . Hematological abnormalities were uncommon; the leukocyte count was normal in 88 . 1% of all patients . Compared to Salmonella Paratyphi A infected patients , Salmonella Typhi patients had slightly but significantly higher median values for leukocytes ( 6 . 8 x 109/L vs . 6 . 3 x 109/L; p = 0 . 035 ) and C-reactive protein ( CRP ) ( 47 . 0 mg/L vs . 36 mg/L; p = 0 . 034 ) , with more presence of leukocytosis ( 10 . 0% vs . 2 . 2% p = 0 . 015 ) . Salmonella Paratyphi A infection was associated with a higher monocyte count compared to Salmonella Typhi ( 0 . 48 x 109/L vs . 0 . 33 x 109/L ) , but this difference did not reach statistical significance ( p = 0 . 069 ) . Both anaerobic and aerobic blood cultures showed signs of growth after a median of two days ( IQR 2–3 ) for all enteric fever patients . In 221 enteric fever patients a pair of one aerobic bottle and one anaerobic bottle was sampled , and in 180 of those cases ( 81 . 4% ) both bottles grew . In the other cases ( growth in only a single bottle ) , it was the aerobic bottle which grew in nearly two-thirds ( 65 . 9%; 27/41 ) of pairs . Reported antibiotic exposure in the two weeks before blood culture sampling was not associated with a difference in the median days to growth for both aerobic bottles and anaerobic bottles . In total , 183 out of 190 ( 96 . 3% ) unique Salmonella Paratyphi A isolates and all 64 unique Salmonella Typhi isolates recovered during the study period were available for antibiotic susceptibility testing ( Table 3 ) . For Salmonella Typhi , there was a significant decrease ( p = <0 . 001 ) in the proportion of isolates that were MDR over the 8-year period ( 62 . 9% vs . 17 . 2% ) while decreased susceptibility to ciprofloxacin remained at nearly 100% ( 96 . 9%; 62/64 ) during the entire period . For Salmonella Paratyphi A the emergence of DCS was noted as of 2015 ( S1 Table ) . In this year 19 out of 36 unique isolates ( 52 . 8% ) showed DCS . Overall , Salmonella Typhi was significantly more likely to be MDR and more likely to display DCS than was Salmonella Paratyphi A ( 42 . 2% vs . 0 . 0%; p = <0 . 001 and 96 . 9% vs . 11 . 5%; p = <0 . 001 respectively ) . Of note , for both serovars no ciprofloxacin resistance was reported and the presence of nalidixic acid and pefloxacin resistance were excellent predictors of DCS except in case of one isolate with a single gyrB mutation ( Table 4 and S1 Table ) . Furthermore , no resistance against third-generation cephalosporins , carbapenems or azithromycin was found . All but one of the Salmonella Typhi isolates were confirmed to be of the H58 haplotype ( recently reclassified as the 4 . 3 . 1 genotype ) , with only 27 out of 63 ( 42 . 9% ) unique H58 isolates displaying MDR but 98 . 4% ( 62/63 ) displaying DCS . The only non-H58 isolate belonged to genotype 3 . 2 . 1 and was pan-susceptible . All of the Salmonella Paratyphi A isolates with DCS belonged to the C5 clade . Most frequently observed in both Salmonella Typhi and Salmonella Paratyphi A with DCS was the gyrA mutation leading to serine-to-phenylalanine substitution at codon 83 ( Ser83Phe ) ( Table 4 ) . These isolates showed DCS and resistance to pefloxacin and nalidixic acid . There was one Salmonella Typhi isolate with a double gyrA mutation and one with a gyrB mutation . The latter mutation ( serine-to-phenylalanine substitution at codon 464 ( Ser464Phe ) ) was associated with intermediate susceptibility to nalidixic acid and DCS . No mutations in ParC or ParE were observed . Various resistance genes ( blaTEM-1B , catA1 , sul1 , sul2 , dfrA7 , tet ( B ) , strAB ) were detected in MDR Salmonella Typhi which were associated with the presence of an incHI1 PST6 plasmid ( S1 Table ) . The present study describes the clinical and microbiological aspects of enteric fever in a large group of patients attending an adult hospital in Cambodia with several interesting results . First , and in line with some other Asian countries , a clear increase was noted in the proportion of Salmonella Paratyphi A infections . This can largely be explained by a community outbreak which occurred in 2013 , but the number of cases has remained high also in succeeding years . A recent genetic study on the Cambodian Salmonella Paratyphi A outbreak isolates showed that these isolates belong to a clade that has been circulating in the South-East Asian region already for decades [23] . Further , no indications were found for significant genetic changes within the Cambodian isolates suggesting that environmental and/or behavioral factors are more likely to play a role . Patients with paratyphoid fever were significantly more likely than typhoid fever patients to be residents of Phnom Penh , which suggests that exposure to the bacterium is more common in the city . Previous studies from Nepal and Indonesia have linked paratyphoid fever to recent immigration into the capital and consumption of street food [29 , 30] . Increased dependency on street food has been linked to urbanization , and Phnom Penh is rapidly expanding . As part of urban expansion , some of the city’s peri-urban lakes have been filled with sand to reclaim land [31] . These lakes are estimated to receive 80% of the city’s ( untreated ) waste water and act as a natural sewage treatment through aquatic cultivation of vegetables of which some are consumed raw [32] . Reductions in the size of these lakes could have led to higher concentrations of fecal sludge and bacteria in the remaining water and increased flooding in the city [33] . The majority of enteric fever cases occurred in the dry season . During this season more vegetables are harvested and it is also known for an increased availability of snails and clams ( bivalve shellfish ) , due to low water levels in rivers . Shellfish are known to be able to concentrate micro-organisms from water . They are popular snacks which are dried outside rather than boiled during the dry season . In addition , this season coincides with the two most important festivities of the year , the Chinese and Khmer New Year which are associated with increased migration in and out of the city and longer storage duration of food . Last , high daily temperatures may lead to more indiscriminate intake of water and ice cubes . These factors are currently being explored more in-depth . Second , based on individual symptoms at presentation , infections caused by Salmonella Typhi vs . Salmonella Paratyphi A were similar and indistinguishable , which is in line with other studies from Asia [3 , 4] . For both serovars , the median pulse rates at presentation ( 106 and 105 beats/minute ) were high . This has been noted before in children with enteric fever [34] . No complications or deaths occurred which could be ascribed to a prompt start of antibiotic therapy and an early presentation . The latter can also explain the absence of relative bradycardia and the low rate of diarrhea observed which are typically seen in later stages of the disease [35] . In general , laboratory abnormalities were non-specific and leukocyte counts were normal in 87 . 4% of all enteric fever patients which was also found by others [36] . Higher leukocyte counts and CRP values were found among Salmonella Typhi-infected patients , suggesting a more severe infection . This is in line with a recent human challenge study , which found that a challenge with Salmonella Paratyphi A in healthy volunteers resulted in a milder disease profile ( high rates of afebrile bacteremia ) than that observed following typhoid challenge [37] . Some differences in presentation were noted when comparing these results to travelers infected with the same Salmonella Paratyphi A C5 strain returning from Cambodia to France . In the latter study , the majority of patients did have diarrhea ( 70 . 6% ) and were hospitalized ( 86% ) [14] . This difference may be due to other waterborne or oral-fecal infections travelers frequently contract and/or less financial constrains related to hospital admission [2] . Clinical presentation in the present study also differed from typhoid fever patients in African countries where higher rates of severe complications and mortality are observed [38] . As the same H58 haplotype of Salmonella Typhi is dominant in Asia and in eastern Africa , differences could perhaps be explained by timely access to health care and adequate treatment as well as to host-related factors including underlying co-morbidities like malnutrition . It has been suggested that isolates of the H58 lineage and MDR strains in general are associated with increased virulence and pathogenicity [39–41] . Therefore the results regarding the clinical presentation and severity of cases as described here , might not be applicable to areas where other lineages dominate . As a third observation , antibiotic resistance trends were very different for the two serovars . While 42 . 2% of the unique Salmonella Typhi isolates displayed MDR , none of the Salmonella Paratyphi A isolates did . DCS was present in nearly all Salmonella Typhi isolates , but only emerged in Salmonella Paratyphi A from 2015 . The rapid increase of DCS in Salmonella Paratyphi during that year is of concern as ciprofloxacin is the treatment of choice for uncomplicated enteric fever . Fourth , although all but one Salmonella Typhi isolates were found to belong to the globally dominant H58 haplotype , more than half were not associated with MDR and the proportion of ( plasmid-mediated ) MDR Salmonella Typhi significantly decreased during the study period . This trend has previously been noted in India , Nepal and neighboring country Vietnam [42–44] , but contrasts with a recent study on Salmonella Typhi isolates from rural Cambodia where 89% of the H58 isolates displayed the MDR phenotype [45] . The re-emergence of susceptibility might result from a lack of antibiotic pressure since fluoroquinolones have become the preferred treatment both in community and hospital settings in Phnom Penh . No resistance against ceftriaxone nor against azithromycin was observed . However , reports on extended spectrum beta-lactamases ( ESBL ) positive and azithromycin resistant Salmonella spp . isolates are emerging globally including one from the same hospital on Salmonella enterica serovar Choleraesuis [20 , 46 , 47] underlining the importance of continued microbiological surveillance . Last , molecular analysis of isolates from three patients with a recurrent infection showed relapse was more likely than re-infection with isolate pairs differing only 2–3 SNPs which can occur during the period of persistence within the human body and suggests relapse rather than re-infection [48] . Relapse is estimated to occur in around 5–10% of enteric fever cases usually two to three weeks after the resolution of fever [5] . In our study , a blood culture confirmed recurrence was witnessed only in 4 out of 254 cases ( 1 . 6% ) . It is likely that other recurrent infections have been missed , partly due to the different medical systems that co-exist in Cambodia in which patients readily switch from one healthcare provider to another , especially if symptoms persist . This study has several limitations . First , the hospital-based setting precluded generalization to patients whose symptoms were not severe enough to seek medical care in a hospital or clinic . Second , the study concerned mostly adults and therefore findings might not be equally applicable to a pediatric population . Third , the study was retrospective in nature; not all clinical charts were available for review and clinical record keeping was variable among different clinicians . It was not possible to reliably estimate time to defervescence . Despite these limitations , this is one of the largest and most comprehensive descriptive studies on Salmonella Paratyphi A infections so far which is relevant given the global increase in Salmonella Paratyphi A infections . The data do not represent one single hospital , but several clinics located in different districts of the city . Some of these clinics have reduced rates for the poor and during the study period all blood cultures were provided for free . This helped to overcome some of the bias associated with a hospital based study . The high proportion of Salmonella Typhi and Paratyphi A recovered from blood cultures indicated that enteric fever is a very frequent disease in Phnom Penh . While efforts are made to increase the microbiological diagnostic capacity in the country , a rapid test for invasive Salmonella infections would be a welcome tool for fast and reliable diagnosis . It could increase knowledge on the burden of disease in the community and could replace the flawed Widal test that is still frequently used . As the current Salmonella Typhi vaccine provides no to very little protection against Salmonella Paratyphi A , the development of an effective Salmonella Paratyphi A vaccine should be promoted , pending improved water quality and sanitation [49] . Enteric fever is frequent in Phnom Penh and the proportion of cases due to Salmonella Paratyphi A has increased . Studies to investigate risk factors and possible transmission routes are urgently needed to advise public health interventions . No MDR was observed for Salmonella Paratyphi A but DCS increased rapidly . DCS remained highly prevalent in Salmonella Typhi while MDR rates have declined . Ceftriaxone and azithromycin remain highly active in vitro but continued surveillance is imperative to monitor resistance .
Enteric fever is a bloodstream infection caused by the bacteria Salmonella Typhi or Salmonella Paratyphi A , B , or C . It is common in low resource settings and linked to poor water quality and sanitation . The disease is also endemic in Cambodia and since 2013 there has been a sharp increase in the number of Salmonella Paratyphi A infections . We sought to compare the clinical phenotypes and antibiotic susceptibilities of Salmonella Paratyphi A infections with those of Salmonella Typhi infections in this setting . We retrospectively collected demographic , clinical and laboratory data from clinical charts of 254 patients with a blood culture positive for enteric fever . We also assessed antibiotic susceptibility patterns and sequenced the genome of a subset of isolates . We found that since 2013 the majority of enteric fever cases are caused by Salmonella Paratyphi A which increasingly shows decreased susceptibility to the antibiotic ciprofloxacin , the current first line treatment . In contrast , in Salmonella Typhi a re-emergence of susceptibility for the former first line antibiotics of ampicillin , co-trimoxazole and chloramphenicol was observed . Presenting symptoms of Salmonella Typhi and Salmonella Paratyphi A were identical , minor differences were observed in laboratory parameters .
[ "Abstract", "Introduction", "Materials", "and", "methods", "Results", "Discussion", "Conclusion" ]
[ "medicine", "and", "health", "sciences", "body", "fluids", "pathology", "and", "laboratory", "medicine", "pathogens", "geographical", "locations", "microbiology", "salmonella", "typhi", "salmonellosis", "bacterial", "diseases", "antibiotic", "resistance", "signs", "and", "symptoms", "enterobacteriaceae", "pharmacology", "bacteria", "bacterial", "pathogens", "infectious", "diseases", "antimicrobial", "resistance", "medical", "microbiology", "microbial", "pathogens", "salmonella", "enterica", "salmonella", "people", "and", "places", "diagnostic", "medicine", "blood", "asia", "anatomy", "fevers", "physiology", "microbial", "control", "biology", "and", "life", "sciences", "cambodia", "organisms" ]
2017
The clinical and microbiological characteristics of enteric fever in Cambodia, 2008-2015
Circadian rhythms modulate the biology of many human tissues , including brain tissues , and are driven by a near 24-hour transcriptional feedback loop . These rhythms are paralleled by 24-hour rhythms of large portions of the transcriptome . The role of dynamic DNA methylation in influencing these rhythms is uncertain . While recent work in Neurospora suggests that dynamic site-specific circadian rhythms of DNA methylation may play a role in modulating the fungal molecular clock , such rhythms and their relationship to RNA expression have not , to our knowledge , been elucidated in mammalian tissues , including human brain tissues . We hypothesized that 24-hour rhythms of DNA methylation exist in the human brain , and play a role in driving 24-hour rhythms of RNA expression . We analyzed DNA methylation levels in post-mortem human dorsolateral prefrontal cortex samples from 738 subjects . We assessed for 24-hour rhythmicity of 420 , 132 DNA methylation sites throughout the genome by considering methylation levels as a function of clock time of death and parameterizing these data using cosine functions . We determined global statistical significance by permutation . We then related rhythms of DNA methylation with rhythms of RNA expression determined by RNA sequencing . We found evidence of significant 24-hour rhythmicity of DNA methylation . Regions near transcription start sites were enriched for high-amplitude rhythmic DNA methylation sites , which were in turn time locked to 24-hour rhythms of RNA expression of nearby genes , with the nadir of methylation preceding peak transcript expression by 1–3 hours . Weak ante-mortem rest-activity rhythms were associated with lower amplitude DNA methylation rhythms as were older age and the presence of Alzheimer's disease . These findings support the hypothesis that 24-hour rhythms of DNA methylation , particularly near transcription start sites , may play a role in driving 24-hour rhythms of gene expression in the human dorsolateral prefrontal cortex , and may be affected by age and Alzheimer's disease . Circadian rhythms—intrinsic 24-hour biological rhythms—have a major impact on the molecular biology , physiology , and function of many human tissues , including the human brain , where they have an important influence on neurological diseases like dementia , epilepsy , and stroke . In model organisms , circadian rhythms are generated in neurons of the suprachiasmatic nucleus ( SCN ) by a transcription-translation feedback cycle involving a set of evolutionarily conserved “clock” genes [1] . Similar clocks are present in other tissues [2] , including neocortex . These tissue clocks are entrained by the SCN and drive circadian rhythms of tissue physiology , in part through 24-hour cycles of histone modification and gene expression involving a sizeable subset of the transcriptome [3] that varies from tissue to tissue [4] . Whether circadian rhythms of DNA methylation are important for maintaining or modulating circadian rhythms of gene expression in mammalian tissues is uncertain . Recent work in Neurospora suggests that circadian rhythms of DNA methylation may play a role in the fungal molecular clock [5] . Moreover , recent studies demonstrated the importance of non-circadian plastic DNA methylation in mediating the long term effect of light on changes in the period of the intrinsic circadian clock in mice [6] , and in mediating the effect of photoperiod on endocrine function in hamsters [7] . However , 24-hour rhythms of promoter region DNA methylation were not found in a study of mouse suprachiasmatic nucleus [6] or in a recent study of mouse liver [8] . To our knowledge , 24-hour rhythms of DNA methylation and their relationship to circadian rhythms of gene expression have not been demonstrated in any mammalian tissue , including human brain . In fact , there are few studies concerning epigenetic mechanisms influencing circadian rhythms of gene expression in human neocortex . This is an important gap because circadian rhythms exert an important effect on neurological diseases like dementia and epilepsy , as well as on cognition and voluntary human behavior , and the neocortex is central to all of these processes . Understanding and potentially therapeutically manipulating the circadian influence on human neurological diseases and behavior will depend on elucidating their genetic and epigenetic basis in human neocortical tissues . The dorsolateral prefrontal cortex in particular plays a key role in several cognitive domains [9] that show considerable circadian fluctuation , as well as in diseases like schizophrenia [10] . Moreover , significant 24-hour rhythms of gene expression have been demonstrated in human dorsolateral prefrontal cortex [11] . Because the circadian regulation of gene expression varies between tissues and species , there is no perfect substitute for directly studying genetic and epigenetic mechanisms underlying circadian rhythms in human neocortical tissue . However , progress in examining circadian rhythms of epigenetic modification in human neocortex has been limited by difficulties in obtaining large sets of human neocortical specimens at a wide range of circadian times suitable for epigenetic analysis . The overall aim of this study was to test the hypothesis that 24-hour rhythms of DNA methylation exist in human dorsolateral prefrontal cortex , and play a role in 24-hour rhythms of RNA expression . To do so , we determined DNA methylation levels in post-mortem human dorsolateral prefrontal cortex samples from 738 community-dwelling organ donors at 420 , 132 autosomal DNA methylation sites across the genome . We considered DNA methylation levels as a function of time of death , parameterized these data using cosine functions , and determined global statistical significance by permutation . We then related 24-hour rhythms of DNA methylation to local gene landmarks , to parallel rhythms of RNA expression determined by RNA sequencing , and to ante-mortem behavioral rhythms measured by actigraphy . We found evidence for widespread 24-hour rhythms of DNA methylation whose timing was closely related to the position of specific DNA methylation sites relative to gene landmarks . Moreover , we found that genomic regions proximate to transcription start site were enriched in high amplitude rhythmic DNA methylation sites , and that the timing of rhythmicity at these sites was time-locked to rhythms of nearby gene expression , with the nadir of methylation preceding peak transcript expression by 1–3 hours . We demonstrated an association between the robustness of ante-mortem rest-activity rhythms and the amplitude of rhythms of DNA methylation . Finally , we identified effects of age , sex , and Alzheimer's disease on the amplitude and phase of rhythms of DNA methylation . We analyzed postmortem human neocortical DNA methylation data from 738 individuals participating in 2 longitudinal cohort studies of aging – the Religious Orders Study ( ROS ) and the Rush Memory and Aging Project ( MAP ) . All ROS and MAP participants are organ donors and hence time of death is well documented . Characteristics of the study subjects are shown in Table 1 . DNA methylation levels at 420 , 132 DNA methylation sites spanning all 22 autosomes was generated using the Illumina Infinium HumanMethylation450 Bead Chip assay ( Illumina , San Diego , CA ) . Prior to further analyses , we accounted for the effects of age , sex , presence/absence of dementia , source cohort , post-mortem interval , and batch effects by regressing the methylation data against these factors and taking the residuals , which were then normalized to the mean and standard deviation of all 738 subjects . These normalized residuals represent the relative methylation at each site adjusted for these covariates , and were used for all further analyses , except where specifically indicated . To identify temporal patterns in DNA methylation at each of the sites , we considered DNA methylation as a function of clock time of death , with each subject contributing a single data point to a time series spanning 24 hours . Visual inspection of these data revealed that some sites were clearly rhythmic ( Figure 1 A–B ) while others were clearly not ( Figure 1 C–D ) . Based on visual inspection of these data , and in keeping with prior work examining 24-hour rhythms of gene expression in neocortical tissue [11] , we then modeled these data using cosine curves . We parameterized these data using functions of the form M = m+ ( β1 ) *cos ( t−βA ) . . [Eq1] where m is the mesor ( the mean value considering all time points ) , β1 is the amplitude of oscillation , βA is the timing of the peak , and t is the time of death . We calculated the proportion of variance explained by the fit cosine model at each DNA methylation site ( Supporting File 1 ) . We first carried out a series of analyses to identify global patterns of rhythmicity . To quantify the probability that the observed data could have occurred by chance alone , we performed a series of analyses comparing the observed data to 10 , 000 permuted null datasets generated by randomly shuffling the times of death in our data while preserving the correlation between DNA methylation sites . We fit cosine curves at each of the 420 , 132 sites in each null dataset , calculated the proportion of variance at each site explained by the fit cosine curve , and determined the time of the methylation nadir ( βA-π ) . We then carried out four analyses comparing the observed to the 10 , 000 permuted null datasets: 1 ) We calculated the mean total proportion of variance collectively explained by the fit cosine curves in each of the 10 , 000 permuted null datasets and in the observed data , and determined the proportion of null datasets in which this was as large or larger than in the observed data . In none of the 10 , 000 permuted null datasets was the mean proportion of variance explained by cosine curves greater than in the observed data , indicating that the average rhythmicity of the 420 , 132 sites is greater than expected by chance alone , and the probability of the observed data being due to chance alone is p<0 . 0001 ( Figure 2A ) . 2 ) We repeated the same for the median total proportion of variance explained . As above , in none of the 10 , 000 permuted null datasets was the median proportion of variance explained by cosine curves greater than in the observed data , indicating p<0 . 0001 ( Figure 2B ) . 3 ) We used the Wilcoxon rank-sum test to compare the observed distribution of proportions of variance explained by cosine curves to an empiric null distribution generated by taking the mean of the corresponding vectors from the 10 , 000 permuted null datasets . The observed distribution was significantly greater than the empiric null distribution ( W = 91342066816 p<2 . 2×10−16 by the Wilcoxon rank-sum test ) . 4 ) We compared the distribution of methylation nadir times in the observed and permuted null datasets ( Figure 2C ) . As expected , in the permuted null datasets , the methylation nadirs were uniformly distributed . By contrast , the methylation nadirs showed significant non-random clustering in the observed data ( H2 = 10449 . 1; p<2 . 2×10−16 by the Rao test for equality of dispersions ) . Considering these four analyses together , we concluded that the probability of the 24-hour rhythmicity seen in the observed data occurring by chance was exceedingly small . DNA methylation is thought to play a role in regulating gene transcription . Therefore , we examined the relationship between the physical position of DNA methylation sites relative to transcription start sites and the observed parameters of rhythmicity such as amplitude and phase ( Figure 3 ) . First , we considered all interrogated DNA methylation sites within 20 kb of any GENCODE v14 annotated transcription start site , and plotted the temporal distribution of methylation nadir times in 500 bp bins ranging from −20 kb to +20 kb ( Figure 3A ) . Visual inspection revealed an association between physical position of a DNA methylation site relative to the nearest transcription start site , and the timing of the nadir of methylation , with sites closest to the transcription start site being most likely to reach their methylation nadir in the early morning ( ∼5:30 ) while those upstream and downstream being more likely to reach their methylation nadir in the evening ( ∼20:30 ) . To formally test this , we stratified DNA methylation sites into those between −20 kb and −1 kb of transcription start sites , those between −1 kb and +1 kb of transcription start sites , and those within +1 kb and +20 kb of transcription start sites ( Figure 3B ) . The temporal distributions of methylation nadir times in these three groups differed significantly ( H1 = 7136 . 9; p<2 . 2×10−16 by the Rao test for equality of polar direction ) . The higher the amplitude of cycling , the more likely it is to be biologically significant . We therefore examined in more detail the subset of DNA methylation sites with the highest amplitude of cycling . We defined a site as high amplitude if the fit cosine curve had a peak-to-trough amplitude of rhythmicity greater than 10% of the mean value of methylation . We examined the distribution of such high-amplitude sites by dividing the 20 kb upstream and downstream of each transcription start site into 500 bp bins as above , and we determined the proportion of high amplitude DNA methylation sites in each bin . High-amplitude DNA methylation sites were enriched in the 1000 kb around transcription start sites compared to other genomic regions ( χ2 64712 . 6 , p<2 . 2×10−16; Figure 3C ) . We then repeated the above analyses , except that rather than dividing the genome into bins based on position relative to transcription start sites , we incorporated information about other gene landmarks and divided the genome into 9 bins: regions within 2 kb upstream of transcription start site , in the 5′UTR , in the 1st exon , in the 1st intron , in other exons , in other introns and in the 3′UTR of protein coding transcripts; regions in or within 2 kb upstream of non-protein coding transcripts; and intergenic regions ( defined as all other genomic regions ) . Sites in the 2 kb upstream of transcription start sites , and in the 5′UTR , 1st exon , and 1st intron were most likely to reach their methylation nadir in the early morning , while those in other exons/introns , the 3′UTR , noncoding transcripts , and intergenic regions were most likely to peak in the evening ( H1 = 14683 . 8; p<2 . 2×10−16 by the Rao Test for equality of polar direction; Figure 4A–B ) . Moreover , the 2 kb upstream of transcription start sites , the 5′UTR , and the 1st exon were relatively enriched in sites with relative high amplitude oscillations as described above ( χ2 51250 . 8 , p<2 . 2×10−16; Figure 4C ) . DNA methylation is hypothesized to play a role in regulating gene transcription . In a subset of 536 participants ( Table S1 ) , we generated RNA sequencing data from the same tissue blocks used to generate the DNA methylation data , quantifying the expression level of GENCODE v14 annotated transcripts containing or within 2 kb of high amplitude DNA methylation sites , and detectible in at least 10% of our samples . A total of 69 , 605 GENCODE transcripts spanning 15 , 091 genes containing or near 20 , 656 high amplitude DNA methylation sites met these criteria . As for the methylation data , we considered RNA abundance for each transcript for each sample as a function of time of death and fit cosine curves . From these fit curves , we determined the timing of peak RNA abundance ( Supporting File 2 ) . We divided genomic regions into 7 bins based on gene landmarks as above , excluding non-coding transcripts and intergenic regions , and repeated the above analyses except that rather than considering the absolute clock time of the nadir of methylation at each site , we considered the timing of the nadir of methylation relative to timing of peak RNA expression of the associated transcript . Where a DNA methylation site was associated with more than 1 transcript , the circular mean of the peak times of all associated transcripts was taken , and the timing of the nadir of methylation was taken relative to this time . There was a significant clustering of nadir methylation times relative to the timing of peak RNA abundance for DNA methylation sites in the 2 kb upstream of the transcription start site , the 1st exon , the 5′UTR , and to a lesser extent the 1st intron ( p = 1 . 7×10−42 , p = 8 . 5×10−29 , p = 2 . 7×10−29 , and p = 6 . 2×10−13 respectively by Rayleigh's test ) , with the nadir of methylation preceding the timing of peak RNA abundance by 1–3 hours for sites 2 kb upstream of the TSS , in the 5′UTR , in the 1st exon , and in the 1st intron ( Figure 5 ) . By contrast , no such clustering was seen for sites in other exons , other introns , and the 3′UTR ( p>0 . 05 for all ) . A number of clinical factors such as age [12] , sex [13] , [14] , and presence of Alzheimer's disease [15] have been described to impact 24-hour rhythms . Moreover , dorsolateral prefrontal cortex molecular 24-hour rhythms may plausibly reflect or impact observed behavioral 24-hour rhythms . We therefore examined the impact of these factors on the amplitude and timing of 21 , 282 high amplitude DNA methylation sites ( including intergenic sites ) . We assessed the effect of these variables on the parameters of DNA methylation rhythmicity by considering extended cosine models of the form M = m+ ( β1+β2x ) *cos ( t−βA−βBx ) [Eq3] where x represents high vs . low age , male vs . female sex , present vs . absent Alzheimer's disease , or high vs . low behavioral rhythmicity , β2 reflects the effect of x on amplitude , and βB reflects the effect of x on phase . Female sex , higher age , and absence of dementia were associated with an earlier average phase of rhythms of methylation ( Figure 6 ) while the presence of Alzheimer's disease , female sex , higher age , and lower ante-mortem actigraphic rhythmicity were associated with a lower average amplitude of methylation rhythms ( Figure 7 ) . Using data from 420 , 132 DNA methylation sites spanning all 22 autosomes from 738 post-mortem human dorsolateral prefrontal cortex samples , and associated RNA sequencing data in a subset of 536 of these , this study provided evidence of 24-hour rhythms of DNA methylation whose parameters were closely related to the position of DNA methylation sites relative to gene landmarks . In particular , the timing of DNA methylation rhythms at sites proximate to transcription start sites had a characteristic phase-relationship with rhythms of RNA expression such that the nadir of methylation preceded the peak of expression by 1–3 hours . Moreover , gene regions proximate to the transcription start site were relatively enriched in DNA methylation sites with higher amplitude oscillations . In addition , higher amplitude rhythms of DNA methylation were associated with more robust ante-mortem rest-activity rhythms measured by actigraphy . Finally , age , sex , and the presence of Alzheimer's disease were significantly associated with characteristic differences in the amplitude and timing of 24-hour rhythms of DNA methylation . Taken together , these results suggest that cyclical alterations in DNA methylation status , particularly of DNA methylation sites proximate to transcription start sites , may influence 24-hour rhythms of RNA expression . Moreover , they raise the possibility that that altered 24-hour rhythms of DNA methylation may be an important mediator of the effects of age , sex , and dementia on physiological and behavioral 24-hour rhythms . That 24-hour rhythms of histone acetylation and chromatin conformational change play an important role in driving and modulating 24-hour cycles expression of clock and clock output genes in at least some model mammalian organisms is established [3] , [16] , [17] . The role of DNA methylation in mammalian circadian rhythms is less clear . While DNA methylation is thought to be a relatively stable epigenetic modification , recent work has shown it to be much more dynamic than previously thought [18] , [19] . A role for site-specific cycles of clock gene methylation in modulation of circadian rhythms has recently been established in Neurospora [20] . Moreover , others have recently demonstrated a role for non-circadian plasticity of DNA methylation in mediating the effect of light on the period of the intrinsic circadian clock in mice [6] , and in modulating the endocrine response to changes in photoperiod in hamsters [7] . However , to our knowledge , site-specific 24-hour rhythms of DNA methylation have not to date been demonstrated in any mammalian tissue , including human neocortex . Moreover , while 24-hour rhythms of global DNA methylation have been reported in human white blood cells [21] , the site-specific temporal architecture underlying this observed phenomenon was unclear , as was the extent to which similar rhythms can be found in non-blood tissues . In this study of 420 , 132 CpG sites distributed across all 22 autosomes , we found evidence for significant 24-hour rhythmicity of DNA methylation in human dorsolateral prefrontal cortex with a temporal organization and amplitude exceedingly unlikely to be attributable to chance alone . Our results differ somewhat from recent studies of mouse liver [8] and suprachiasmatic nucleus [6] , which found no significant 24-hour rhythms of promoter-region DNA methylation . There are several potential reasons for this discrepancy . First , there is a fundamental difference of species ( human vs . mouse ) and tissue ( neocortex vs . liver/suprachiasmatic nucleus ) . Second , the present study examined methylation across the 24-hour cycle , whereas these other recent studies compared methylation levels at a small number of discrete circadian times , which would have missed rhythmic DNA methylation sites whose acrophase and nadir were out of phase with the sampling times . Third , the present study examined individual DNA methylation sites on a genome-wide scale , including all gene regions , and stratified by location relative to gene landmarks , whereas these other recent studies examined only promoter-region DNA methylation sites . Finally , the present study had a much larger number of tissue samples ( n = 738 ) , allowing greater statistical power to detect rhythmicity . Our data support a differential functional role for 24-hour rhythms of DNA methylation depending on the location of the DNA methylation site . Regions proximate to transcription start sites ( e . g . within 2 kb upstream of the transcription start site , the 5′UTR , the 1st exon , or the 1st intron ) were particularly highly enriched for high amplitude rhythmic DNA methylation sites , and the timing of methylation rhythms at these sites was time-locked to rhythms of local gene expression , with the timing of the nadir of methylation preceding the peak of gene expression by 1–3 hours . This suggests that 24-hour rhythms of DNA methylation at sites proximate to transcription start sites may play a particular role in regulating the transcription of rhythmic transcripts . This is in keeping with the hypothesis that methylation sites near the transcription start site are most likely to play a role in regulating transcription , while those elsewhere may play non-transcription related roles [22] . Meanwhile , the clustering of methylation nadir times between 18:00 and 22:00 for sites removed from transcription start sites is in concordance with previous work in mouse liver showing a global decrease in DNA methylation in the later afternoon [23] . In this study , men had relatively later rhythms of DNA methylation than women . This is in keeping with our previous work showing that men have 24-hour rhythms of neocortical clock gene expression [24] and activity [25] that are relatively delayed compared to females . We also observed in our data that greater age was associated with relatively earlier and lower amplitude rhythms of DNA methylation and that the presence of pathologically confirmed Alzheimer's disease was also associated with relatively lower amplitude and delayed rhythms of rhythms of DNA methylation . This is concordant with previous work showing a relative phase advance of several measures of circadian rhythmicity with increasing age [25] [12] , and a relative decrease in amplitude of other measures of circadian rhythmicity in the context of dementia [15] , [26] . Finally , in the subset of 134 individuals who had actigraphic recordings prior to death , those individuals who had less robust 24-hour rhythmicity on their actigraphic recordings also had on average somewhat attenuated rhythms of DNA methylation at the time of death , supporting a link between 24-hour rhythms of neocortical DNA methylation , and 24-hour rhythms of behavior . As this study was cross-sectional in nature , the causal relationship between age , dementia , dorsolateral prefrontal cortex 24-hour DNA methylation rhythms , and behavioral 24-hour rhythms cannot be determined from these data alone , and further studies , particularly in animal models of aging and neurodegeneration , will be needed . Moreover , whether these differences are fundamentally due to differences a the level of the dorsolateral prefrontal cortex , or reflect differences in the function of the central circadian pacemaker , or even differences in confounding environmental exposures cannot be deduced from our data . This study has a number of methodological strengths . We assessed DNA methylation and RNA expression on a genome-wide scale and in all gene regions , allowing comparison of the circadian properties of DNA methylation sites in the promoter region , 5′UTR , exons , introns , 3′UTR , and intergenic regions . Moreover , we measured DNA methylation and RNA expression from the same samples , allowing the inference of temporal correlations . Also , the large number of subjects and high temporal density of sampling ( >50 data points per hour ) allows a much more precise consideration of phase relationships than would be possible in an experiment where the data were sampled less frequently ( e . g . every hour or two ) as is the case in many circadian studies . Moreover , the use of neocortical tissue from humans rather than model organisms enhances the potential for clinical translation . In addition , the fact that all of the participants were organ donors ensures accurate determination of time of death and short postmortem intervals . Finally , these data were obtained from subjects living in the community , rather than in a laboratory , making the data more directly applicable to real-world scenarios . In considering these data , a few methodological points are worth noting . In this study , we inferred group-level average 24-hour rhythms of DNA methylation and RNA expression from postmortem samples and were limited in exploring individual level differences in 24-hour rhythmicity . However , ethical factors preclude serial sampling of neocortical tissue from naturally behaving individuals , which would be necessary to obtain true individual-level characterization of 24-hour rhythms of neocortical DNA methylation . Moreover , behavioral state at death ( e . g . sleep/wake ) and environment ( e . g . light exposure ) at death were not known . Therefore , it is possible that the observed 24-hour rhythms were confounded by rhythmic differences in behavior , environment , behavioral state , or medical status at death . While laboratory-based experimental designs ( e . g . forced-desynchrony experiments ) exist that can decouple environmental/behavioral effects from circadian effects , similar studies on human neocortical tissue cannot be performed in the context of such experiments . Further studies of neocortical DNA methylation in model organisms studied under controlled conditions will be needed to distinguish environmental , behavioral , and circadian components of 24-hour rhythms of neocortical DNA methylation . Finally , DNA methylation was assessed using data from a beadset ( the Illumina 450k Array ) with specifically selected methylation sites rather than a more unbiased approach that generates truly genome-wide data . Thus , it is conceivable that the methylation sites represented on the beadset platform that we used may not be completely representative of DNA methylation sites as a whole , particularly with regard to intergenic regions that are relatively under-represented on the Illumina 450k Array . Taken together , the data from this study suggest that as in Neurospora , 24-hour cycles of DNA methylation , particularly at sites proximate to the transcription start site , may be an important mechanism regulating 24-hour rhythms of gene expression in the human brain and potentially other human and mammalian tissues . Furthermore , they add to the growing body of evidence that mammalian DNA methylation , once thought to be a relatively stable epigenetic mark , can be dynamic on time scales as short as hours . These results also invite examination of the role of 24-hour rhythms of DNA methylation in the regulation of 24-hour rhythms of gene expression and tissue biology in other clinically important human tissues such as myocardium and liver . Moreover , work in mammalian model systems is needed to identify mechanisms underlying site-specific 24-hour rhythmic DNA methylation . This study included participants from two ongoing longitudinal cohort studies of older individuals: the Religious Orders Study ( ROS ) and the Rush Memory and Aging Project ( MAP ) . The MAP is a community-based study of aging in the greater Chicago area . Recruitment and assessment procedures are described elsewhere [27] . Participants are free of dementia at study enrollment , and agree to annual evaluations and brain donation upon death . At the time of the current analyses , 1667 individuals had completed baseline evaluation and 485 had died , with cerebral cortex DNA methylation data passing quality control criteria ( see below ) available from 402 . The ROS is a longitudinal study of aging in Catholic priests , nuns , and brothers from across the USA . A detailed description can be found elsewhere [28] . At the time of the current analyses , 1172 ROS participants had completed baseline evaluation and 569 had died , with cerebral cortex DNA methylation data passing quality control criteria ( see below ) available from 346 . Of the 748 samples with adequate DNA methylation data , 2 did not have an accurate time of death recorded and were excluded from our analyses . Because all participants in the ROS and MAP are organ donors , time of death is well captured in both cohorts . After quality control filtering ( see below ) data from 738 participants were included in the current analyses . Characteristics of the study participants are shown in Table 1 . The study was conducted in accordance with the latest version of the Declaration of Helsinki and was approved by the Institutional Review Board of Rush University Medical Center . Written informed consent was obtained from all subjects , followed by an Anatomic Gift Act for organ donation . DNA methylation was assessed in 746 human postmortem dorsolateral prefrontal cortex samples as previously described [29] , [30] . Frozen 100 mg dorsolateral prefrontal cortical blocks were thawed on ice and gray matter was manually dissected for DNA extraction using the QIAamp DNA Mini Kit ( Qiagen , Venlo , Netherlands; Cat: 51306 ) . DNA concentration was measured by using the Quant-iT PicoGreen Kit ( Life Technologies , Carlsbad , CA ) and 16 µL of DNA from each sample at a concentration of 50 ng/µL was assayed using the Illumina Infinium HumanMethylation450k Bead Chip assay ( Illumina , San Diego , CA ) by the Broad Institute's Genomics Platform . Raw data generated from Illumina 450k platform were processed using Genome Studio software Methylation Module v1 . 8 ( Illumina , San Diego , CA ) to generate beta-values and detection p-values for 485 , 513 CpG across the human genome following color channel normalization and background removal . We excluded from analysis probes with detection p-values>0 . 01 in any sample , probes in which 47/50 nucleotides matched sex chromosome sequences during sequence alignment using BLAT [31] , probes in which a SNP with a minor allele frequency> = 0 . 01 exists within 10 base pairs upstream or downstream of the CpG site , and probes on the sex chromosomes , leaving 420 , 132 autosomal CpGs in the dataset . Sample quality was assessed using principal component analysis and we included only those samples having principal component 1 , 2 and 3 ( PC1 , PC2 and PC3 ) values within +/−3 standard deviations from their respective means . We also excluded subjects with poor bisulfite conversion efficiency , defined as having at least 2 of the 10 bisulfite conversion control probes failing to reach a value of 0 . 8 . After these exclusions , we had 738 remaining samples . Missing data were imputed and approximated using the k-nearest neighbor algorithm with k = 100 . Following quality control filtering as above , data from 738 subjects were available for analysis . RNA was extracted from dorsolateral prefrontal cortex blocks from a subset of 536 individuals ( Table S1 ) using the miRNeasy mini kit ( Qiagen , Venlo , Netherlands ) and the RNase free DNase Set ( Qiagen , Venlo , Netherlands ) . These samples were quantified by Nanodrop ( Thermo Fisher Scientific , Waltham , MA ) and an Agilent Bioanalyzer was used to assess quality . Samples with Bioanalyzer RNA integrity ( RIN ) score of 5 or less or with less than 5 µg of RNA were excluded . RNA sequencing library preparation was performed by the Broad Institute Genomics Platform using the strand specific dUTP method [32] with poly-A selection [33] . This consists of poly-A selection followed by first strand specific cDNA synthesis , and then uses dUTP for second strand specific cDNA synthesis followed by fragmentation and Illumina adapter ligation for library construction . Sequencing was performed on the Illumina HiSeq with 101 bp paired-end reads and achieved coverage of 150M reads for the first 12 samples , which served as a deep coverage reference . The remaining samples were sequenced with coverage of 50M reads . Next , we trimmed off beginning and ending low quality bases , trimmed adapter sequences from the reads , and removed ribosomal RNA reads . We then used the Bowtie 1 software package [34] to align the trimmed reads to the reference genome . Finally , we used the RSEM software package to estimate , in units of fragments per kilobase per million fragments mapped ( FPKM ) , expression levels for 69 , 605 GENCODE v14 transcripts overlapping with high amplitude DNA methylation sites or whose transcription start sites were within 2 kb of such DNA methylation sites . Age was computed from the self-reported date of birth and the date of death . Sex was recorded at the time of the baseline interview . Individuals were classified as having/not having clinical dementia as previously described [35] . Briefly , trained technicians annually administered 21 cognitive tests spanning 5 cognitive domains [36] . The results of cognitive tests were reviewed by a neuropsychologist to determine the presence or absence of cognitive impairment . At each annual evaluation , a clinician combined the most current available cognitive and clinical data to determine whether the subject had dementia or not according to the NINDS-ADRDA criteria [37] . The final determination of the presence/absence of dementia at the time of death was based on consideration of all cognitive assessments prior to death . For a pathological diagnosis of Alzheimer's disease , as described previously [38] , Bielschowsky silver stain was used to visualize neurofibrillary tangles , diffuse plaques , and neuritic plaques in the frontal , temporal , parietal , and entorhinal cortices , and the hippocampus . Braak stages 0 through VI were assigned based upon the distribution and severity of neurofibrillary tangle pathology [39] . All cases received a neuropathologic diagnosis of no Alzheimer's disease , low likelihood Alzheimer's disease , intermediate likelihood Alzheimer's disease , or high likelihood Alzheimer's disease based on the National Institutes of Aging ( NIA ) -Reagan criteria [40] . A subset of 134 participants in the MAP cohort had undergone up to 10 days of actigraphy a median of 16 . 0 months prior to death ( Table S2 ) . Study staff placed actigraphs ( Actical , Philips Respironics , Bend , OR ) set to record in 15-second epochs on participants' nondominant wrists for up to 10 days . We calculated the interdaily stability statistic [26] , [41] , which is a measure of the day-to-day regularity of the rest-activity rhythm with 1 indicating perfect regularity , and 0 indicating no regularity . For both the DNA methylation and RNA expression data , prior to further analyses , we sought to account for the contribution of identifiable biological ( age , sex , presence/absence of clinical dementia ) and technical ( source cohort , post-mortem interval , batch ) factors to the overall variance in expression or methylation levels at each site , and thereby decrease the “noise” in the data , by regressing the methylation and expression data against these factors . After fitting the model , the residuals of the model were kept and represent the expression or methylation level at each site adjusted for these factors . This accounts for the contribution of these factors to the overall “noise” in the mean expression or methylation levels at each site , but does not preclude assessment of the effects of these factors on the amplitude and phase of rhythmicity . Finally , we scaled the methylation or expression level at each site to the standard deviation for that site considering all 738 subjects . To identify temporal patterns in DNA methylation at each CpG site , we considered DNA methylation as a function of clock time of death , with each subject contributing a single data point to a time series spanning 24-hours . First , to visually identify trends , we divided the data into 4-hour bins and plotted the mean expression levels and 95% confidence intervals of the means . Visual inspection of these figures suggested that 24-hour rhythms of DNA would be appropriately modeled using cosine curves . Therefore , we parameterized daily variation in the DNA methylation data using functions of the form: M = m+ ( β1 ) *cos ( t−βA ) . . [Eq1] where m is the mesor ( the mean value considering all time points ) , ( β1 ) is the amplitude of oscillation , βA is the timing of the peak , and t is the time of death . For computational efficiency , equivalent linearized models of the form M = m+βc*cos ( t ) +βs*sin ( t ) . [Eq2] were fit using the R function lm ( ) and the parameters β1 and βA from Eq1 were calculated using the formulae β1 = ( βc2+βs2 ) 0 . 5 and βA = arctan ( βs/βc ) . For all our analyses , we fixed the period at 24-hours . This is a limitation of any study design where each individual contributes only 1 data point to a 24-hour sampling period . All clock times were converted to radians ( 2π radians = 24 hours; 0 radians = midnight ) for analysis and then converted back to hours for the purposes of visual representation . In our primary analyses , we examined all 420 , 132 sites together , to identify aggregate patterns of rhythmicity . To quantify the probability that the observed data could have occurred by chance alone , we performed a series of analyses comparing the observed data to 10 , 000 permuted null datasets generated by randomly shuffling the times of death in our data while preserving the correlation between DNA methylation sites . For each DNA methylation site in each of these permuted null datasets , we fit a cosine curve as above , calculated the proportion of variance at that site explained by the cosine curve , and determined the time of the acrophase ( βA ) and nadir ( βA-π ) of the fit curve . We then carried out four analyses comparing the observed to the permuted null data: 1 ) we calculated the mean total proportion of variance collectively explained by the individually fit cosine curves in each of the 10 , 000 permuted null datasets and in the observed data , and determined the proportion of null datasets in which this was as large or larger than the observed data . 2 ) We repeated this for the median total proportion of variance collectively explained by the individually fit cosine curves . 3 ) We generated a sorted mean empiric null distribution of proportions of variance explained by taking the mean of the 10 , 000 sorted permuted null distributions ( each of length 420 , 132 ) , and used the Wilcoxon signed-rank test to compare this with the observed distribution of 420 , 132 proportions of variance explained . 4 ) We used the Rao test [42] to compare the observed distribution of methylation nadir times ( βA-π ) to those in the 10 , 000 permuted null datasets . We next examined the relationship between the estimated parameters of rhythmicity ( amplitude and phase ) at each DNA methylation site , and the location of the site relative to nearby transcription start sites . First , we focused in on regions of the genome within 20 kb of GENCODE v14 annotated transcription start sites [43] . We divided these regions into 80 equally-spaced 500 bp bins from −20 kb to +20 kb relative to transcription start sites such that , for instance , the −20 , 000 bp to −19 , 500 bp bin contained all genomic regions ranging from −20 , 000 bp to −19 , 500 bp of any GENCODE-annotated transcription start site . We identified DNA methylation sites contained in each bin , determined the probability distribution of the timing of the methylation nadirs at these sites , and represented this visually as a heat map with the 24-hour cycle divided into 24 equal 1-hour windows . Visual inspection of this heat map suggested a differential phase distribution of DNA methylation sites within 1 kb of transcription start sites , those more than 1 kb upstream of transcription start sites , and those more than 1 kb downstream of transcription start sites . Therefore , we grouped these DNA methylation sites into one of three groups ( −20 kb to −1 kb , −1 kb to +1 kb , and +1 kb to +20 kb ) , plotted the distribution of the timing of the methylation nadirs in each group as a histogram , and compared these temporal distributions using Rao's test [42] . We then went on to examine for associations between physical position and the amplitude of 24-hour cycling . We classified individual DNA methylation sites as high amplitude the peak-to-trough amplitude of rhythmicity was greater than 10% of the mean value of methylation at that site . Using the same bins relative to transcription start sites as above , we determined the proportion of DNA methylation sites that are high amplitude sites , as a function of position from the nearest transcription start site . Enrichment was tested using the chi-square test . We then repeated the above analyses , except that rather than dividing the genome into bins based on position relative to transcription start sites , we incorporated information about other gene landmarks and divided genomic segments into 9 bins: regions within 2 kb upstream of transcription start sites , in the 5′UTR , in the 1st exon , in the 1st intron , in other exons , in other introns , and in the 3′UTR of protein coding transcripts; regions in or within 2 kb upstream of non-protein coding transcripts , and intergenic regions ( defined as all other genomic regions ) . Following this , we examined the relationship between rhythms of DNA methylation and RNA abundance for 20 , 656 DNA methylation sites classified as high amplitude cycling sites ( based on an amplitude of cycling >10% of the mean value of methylation ) and lying in or within 2 kb of GENCODE v14 annotated transcripts in a subset of 536 subjects who had both DNA methylation and RNA sequencing data . We considered all GENCODE v14 [43] isoforms detected in at least 10% of our samples . We divided genomic regions into 7 bins based on gene landmarks as above , excluding non-coding transcripts and intergenic regions , and repeated the above analyses except that rather than considering the absolute clock time of the nadir of methylation at each site , we considered the timing of the nadir of methylation relative to timing of peak RNA expression of the associated transcript . Where a particular DNA methylation sites was associated with more than one transcript , the angular mean of the peak time of all associated transcripts was taken , and the timing of the nadir of methylation was taken relative to this time . These analyses were first visually represented as a heat map , and then a formal bin-by-bin analysis was performed using Rayleigh's test [44] to test for temporal clustering of methylation nadir times relative to the timing of peak RNA expression . We next examined the impact of age , sex , presence/absence of Alzheimer's disease , and the regularity of ante-mortem rest-activity rhythms measured by actigraphy on the amplitude and timing of 21 , 282 high-amplitude DNA methylation ( those described above plus high amplitude intergenic sites ) . We dichotomized age into high vs . low based on the median ( i . e . above or below 88 . 4 years age time of death ) , sex into male vs . female , and Alzheimer's disease into present/absent based on NIA-Reagan criteria [40] intermediate/high vs . low/no . We dichotomized the subset of 134 individuals who had antemortem actigraphy into high vs . low behavioral rhythmicity based on their interdaily stability values being above or below the median ( i . e . above or below 0 . 49 ) . At each high amplitude rhythmic DNA methylation site , we fit extended cosine models of the form M = m+ ( β1+β2x ) *cos ( t−βA−βBx ) [Eq3] where x represents high vs . low age , male vs . female sex , present vs . absent Alzehimer's disease , or high vs . low behavioral rhythmicity , β2 reflects the effect of x on amplitude , and βB reflects the effect of x on phase . As above , for computational efficiency , we fit linearized versions of Eq3 similar to Eq2 using the function lm ( ) and determined the values of β2 and βB from this . We then used the Wilcoxon rank-sum test to compare the distribution of amplitudes between levels of each dichotomous predictor , and used Rao's test to compare the distribution of methylation nadir times between levels of each dichotomous predictor . In total , the analyses described above include 24 independent hypotheses tested . Applying the Bonferroni-Holm correction we therefore set the threshold for significance for each of these tests at p = 0 . 05/24 = 0 . 002 . For all analyses , visual examination of residual plots confirmed that cosine curves of the form described above provided a functionally appropriate description of temporal trends and confirmed model assumptions of homogeneous variance .
Circadian rhythms are intrinsic 24-hour biological rhythms that influence many aspects of human biology , including normal and abnormal human brain functions such as cognition and seizures . Circadian rhythms are maintained by a near 24-hour feedback loop mediated by a series of “clock” genes that are similar across species , including humans . However , the specific mechanisms underlying the circadian regulation of gene transcription are unknown . DNA methylation is an epigenetic mechanism that can influence gene expression without changes in DNA sequence . The 24-hour rhythms of DNA methylation are one mechanism contributing to 24-hour rhythms of clock gene expression in fungi . However , this has not been demonstrated in mammals including humans . In this study , we examined levels of DNA methylation at>400 , 000 sites across the genome in the brains of 738 human subjects and showed significant 24-hour rhythms of DNA methylation . Moreover , we showed that for specific locations of DNA methylation site , these rhythms of methylation were linked to rhythms of gene expression . This is important because it suggests that circadian rhythms of DNA methylation may be an important mechanism underlying circadian rhythms of gene expression in the human brain , and hence circadian rhythms of normal and abnormal brain function .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "and", "health", "sciences", "brain", "time", "series", "analysis", "circadian", "oscillators", "mathematics", "statistics", "(mathematics)", "genome", "analysis", "chronobiology", "dna", "dna", "methylation", "discrete", "mathematics", "combinatorics", "research", "and", "analysis", "methods", "genomics", "neocortex", "mathematical", "and", "statistical", "techniques", "gene", "expression", "statistical", "methods", "serial", "analysis", "of", "gene", "expression", "dna", "modification", "biochemistry", "circadian", "rhythms", "entorhinal", "cortex", "permutation", "anatomy", "genetics", "transcriptome", "analysis", "biology", "and", "life", "sciences", "physical", "sciences", "computational", "biology", "cerebral", "cortex" ]
2014
24-Hour Rhythms of DNA Methylation and Their Relation with Rhythms of RNA Expression in the Human Dorsolateral Prefrontal Cortex
The interaction between follicular T helper cells ( TFH ) and B cells in the lymph nodes and spleen has a major impact on the development of antigen-specific B cell responses during infection or vaccination . Recent studies described a functional equivalent of these cells among circulating CD4 T cells , referred to as peripheral TFH cells . Here , we characterize the phenotype and in vitro B cell helper activity of peripheral TFH populations , as well as the effect of HIV infection on these populations . In co-culture experiments we confirmed CXCR5+ cells from HIV-uninfected donors provide help to B cells and more specifically , we identified a CCR7highCXCR5highCCR6highPD-1high CD4 T cell population that secretes IL-21 and enhances isotype-switched immunoglobulin production . This population is significantly decreased in treatment-naïve , HIV-infected individuals and can be recovered after anti-retroviral therapy . We found impaired immunoglobulin production in co-cultures from HIV-infected individuals and found no correlation between the frequency of peripheral TFH cells and memory B cells , or with neutralization activity in untreated HIV infection in our cohort . Furthermore , we found that within the peripheral TFH population , the expression level of TFH-associated genes more closely resembles a memory , non-TFH population , as opposed to a TFH population . Overall , our data identify a heterogeneous population of circulating CD4 T cells that provides in vitro help to B cells , and challenges the origin of these cells as memory TFH cells . Follicular helper CD4 T cells ( TFH ) are crucial for the development of antigen-specific B cells within germinal centers ( GC ) . TFH cells interact through co-stimulatory receptors and provide essential soluble factors ( i . e . IL-4 , IL-21 ) to promote the survival , isotype switching and selection of high affinity memory B cells [1] . Phenotypic and gene signature analysis has revealed a highly conserved molecular profile of TFH cells in humans , non-human primates ( NHP ) and mice , which is characterized by increased expression of Bcl-6 , CXCR5 , PD-1 , ICOS and decreased expression of CCR7 [2]–[4] . Human TFH cells exhibit a polarized cytokine profile characterized by compromised production of TH1 cytokines and increased secretion of IL-4 , IL-10 and IL-21 [5] . Although IL-21 is characterized as a “hallmark” cytokine of TFH cells , other THelper subsets produce this cytokine [6] . The origin and differentiation of TFH is unclear , as previous studies found TFH cells can derive from TH1 or TH2 cells , or independently of other CD4 lineages [7]–[9] . However , it is well established that the transcription factor Bcl-6 regulates several molecules involved in TFH development ( i . e . PD-1 , IL-21R , CXCR5 ) [10] , [11] . Similarly , the fate of TFH , particularly those in the germinal center ( GC-TFH ) , following the effector phase of the immune response is unclear . We have recently shown that NHP GC-TFH display compromised in vivo cell cycling and are prone to in vitro cell death [4] . Other studies have shown that TFH can form a memory pool found in anatomical sites outside the lymph nodes [12] . Hence , TFH cells may adopt a “central memory” phenotype or undergo cell death after the effector phase [13] . In humans , a circulating CD4 T cell population characterized by high CXCR5 expression can provide in vitro help for B cell isotype switching and shares functional characteristics with TFH cells [14] . It was proposed that these circulating cells , termed “peripheral TFH” ( pTFH ) could represent the memory counterparts of TFH outside the lymphoid organs . Further investigation is needed to establish a direct relationship between TFH cells and pTFH cells . It is becoming increasingly important to understand the interplay between CD4 T cells and B cells during HIV infection , specifically with relation to the generation of broadly neutralizing antibodies . Chronic HIV/SIV infection results in profound changes in CD4 T cell dynamics in lymph nodes characterized by TFH accumulation and increased ability of non-TFH to egress the lymph node [4] , [15] . How this impacts upon the dynamics of pTFH is unknown . Elucidating the biology and dynamics of pTFH , and their ability to provide B cell help may be important for our understanding of TFH memory formation during chronic infection , as well as the establishment of immune correlates reflecting the interactions between CD4 T cells and B cells within secondary lymphoid organs . This is of particular interest for monitoring clinical studies where the B cell arm of the immune system is under investigation [16] . Here we define , detect , quantify and characterize peripheral CD4 T cell populations that support B cell differentiation . We show that particular circulating CD4 T cell populations with distinct cytokine profiles have the capacity to help B cells in vitro . We further show that the frequencies of pTFH populations are significantly compromised during chronic HIV infection but can recover with antiretroviral treatment ( ART ) , although in vitro immunoglobulin production from HIV-infected subjects both on and off ART is reduced compared to healthy subjects . Furthermore , gene expression analysis of pTFH cells and CD4 T cells in tonsil tissue suggest pTFH cells are most closely related to a non-TFH memory population within secondary lymphoid organs . Overall , our data challenge the relationship between pTFH cells and TFH memory cells . Previous studies defined a population of circulating CD4 T cells that express CXCR5 , promote the differentiation of naïve B cells and induce immunoglobulin secretion in vitro [14] , [17] . We further defined CXCR5high CD4 T cells from blood , analyzed their cytokine production and determined their ability to promote B cell differentiation in vitro . CXCR5high CD4 T cells were found predominantly within the CD27highCD45ROhigh CD4 T cell population ( hereafter referred to as central memory ( CM ) ) , in agreement with previous studies [17] . The majority of the CXCR5high CD4 T cell population also expressed CCR7 and we found the CCR7highCXCR5high population represented 6 . 5+/−2 . 8% ( mean+/−S . D . ) of total CD4 T cells in healthy subjects ( Figure 1A ) . The majority of CXCR5high cells expressed CD150 . We further analyzed these cells based on expression of CCR6 , which was previously used in combination with CXCR3 to define a pTFH subset that promotes IgG and IgA production [14] , and PD-1 . CCR7highCXCR5highCCR6high cells represented 1 . 2+/−0 . 9% of total CD4 T cells and a minority of these cells were PD-1high . To analyze the ability of these populations to promote B cell differentiation , naïve and CM CD4 T cells from HIV-uninfected individuals were sorted based on expression of CCR7 , CXCR5 , CD150 , CCR6 and PD-1 ( Figure 1A ) , and cultured with autologous naïve B cells ( CD19+CD27−IgD+ ) as previously described [14] , [18] in the presence of staphylococcal enterotoxin B ( SEB ) . Notably , our sorted naïve B cell population did not express isotype-switched immunoglobulin ( Figure S1A ) and culture conditions that lacked SEB did not induce immunoglobulin production ( data not shown ) . Naïve and CM CCR7low CD4 T cells failed to promote B cell differentiation and immunoglobulin production whereas CM CCR7highCXCR5low cells induced limited production of IgM , IgG1 and IgG3 compared to the CCR7highCXCR5high populations ( Figure 1B ) . The CCR7highCXCR5highCCR6highPD-1high population induced the greatest production of IgG1 , IgG3 and IgA compared to the CXCR5low population . Prior studies defined pTFH cells based on surface expression of CXCR5 , CCR6 and the lack of CXCR3 expression [14] . We found that the greatest help for immunoglobulin production was from CXCR5highCCR6high cell populations and , within those , from the PD-1high cells . We did not eliminate a small population of CXCR3+ cells in order to avoid removing a larger population of CXCR5highCCR6high cells that induce B cell differentiation ( Figure S1B ) . The cytokine profile of pTFH populations shared characteristics with other Thelper subsets , including TH1 , TH17 and Treg cells . Supernatant from the CXCR5highCCR6highPD-1low coculture contained the greatest quantities of TNF-α , IL-2 , and IL-17 compared to the CXCR5highCCR6lowPD-1high coculture ( Figure 1C ) . Notably , the CXCR5highCCR6highPD-1high population , which promoted the greatest production of IgG1 , IgG3 and IgA , showed the greatest IL-21 production , although at low levels . Overall , CXCR5high CD4 T cell populations induced B cell immunoglobulin production , although the CXCR5highCCR6highPD-1high population did so most efficiently . However , this population is not characteristic of a TFH population found in secondary lymphoid organs , as coculture supernatants included a broad array of cytokines characteristic of TFH cells and multiple other Thelper subsets . To determine the impact of HIV on pTFH populations , we compared pTFH cells from HIV-uninfected subjects and treatment-naïve HIV-infected subjects ( Table S1 ) as a frequency of total CD4 cells . Irrespective of how pTFH cells were defined , there was a significant decrease in the pTFH population from HIV-infected subjects compared to HIV-uninfected subjects ( Figure 2A ) . Subjects with CD4 counts greater than 200 had significantly lower pTFH populations , while subjects with CD4 counts less than 200 had the lowest frequency of all phenotypically defined pTFH populations . However , when we defined the CCR6highPD-1high population as a subset of the CXCR5high population , the frequency of the CCR6highPD-1high population increased in subjects with CD4 counts less than 200 ( Figure S2A ) . The increase in PD-1high cells was likely due to immune activation in HIV infection , as we observed increases in the frequency of both PD-1high and ICOShigh cells within the CXCR5high population , with the greatest increases seen in samples with CD4 counts less than 200 ( Figure S2A ) . We also observed a positive trend between CXCR5highPD-1high cells and serum concentrations of soluble CD14 . ( Figure S2A ) . For 10 HIV-infected individuals on whom we had longitudinal samples , we observed a loss of pTFH populations as a frequency of total CD4 T cells over 36 to 48 months ( Figure 2B ) . However , the frequency of PD-1high , ICOShigh and CCR6highPD-1high cells within the CXCR5high population remained stable ( Figure S2B ) . Next , we investigated the impact of ART on the frequency of pTFH within total CD4 T cells . Longitudinal analysis on samples from before and after 24 and 48 weeks of ART revealed a recovery of pTFH populations ( Figure 2C ) . However , the frequency of PD-1high , ICOShigh and CCR6highPD-1high cells remained stable within the CXCR5high population ( Figure S2C ) . Overall , HIV infection causes a loss of pTFH cells and ART promotes the recovery of these populations . To investigate the impact of HIV on the ability of pTFH cells to support B cell differentiation , we performed co-culture experiments with pTFH cells from HIV-infected subjects . We focused on the CXCR5highCCR6high population that included both PD-1high and PD-1low cells due to limited cell numbers in HIV-infected subjects . Similar to previous results , the CXCR5highCCR6high population from HIV-uninfected subjects supported significantly more immunoglobulin production compared to the CXCR5low population . ( Figure 3A ) . However , for HIV-infected subjects we observed less overall immunoglobulin production when CXCR5highCCR6high CD4 T cells were co-cultivated with naïve B cells . Furthermore , in viremic subjects , we observed increased IgM and IgG1 production in co-culture supernatants from the CXCR5low population , compared to HIV-uninfected subjects . Similar to HIV-uninfected subjects , we found that pTFH cells from HIV-infected subjects produced a broad spectrum of cytokines ( Figure S3A ) . Our data raise the possibility that some pTFH cells exhibit a CXCR5low phenotype in HIV infection . This phenotype could be due the down regulation of CXCR5 on pTFH cells , or indicate the existence of a unique CXCR5low pTFH population in chronic HIV infection . In order to distinguish these two possibilities , we investigated whether CXCL-13 impacts CXCR5 expression on CD4 T cells . We found that incubation of HIV-uninfected PBMC with CXCL-13 led to a decrease in frequency of CXCR5-positive CD4 T cells , presumably due to the internalization of CXCR5 ( Figure 3B ) . Furthermore , in HIV infection we found that viral load positively correlated with CXCL-13 levels and negatively correlated with the frequency of CXCR5-positive CD4 T cells ( Figure 3C ) . However , we did not observe a direct correlation between CXCL13 levels and the frequency of CXCR5-positive CD4 T cells . Importantly , we also found that in vitro infection of CXCR5-expressing CD4 T cells did not impact CXCR5 surface expression ( Figure S3B ) . Therefore , our data support the possibility that in untreated HIV infected individuals , increased levels of CXCL-13 could effect CXCR5 surface expression on pTFH cells . TFH-dependent B cell differentiation requires IL-21 . To characterize directly cytokine production from pTFH cells from HIV-uninfected and HIV-infected subjects , we performed intracellular cytokine staining after ex vivo SEB stimulation . In addition to surface markers used to define pTFH cells , we detected CD154 , IFN-γ , IL-2 , IL-17 and IL-21 ( Figure 4A ) . In HIV-uninfected individuals , a minority of CD154-positive , cytokine-positive cells express a CCR7high phenotype ( 10 . 1% of IFN-γ positive cells; 28% of IL-2-positive cells; 19 . 4% of IL-17-positive cells and 17 . 9% of IL-21-positive cells ) , while a gradual reduction of cytokine production was found in further differentiated cells based on CXCR5 and CCR6 expression ( Figure 4B ) . However , for all of the cytokines detected , we observed a population of cells that were CCR7highCXCR5highCCR6high , including IL-21-producing cells . Overall , we determined that a mean of 4 . 5% of CD154-positive IL-21-positive cells were CCR7highCXCR5highCCR6high ( Figure 4B ) . However , this pTFH population also produced IFN-γ , IL-2 and IL-17 ( 0 . 8% of IFN-γ positive cells; 9 . 0% of IL-2-positive cells and 7 . 1% of IL-17-positive cells ) . Next , we analyzed cytokine production from HIV-infected subjects off-treatment . Overall , we observed a loss of cytokine-producing cells from the CCR7high population and a general shift towards the CXCR5lowCCR6low population ( Figure 4A ) . Thus , we observed a loss of CCR7highCXCR5highCCR6high pTFH cells that produce IL-2 , IL-17 and IL-21 ( Figure 3B; IL-2: 9 . 0% for HIV-negative vs 2 . 0% for HIV-positive; IL-17: 7 . 1% for HIV-negative vs 2 . 2% for HIV-positive; IL-21: 4 . 5% for HIV-negative vs 1 . 1% for HIV-positive ) . To analyze HIV-specific cells , PBMC were stimulated with Gag peptide pools and analyzed for cytokine expression . Very few IL-2-positive and IL-17-positive cells were detected within the CM compartment ( data not shown ) . Gag-specific IFN-γ and IL-21-producing cells were detected , however , compared to SEB-stimulation fewer HIV-specific cells expressed CCR7 ( 4 . 4% vs 10 . 7% of IFN-γ positive cells; 3 . 5% vs 11 . 9% of IL-21-positive cells for Gag and SEB stimulation , respectively ) . A majority of HIV-specific cells were not CCR7highCXCR5highCCR6high ( Figure 4C; 0 . 4% of IFN-γ positive cells and 0 . 9% of IL-21-positive cells were CCR7highCXCR5highCCR6high ) . Overall , we observed IL-21 production from the CCR7highCXCR5highCCR6high pTFH population , although we detected the most IL-21 in non-pTFH cells , which were CCR7low and CXCR5low . In addition to IL-21 , the CCR7highCXCR5highCCR6high pTFH population produced IL-2 and IL-17 , cytokines characteristic of TH1 and TH17 cells , respectively . However , from HIV-infected individuals we observed a loss of CCR7highCXCR5highCCR6high cells making IL-2 , IL-17 and IL-21 . Previous studies have described a relationship between the frequency of peripheral CXCR5high cells and memory B cells and antibody titers with vaccination [16] . Therefore , we analyzed the relationship between the frequency of pTFH cells and IgG-positive memory B cells in PBMC from HIV-infected individuals . We found no significant correlation between the frequency of pTFH cells and IgG-positive B cells ( Figure 5A ) . Similarly , we failed to detect a relationship between the frequency of pTFH and HIV-1 Env-specific antibody titers or total plasma IgG levels ( data not shown ) . It has also been reported that PD-1high CD4 T cells in blood are associated with cross-clade neutralizing antibody responses during HIV infection [19] and these PD-1high CD4 T cells may represent a population of pTFH cells . Thus , the relationship between pTFH cells and neutralization activity was analyzed using HIV-infected samples classified as good neutralizers ( median ID50>100 ) or poor neutralizers ( median ID50<100 ) [20] . Irrespective of how pTFH cells were defined , we failed to find any relationship between neutralization activity and pTFH cells ( Figure 5B ) . While pTFH cells induce B cell differentiation and immunoglobulin secretion in vitro , the relationship between pTFH and TFH cells in secondary lymphoid organs remains unclear . Our in vitro coculture studies indicated the greatest isotype-switched immunoglobulin production was elicited from B cells cocultivated with CXCR5highCCR6high pTFH cells ( Figure 1B ) . Therefore , we investigated the expression of CCR6 on TFH ( CXCR5highPD-1high ) and non-TFH ( CXCR5lowPD-1low ) tonsil cells to determine if the CXCR5highCCR6high pTFH population is related to TFH cells within secondary lymphoid organs ( Figure 6A ) . The lowest frequency of CCR6high cells was found within the CXCR5highPD-1high compartment ( 1 . 5% of CXCR5highPD-1high cells ) and the greatest frequency of CCR6high cells within the non-TFH compartment ( 9% of CXCR5lowPD-1low cells; Figure 6B ) . Similarly , RNA sequence data from the CXCR5highCCR6highPD-1high pTFH population more closely resembles a memory , non-TFH CD4 T cell population from the tonsil ( CM CD57lowPD-1dimCCR7highCCR5lowCXCR4low ) as compared to the non-germinal center TFH population ( CM CD57lowPD-1highCCR7lowCXCR5high ) or the GC-TFH population ( CM PD-1highCD57high; Figure 6C ) . In agreement with previous reports [5] , [17] , tonsil TFH populations expressed higher levels of BCL6 , IL-21 , and CXCL13 , and lower levels of PRDM1 and S1PR1 compared to the non-TFH memory population . The pTFH population from HIV-uninfected individuals expressed comparable levels of S1PR1 and PRDM1 to the non-TFH memory population in the tonsil ( Figure 6 ) . We also observed lower transcript levels of MAF , BCL6 , IL-21 , and CXCL-13 in the pTFH population compared to tonsillar TFH populations . Importantly , MAF protein expression was highest in the CCR6highPD-1high pTFH population compared to other peripheral populations , although still lower than tonsillar TFH cells . ( Figure 6D ) . For many of the selected genes , pTFH cells from HIV-infected subjects were comparable to pTFH from HIV-uninfected individuals , however , we observed greater transcript levels of activation molecules such as ICOS and CD69 . Additionally , the levels of IL-21 were decreased in pTFH cells from HIV-infected individuals , supporting earlier results ( Figure 4B ) . Collectively , our data suggest the pTFH population characterized as CXCR5highCCR6high most closely resembles a non-TFH memory population in the tonsil . The development and nature of human TFH memory cells following an effector immune response are not known . The ability to define a population of memory TFH cells in PBMC ( pTFH ) would help inform our understanding of CD4 T cell dynamics within lymphoid tissue during vaccination or infection . Studies of chronic infection may be helpful in this regard [21] . Whether the accumulation of TFH cells during chronic infection [4] , [15] impacts the TFH memory population is of particular interest , especially if memory TFH cells migrate between lymphoid organs and peripheral tissues . Recent studies [14] , [16] have suggested that circulating CXCR5high CD4 T cells may represent the peripheral counterparts of TFH cells . However , the relationship between pTFH and TFH cells within secondary lymphoid organs remains unclear . Therefore , it is of great relevance to determine if pTFH cells originate from GC-TFH cells and represent a memory TFH population , reflect a precursor population that differentiates into GC-TFH upon re-exposure to antigen , or both . Our studies begin to address these issues by further defining pTFH cells , comparing pTFH cells to tonsillar TFH cells , and analyzing the effect of HIV on these cells . In concordance with previous studies , we showed that circulating CXCR5high CD4 T cells support B cell differentiation in vitro [14] , [17] . A majority of the CXCR5high cells expressed CD150 , and while CD150 was used for gating in the co-culture assays , we found it did not impact the loss of pTFH cells or effect our results with respect to loss of pTFH cells , recovery with ART or lack of association with B cell or antibody responses ( data not shown ) . However , within the CXCR5high population the expression of CCR6 and PD-1 did further define pTFH populations with differential abilities for naïve B cell help and isotype switching . Thus , pTFH cell populations support both the activation and maturation of naïve B cells , and immunoglobulin isotype switching . Correspondingly , the individual pTFH populations produced cytokines associated with B cell maturation and survival , such as IL-21 [22] , IL-2 [23] and IL-17 [24] , in contrast to TFH cells within secondary lymphoid tissue , which display a limited cytokine profile that includes IL-4 , IL-10 and IL-21 , but compromised production of IL-2 and IL-17 [4] . Whether these pTFH populations represent different stages of TFH memory development or originate from separate CD4 T cell populations within lymphoid tissue [25] is still unclear . In order to better understand the relationship between TFH and pTFH cells , we compared gene expression levels between pTFH and tonsillar CD4 T cell populations and focused on genes important for TFH differentiation , migration , and function . We found that the pTFH population with the greatest B cell helper function most closely resembled a CM , non-TFH CD4 T cell subset within the tonsil . While our studies do not directly address the relationship between GC-TFH in lymph nodes and circulating CD4 T cells from the same patients , our data challenge whether pTFH are memory TFH cells . A recent study reported that germinal center TFH cells in mice migrate throughout the follicle , but generally do not leave the follicle to enter the blood [26] . While it is conceivable that pTFH cells represent a very minor population of TFH cells that exit the follicle , it is also possible that pTFH cells are reflective of a precursor TFH population that exits the lymphoid organ and enters the circulation before entering the follicle . However , while we find the CXCR5highCCR6highPD-1high pTFH population does not resemble a memory TFH population , Locci and colleagues found a CXCR5+CXCR3-PD-1+ pTFH subset that functionally and transcriptionally resembles a memory TFH population [27] . A recent study in mice reported that memory TFH cells have reduced mRNA expression of TFH markers such as Bcl6 , IL-21 , ICOS and PD-1 compared to the effector TFH population [28] , indicating the expression of these molecules may change depending on the phase of infection . Therefore , further investigation of pTFH subsets and their relationship to memory and effector populations at multiple stages of infection is needed . pTFH and naïve B cell co-cultures from HIV-infected subjects produced fewer immunoglobulins compared to co-cultures from HIV-uninfected subjects . The observed defect in immunoglobulin production is likely due to impaired pTFH help to B cells instead of B cell dysfunction , as co-cultures included naïve B cells rather than memory B cells that exhibit abnormalities in HIV infection [29] . Furthermore , while co-culture supernatants from HIV-infected subjects demonstrated a heterogeneous cytokine profile , similar to HIV-uninfected subjects , intracellular cytokine staining showed that fewer CCR7highCXCR5highCCR6high pTFH cells produced IL-2 , IL-17 and IL-21 in chronic HIV infection compared to HIV-uninfected individuals . Furthermore , gene expression analysis of HIV-infected pTFH revealed fewer IL-21 and IL-4 transcripts , although the overall levels of cytokine transcripts were low . Recent studies have shown TFH cells within secondary lymphoid organs accumulate in some donors or animals during chronic HIV/SIV infection and that TFH accumulation is associated with GC B cell expansion and increased serum immunoglobulin concentrations [4] , [22] , [30] . In contrast to TFH cells , our studies revealed pTFH cells consistently decrease in chronic HIV infection , with disease progression resulting in a greater reduction of these compartments within the total CD4 T cell population . However , it should be noted that we were unable to analyze TFH cells within secondary lymphoid organs from these subjects and therefore we are unable to directly compare the frequency of pTFH cells and TFH cells from the same individual . The differences between the increase in TFH cells and decrease in pTFH cells may be due to differences in disease state ( i . e . early vs late infection ) or represent a steady state of TFH cells trafficking between the lymphoid tissue and the blood . The decreased frequency of pTFH in the blood may indicate impaired ability of TFH to exit the lymph node in chronic HIV infection where the tissue architecture is not intact . Alternatively , the decreased frequency of pTFH in the blood may be a result of pTFH trafficking to secondary lymphoid organs . In agreement with previous studies [14] , [17] , we found a majority of CXCR5high cells express CCR7 , and it has previously been suggested that pTFH cells migrate to secondary lymphoid organs upon infection due their expression of CCR7 and CD62L [14] . A confounding factor with regard to how we interpret the decrease in pTFH cells is that we also found a reduction in the surface expression of CXCR5 on CD4 T cells in chronic HIV infection , which may result from increased sera levels of CXCL-13 [31] , [32] . Furthermore , our co-culture data indicate that CXCR5low CD4 T cells from viremic subjects can induce some B cell differentiation . These data support the possibility that in chronic HIV infection , a subset of functional pTFH cells may be phenotypically defined as CXCR5low . Additionally , it should be noted that analysis of cellular subsets within the CXCR5high population in chronic HIV infection revealed the frequency of CCR6highPD-1high cells increased . These results are consistent with a state of generalized immune activation , as we also observed increased surface expression of ICOS on CXCR5high and CXCR5highPD-1high cells , and a positive association between the frequency of PD-1high cells within the CXCR5high population and serum concentrations of soluble CD14 [33] . Similarly , gene expression analysis indicated increased transcript levels of activation markers , such as ICOS and CD69 within the pTFH population during HIV infection . Overall , these data emphasize the difficulty in defining pTFH cells in chronic HIV infection and understanding the relationship between pTFH cells and TFH cells . The uncertain definition of pTFH cells in HIV infection may provide an explanation as to why we were unable to identify correlations between pTFH populations and circulating IgG-positive memory B cells , or between pTFH cells and HIV-specific IgG ( data not shown ) . Furthermore , we found no correlation between the frequency of pTFH and the neutralization activity of a well-characterized cohort of HIV-infected donors [20] . However , the absence of a correlation between pTFH cells and circulating HIV Env-specific IgG may also be explained by the lack of a time-dependent association ( early vs . late infection ) between TFH and pTFH cells , or indicate that the generation of IgG and broadly neutralizing antibodies is regulated by parameters other than pTFH , confounded by T-cell independent antibody production commonly observed in HIV infection [34] or generalized immune activation . Thus , our data challenge the application of the pTFH population as a surrogate of GC TFH-B cell interactions in chronic HIV infection . While our studies did not find a correlation between pTFH cells and neutralizing antibodies , several recent studies , each with a different definition of pTFH cells , have reported an association with antibody responses during vaccination , infection or autoimmune disease [27] , [35]–[37] . Therefore , further studies are needed to establish the association between pTFH subsets and the generation of neutralizing antibodies , especially in HIV infection . Overall , our data indicate that a range of circulating CD4 T cell populations can provide B cell help , possibly through differential secretion of soluble factors and/or cell-cell contact interactions [17] , [35] and that HIV infection results in loss of these cells over time , but with relative increases within the CXCR5high compartment which may be explained by immune activation . Furthermore , we did not find any association between pTFH and measures of B cell function such as HIV neutralization breadth/potency , HIV-specific IgG , or total IgG , suggesting application of this population as a surrogate of GC TFH-B cell interactions during HIV infection may be limited . A better understanding of the differentiation process and the developmental relationship between pTFH subsets and lymph node TFH cells is critical for the establishment of reliable peripheral blood CD4 T cell correlates for monitoring infection- or vaccine-associated B cell responses . Signed informed consent was obtained in accordance with the Declaration of Helsinki and approved by the appropriate Institutional Review Board . Tonsil cells were acquired from anonymized discarded pathologic specimens from Children's National Medical Center ( CNMC ) under the auspices of the Basic Science Core of the District of Columbia Developmental Center for AIDS Research . The CNMC Institutional Review Board determined that study of anonymized discarded tonsils did not constitute ‘human subjects research . ’ Fresh HIV-uninfected peripheral blood mononuclear cells ( PBMC ) were obtained from individuals participating in the NIH research apheresis program . Fresh HIV-infected blood was obtained from the Vaccine Research Center Clinic or Drexel University College of Medicine . Frozen HIV-infected PBMC were obtained from three study populations ( Table S1 ) . For untreated HIV infection , cells were obtained from volunteers who participated in a therapeutic vaccination trial ( no efficacy was observed ) conducted in the 1990's prior to the advent of combination antiretroviral therapy ( cART ) [38] . The second study population consisted of donors from a cohort used to identify individuals with HIV broadly neutralizing antibodies [20] . To study the effect of cART , we obtained PBMC from HIV-infected donors participating in AIDS Clinical Trials Group study A5142 prior to initiation of cART and 24 and 48 weeks post-therapy [39] , [40] . PBMC and tonsil cells were cultured in RPMI 1640 supplemented with 10% fetal bovine serum , 2 mM L-glutamine , 100 U/mL penicillin and 100 µg/mL streptomycin ( Invitrogen ) . Directly conjugated antibodies were acquired from the following: ( 1 ) BD Biosciences: CD3-H7APC , CXCR5-Alexa488 ( RF8B2 ) , CCR7-Alexa700 , IgG-APC , IFN-γ-Alexa700 and IL-21-Alexa647 ( 3A3-N2 . 1 ) ( 2 ) Beckman Coulter: CD45RO-ECD and CD27-PC5 ( 3 ) Biolegend: CCR7-BV421 , CCR6-PE ( TG7/CCR6 ) , CCR6-Alexa647 ( TG7/CCR6 ) , CD20-BV570 , CD150-PE , IL-2-BV605 , IL-17a-Cy5 . 5PerCP and CD154-Cy5PE ( 4 ) Invitrogen: CD4-Cy5 . 5PE , CD27-QD655 , CD27-QD605 and CD19-PacBlue ( 5 ) Southern Biotech: IgD-FITC and IgD-PE ( 6 ) eBioscience: cmaf-eFluor660 ( sym0F1 ) , CXCR5-PerCP-efluor710 ( MU5UBEE ) . Biotinylated anti-PD-1 was from R&D and streptavidin-Cy7PE ( or QD655 ) was from Molecular Probes . The following antibodies were conjugated in our lab: CD19-QD705 and CD57-QD565 . Quantum dots and Aqua amine viability dye were obtained from Invitrogen . Co-culture experiments were performed with freshly isolated PBMC . 5×104 CD4 T cell populations were sorted based on expression of CCR7 , CXCR5 , CD150 , CCR6 and PD-1 and cultured with 5×104 autologous naïve B cells ( 1∶1 ratio ) in the presence of SEB ( 0 . 5 µg/ml ) . Supernatants harvested on Day 2 were analyzed for cytokines using Luminex technology ( Milliplex MAP Kit , HTH17MAG-14K , Millipore ) . The lower limit of detection ( LOD ) was set at the lowest concentration on the standard curve and values below the LOD were counted as zero . Supernatants collected on Day 12 were analyzed for immunoglobulins ( Milliplex MAP Kit , HGAMMAG-301K ) . Some supernatants exceeded the saturation limit of the standard curves for IgM and IgG3 . These values were included in the analysis and quantified as being equivalent to the highest determined concentration . Soluble CD14 and CXCL-13 ( R&D Systems ) were measured in plasma or sera from HIV-infection patients according to the manufacturer's instructions . Freshly isolated PBMCs were incubated with recombinant human CXCL-13 ( R&D Systems ) at 37°C or 4°C and analyzed for CXCR5 surface expression by FACS . CD4 T cell populations were sorted from uninfected PBMC ( n = 5 ) , HIV-infected PBMC ( n = 5 ) and uninfected human tonsils ( n = 4 ) based on expression of CCR7 , CXCR5 , CD150 , CCR6 and PD-1 for PBMC and CD57 , PD-1 , CCR7 , CXCR5 , CCR5 and CXCR4 for tonsils . Total RNA was purified from sorted cell populations and treated with DNAse I ( Ambion ) to minimize genomic DNA contamination . Polyadenylated RNA was isolated using Oligo-dT Dynabeads ( Life Technologies ) , chemically fragmented , and used to construct barcoded Illumina Truseq libraries . Libraries were size-selected , quantified , pooled , size-selected and quantified again , and clustered on an Illumina Truseq Paired-End Flowcell v3 . The flowcell was sequenced on an Illumina HiSeq 2000 in a 2×75-base paired-end , indexed run . Adaptor sequence was trimmed from the raw sequencing reads using Trimmomatic . The trimmed sequencing reads were subsequently aligned to the human genome ( hg19 ) using TopHat 2 . Differential expression testing was done using Cufflinks 2 and visualization of differential expression was done using the R package cummerbund . Accession numbers of the selected genes are shown in Supporting Table S2 . Neutralization activity of patient sera was determined against 20 viral isolates using a TZM-bl neutralization assay as previously described [20] . Freshly isolated PBMCs were stimulated with PHA ( 10 µg/ml ) . After 12 hours stimulation , CXCR5high cells were sorted by FACS Aria based on surface molecule expression and infected by a multiplicity of infection ( MOI ) of 0 . 01 with either HIV NL-E or HIV NLAD8-E [41] . The infected cells were cultured in the presence of 50 U/ml recombinant human interleukin-2 ( R&D ) for 5 days and analyzed for CXCR5 expression by FACS . Experimental variables were analyzed using the nonparametric Mann-Whitney U test , the Wilcoxon matched-pairs signed rank test or the Friedman test with Dunn's multiple comparison post-test . Correlation analysis was performed using the nonparametric Spearman test . Error bars depict mean+SEM in all bar graphs shown . The GraphPad Prism statistical analysis program ( GraphPad Software , version 5 . 0 ) was used throughout .
Follicular T helper cells ( TFH ) interact with B cells within germinal centers of lymphoid tissue to promote the survival , isotype switching and generation of high affinity memory B cells and plasma cells . Recently , a population of circulating CD4 T cells that shares phenotypic and functional characteristics with TFH cells , named peripheral TFH cells , has been identified . The relationship between peripheral TFH cells in the blood and TFH cells within the lymphoid tissue remains unclear , and whether or not peripheral TFH cells can provide insight into T cell and B cell dynamics within lymphoid tissue during infection or vaccination is not understood . Here we characterize peripheral TFH cells and show that unlike TFH cells , peripheral TFH cells secrete a diverse array of cytokines and decrease , rather than increase , during chronic HIV infection . Furthermore , we did not observe a relationship between peripheral TFH cells and memory B cells , or with the production of neutralizing antibodies to HIV . Overall , our data indicate that while peripheral TFH cells share some characteristics with TFH cells , they may not represent a good surrogate to study T cell and B cell dynamics within lymphoid tissue .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "antibody-producing", "cells", "infectious", "diseases", "immune", "cells", "cytokines", "b", "cells", "immunoglobulins", "hiv", "t", "cells", "retrovirology", "and", "hiv", "immunopathogenesis", "immunology", "biology", "viral", "diseases", "immune", "system" ]
2014
Loss of Circulating CD4 T Cells with B Cell Helper Function during Chronic HIV Infection
Human African Trypanosomiasis ( HAT ) is a major public health problem in the Democratic Republic of the Congo ( DRC ) . Active and passive surveillance for HAT is conducted but may underestimate the true prevalence of the disease . We used ELISA to screen 7 , 769 leftover dried blood spots from a nationally representative population-based survey , the 2007 Demographic and Health Survey . 26 samples were positive by ELISA . Three of these were also positive by trypanolysis and/or PCR . From these data , we estimate that there were 18 , 592 people with HAT ( 95% confidence interval , 4 , 883–32 , 302 ) in the DRC in 2007 , slightly more than twice as many as were reported . Human African trypanosomiasis ( HAT ) has been reported in most of sub-Saharan Africa as well as in travelers to the region [1] . Currently , the global prevalence of the disease is uncertain . From 2006 to 2008 , there were 7200–8200 reported cases of HAT per year [2] . However , since HAT occurs in remote areas with poor health infrastructures , under-reporting is likely . Thus , estimates of the global burden have been as high as 300 , 000 [3] . Nearly two-thirds of all reported HAT cases are from the Democratic Republic of the Congo ( DRC ) . However , the DRC is a huge country ( 2 . 3 million km2 ) with poor infrastructure and only 2 , 794 km of paved roads ( https://www . cia . gov/library/publications/the-world-factbook/geos/cg . html ) . Only 19% of the presumed at-risk population was screened in 2003 [4] . High prevalence of HAT was found recently in surveillance “blind spots” both in the DRC and elsewhere [5] . Thus , the true number of HAT cases could be much higher than the numbers reported to the World Health Organization ( WHO ) . The problem of over- and underestimating the prevalence of diseases is not unique for HAT . One approach to obtaining accurate assessments of disease prevalence is through nationally representative health surveys [6] . Demographic and Health Surveys ( DHS ) are a widely used method to obtain nationally representative data and have been conducted hundreds of times in developing countries ( http://www . measuredhs . com/ ) . Since 2001 , many DHS have included dried blood spots from participants to be used for a more accurate assessment of HIV seroprevalence . Seroprevalences determined this way are not subject to selection biases and are often quite different from results obtained using sentinel populations such as those who attend antenatal care clinics . Recently , using these new data , the WHO revised its estimates of the global prevalence of HIV [7] . In this study , we attempt to obtain a population-based estimate of HAT prevalence in the DRC . To accomplish this , we screened 7 , 769 leftover dried blood spots from the 2007 DRC DHS . The survey methodology was described previously [8] , [9] . Briefly , a 2-stage stratified cluster design based on a national survey was used to generate nationally representative data on population , health and social indices . Nine thousand households from 300 randomly selected population-representative geographic clusters ( Fig . 1 ) , were selected for inclusion; all women aged 15 to 49 years within these households were surveyed , and , in half of the households , men aged 15 to 59 were surveyed . All men and half of the women were consented for collection of blood spots . The specimens were originally collected for the determination of HIV seroprevalence and were deidentified before we received them . Our study received ethical approval from the Institutional Review Boards of the Kinshasa School of Public Health and the University of North Carolina . The ELISA for T . b . gambiense was performed as described by Hasker et al . with some modifications [10] . From each dried blood spot , two 5 mm diameter disks were punched and eluted in 1 ml elution buffer . The eluted fraction was separated from the disks and assayed in duplicate both in the presence and absence of antigen consisting of a mixture of purified T . b . gambiense LiTat 1 . 3 , and LiTat 1 . 5 each at a concentration of 1 µg/ml , coated at 150 µl per well in microtitre plates ( Maxisorp , Nunc ) . ELISA results were expressed as percent positivity relative to a positive control serum run in each plate . A result was considered positive if ≥ 45% . Immune trypanolysis was performed according to Van Meirvenne et al . [11] with cloned live populations of T . b . gambiense Variable Antigen Types ( VATs ) LiTat1 . 3 and LiTat 1 . 5 and one T . b . rhodesiense VAT ETat 1 . 2R . The test was adapted for testing blood impregnated filter paper according to Holland et al . [12] . Briefly , from each dried blood spot , a 6 mm diameter disk was punched and placed in a well of a flat-bottom microtitre plate containing 20 µl of guinea pig serum ( complement source ) . The plate was covered with a lid and put at 4°C on a microtitre plate shaker for elution . After one hour , 10 µl of a 107 trypanosomes/ml suspension in guinea pig serum were added to each well , leaving the filter paper disks in place . The plate was incubated at ambient temperature and shaken for 30 , 60 and 90 minutes . After 90 minutes , the suspension in each well was examined under the microscope ( 25×10 magnification ) for living trypanosomes . Trypanolysis was considered positive when >50% of the trypanosomes were lysed . T . b . rhodesiense VAT ETat 1 . 2R was used as a control for the absence of non-specific trypanolytic activity of the test specimens . Genomic DNA ( gDNA ) was extracted from dried blood spots using the invitrogen Purelink 96 kit ( invitrogen , Carlsbad , CA ) as described ( Taylor et al , submitted ) . A TaqMan®-MGB real-time PCR assay targeting the 177 bp satellite repeat was developed , modeled after a published SYBR Green method [13] . Applied Biosystems Primer Express Software 3 . 0 was used to design real-time PCR primers and FAM-labeled probe to amplify this region ( Table 1 ) . Primer specificity was evaluated through a BLAST search of the human genome . After optimizing the assay , each real-time PCR reaction contained 1 µg of gDNA , ABI's TaqMan® MasterMix ( 10× ) , 100 nM probe , 300 nM of each primer , and nuclease-free water to reach a total reaction volume of 25 µL . The real-time PCR reactions were carried out using an ABI PRISM® 7000 Sequence Detection System ( Applied Biosystems , Inc . , Foster City , CA , USA ) under the following conditions: 50°C for 2 minutes , 95°C for 10 min . , and 45 cycles of 95°C for 15 seconds and 60°C for 1 min . Human gDNA extracted from whole blood and nuclease-free water were used as negative controls . T . b . brucei DNA at 0 . 1 ng/µL was used as the positive control . All samples and controls were run in duplicate or triplicate . The sensitivity and specificity of this PCR assay was determined on human samples previously obtained [14] . Informed consent from Congolese , Ugandan and Dutch patients was obtained . The study was approved by the Ethical Committee of the University of Antwerp ( reference number: B3002006603 ) . Blood was collected from 59 patients , of whom 33 had peripheral parasites and 26 had CSF parasites only . Control blood was collected from 50 healthy individuals in Uganda , the DRC , and the Netherlands . HAT prevalence was determined by calculating the proportion of the 7 , 769 samples which were positive using the sampling weights of the DHS survey ( in this case the three positive cases were weighted as2 . 3 ) . This proportion was then multiplied by the total mid-year population of the DRC in 2007 , estimated by the Population Reference Bureau to be 62 . 6 million [15] . The confidence interval was computed using the standard error of the percentage calculated by SAS Proc Surveyfreq , which accounts for sampling weights and clustering of the samples tested . A total of 7 , 769 samples were tested by ELISA ( Fig . 2 ) . Of these samples , 26 specimens in 23 sites were found to be positive ( data not shown ) . For PCR confirmation of ELISA-positive specimens we developed a Taqman real-time PCR assay to improve specificity . Using previously collected samples ( not from the DRC DHS set ) , this PCR assay was positive in 33% ( 10/31 ) of the subjects with known microscopy-confirmed HAT in peripheral blood samples and none of the uninfected patients ( 0/17 ) . Thus , this assay had low sensitivity but very high specificity . All 26 ELISA-positive samples were tested by both trypanolysis and PCR ( Fig . 2 ) . Two subjects were positive by trypanolysis with 100% lysis on both LiTat 1 . 3 and LiTat 1 . 5 VAT . One of these trypanolysis-positive specimens was also positive by PCR . In addition , one trypanolysis-negative subject was positive by PCR , suggesting a recent infection that had not yet elicited anti-trypanosomal antibodies . The other 23 ELISA positive samples which were negative by PCR and trypanolysis are likely to be false positives . This false positive rate ( 23/7766 ) translates to a very high ELISA test specificity ( 99 . 7% with 95% CI: 99 . 5–99 . 9 ) . However , given the low prevalence of the disease , the ELISA's positive predictive value is only 11 . 5% ( 95% CI: 4 . 0–28 . 9 ) . All 3 trypanolysis and/or PCR-positive subjects were male and were HIV-seronegative . Two were co-infected with P . falciparum [8] . These 3 cases were found in two sites , both of which are in known endemic regions ( Fig . 1 ) . The overall prevalence of HAT in the DRC was calculated using standard sampling weights and found to be 29 . 7 cases/100 , 000 persons . Assuming a total population of 62 . 6 million , this leads to an estimated 18 , 592 people with HAT ( 95% confidence interval , 4 , 883–32 , 302 ) in the DRC in 2007 . In 2007 , the National Trypanosomiasis Control Program reported 8 , 162 cases of HAT . Our results suggest that 56% of actual HAT cases were not detected and therefore not reported [2] . This is very close to estimates of underreporting used by the WHO ( 65–75% ) [16] . The estimates obtained here are subject to several limitations . First , none of the tests are completely sensitive , so cases of HAT infection could have been missed . Second , HAT is a highly clustered disease , and it is possible that specific small geographic regions with high HAT prevalences were not accurately sampled . Both limitations would have led to understimates of the prevalence of the disease . Nevertheless , our results provide the first nationally representative population-based data on the prevalence of this disease and confirm WHO estimates for under-reporting . This study also confirm that population-based surveys are useful in determining the burden of infectious diseases .
Because of weak health surveillance infrastructures in poor countries , estimates of the burdens ( numbers of infections ) of many tropical diseases may be inaccurate . In particular , current estimates for the global burden of Human African Trypanosomiasis ( Sleeping Sickness , HAT ) vary widely . Most of the reported HAT cases occur in the Democratic Republic of the Congo , where many barriers to surveillance exist . The best way to generate accurate burden estimates is to use a survey sampled to be representative of the general population . Demographic and Health Surveys ( DHS ) are a widely used tool to obtain nationally representative health data and have been conducted hundreds of times in developing countries , In this report , we use samples from the 2007 Democratic Republic of the Congo DHS to estimate the burden of HAT . ELISA tests were conducted on 7 , 769 leftover dried blood spots followed by confirmatory trypanolysis and PCR tests . Our data suggest that there are approximately 18 , 592 cases of Human African Trypanosomiasis ( Sleeping Sickness ) in the DRC , close to WHO estimates .
[ "Abstract", "Introduction", "Methods", "Results", "and", "Discussion" ]
[ "medicine", "public", "health", "and", "epidemiology", "biomarker", "epidemiology", "molecular", "epidemiology", "epidemiology", "infectious", "disease", "epidemiology", "global", "health" ]
2011
Prevalence of Human African Trypanosomiasis in the Democratic Republic of the Congo
The liver is a vital organ involving in various major metabolic functions in human body . MicroRNA-122 ( miR-122 ) plays an important role in the regulation of liver metabolism , but its intrinsic physiological functions require further clarification . This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a ( Mir122a–/– ) to infer Warburg-like effects . Elevated expression of MiR-122a target genes in Mir122a–/–mice , especially those encoding for metabolic enzymes , was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states . By definition of the similarity ratio , we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer , respectively , for hepatocytes of 2-month-old mice in normal and deficient states . The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect , and similarity of 75% to the experimental observation . We also used 2 , 6 , and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data . Furthermore , through a bioinformatics ( LINCS program ) prediction , BTK inhibitors and withaferin A could downregulate DDC expression , suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells . Cancer cell metabolism is an exciting field of biology that provides a novel approach for treating cancer [1–8] . For almost a century , researchers have known that cancer cells have an abnormal metabolism and utilize glucose differently than normal cells do . However , glucose uptake may reveal only part of a cancer’s metabolic system [1–8] . Cancer cells have become habituated to certain fuel sources and metabolic pathways ( “metabolic reprogramming” ) , profoundly changing how they consume and utilize nutrients such as glucose . Inhibiting key enzymes in these metabolic pathways can disrupt tumor cell proliferation and survival without affecting normal cells . The metabolic reprogramming of cancer cells is also linked to specific genetic alterations in oncogenes and tumor suppressor genes . Hence , a systems biology approach , which involves integrating genetic , protein-protein interaction and metabolic networks , may be a useful tool for discovering and developing novel targeted cancer therapeutics . A superior understanding of the genome-scale human metabolic network may lead to the identification of disease genes and related pathways , which may be more appropriate targets for drug development . The development of genome-scale human metabolic networks , such as Recon 1 and 2 [9 , 10] , the Edinburgh human metabolic network ( EHMN ) [11] , and human metabolic reactions [12 , 13] , has resulted in the emergence of network medicine . Network medicine aims to understand the structure and function of the human genome and to provide a connection between the genotype and phenotype [14] . Human metabolism is complex and very specialized in different tissues and cell types . Studies of the human metabolism have focused on reconstructing tissue-specific metabolic networks [13 , 15 , 16] . These previously mentioned genome-scale reconstructions of the human metabolic network are an excellent basis for reconstructing tissue-specific metabolic networks . HepatoNet1 , the first manually reconstructed tissue-specific network of human hepatocytes , was assembled according to two global reconstructions , Recon1 and EHMN , and metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [15] . This reconstructed network consists of 777 metabolites in eight compartments ( six intracellular and two extracellular ) and 2539 reactions , including 1466 transport reactions . The network was curated using more than 1500 primary articles , reviews , and biochemical textbooks . Recently , many algorithms , including the Model Building Algorithm ( MBA ) [17] and the metabolic Context-specificity Assessed by Deterministic Reaction Evaluation ( mCADRE ) method [18] , have been proposed for inferring tissue-specific subnetworks from generic genome-scale human metabolic networks . Two liver-specific metabolic networks , liverMBA and liverCADRE , generated using MBA and mCADRE , respectively , have been used to predict potential drug targets and improve metabolic flux predictions [19 , 20] . The developers of mCADRE claimed that liverCADRE exhibited similar or more improved coverage and higher functionality than the existing models . In addition to these two liver-specific metabolic networks for the normal liver , MBA and mCADRE have been used separately to generate metabolic networks for liver cancer . MicroRNAs have recently been discovered to be key metabolic regulators that mediate the fine tuning of genes that are involved directly or indirectly in cancer metabolism [21] . Mouse studies have revealed that microRNA-122 ( miR-122 ) , which accounts for 70% of the total miRNAs in the liver , plays a pivotal role in liver and has been implicated as a regulator of fatty acid metabolism . Reduced miR-122 levels are associated with hepatocellular carcinoma ( HCC ) , and miR-122 plays a crucial positive role in the regulating hepatitis C virus replication [22] . However , the intrinsic physiological roles of miR-122 remain largely undetermined . Tsai et al . demonstrated that mice lacking the gene encoding miR-122a ( Mir122a–/– ) ( hereafter referred to as Mir122a–/–mice ) are viable but developed temporally controlled steatohepatitis , fibrosis , and HCC [23] . However , how miR-122 affects the metabolic network of hepatocytes is unclear . This study aimed to reveal this metabolic reprogramming mechanism by integrating the flux balance analysis ( FBA ) of a genome-scale metabolic model of hepatocytes and the experimental data of Mir122a–/–mice . Several new targets and inhibitors , which could modulate the Warburg effect , are emerged from this integrated metabolomic analysis and warrant further investigation in a future clinical study . For the untargeted metabolomic analysis , 20 liver tissue samples including 10 control mice and 10 Mir122a–/–mice were extracted using the Folch method , and the aqueous phases were analyzed by LC-TOFMS in the electrospray positive-ion mode ( S1 Fig ) . In the metabolomic profiling , 1234 positive-mode features were identified and applied for SIMCA-P analysis . The orthogonal partial least squares discriminant analysis ( OPLS-DA ) score plot and loading plot showed remarkable separation between the controls and Mir122a–/–mice ( Fig 1A and 1B ) . The variable importance in the projection ( VIP ) values of those variables greater than 1 . 0 is shown in Fig 1C and Table 1 . Thirty-five metabolites with VIP values > 1 . 0 were included in the metabolite set enrichment analysis ( MSEA ) . The datasets were also analyzed using the Metaboanalyst platform . Fig 1D shows the metabolome view of the affected pathways . The results of the untargeted analysis revealed these metabolites to be important discriminators of the healthy controls and Mir122a–/–mice . A tissue-specific metabolic model of hepatocytes obtained from the supplementary data of Recon 2 and cell type-specific models [10] , hereafter referred to as the Recon 2-hepatocyte model , was applied to evaluate flux distributions under normal or miR-122 dysregulated conditions . In this study , the maximization of the ATP production rate was considered the cellular objective . According to the physiological data of mice reported by Trotman et al . [24] , we restricted the secretion rates of direct bilirubin and indirect bilirubin to 1 . 7 ≤ vdirect_bilirubin≤ 8 . 55 μmol/L/day and 0 ≤ vindirect_bilirubin≤ 6 . 84 μmol/L/day , respectively . A minimal medium containing the selected nutrients of glucose , ammonia , sulfate , and phosphate was commonly used to predict cell growth in the study of FBA . This work uses the data of Mir122a knockout mice from Tsai et al . [23 , 25] . All the mice used in this study were male mice of 2-month old . The wild-type and knockout mice are fed by the Laboratory Autoclavable Rodent Diet 5010 , which the ingredients are described in Materials and Methods . Tsai et al . [23 , 25] applied a miRNA-target interaction database to predict miR-122 target genes in mice and humans ( S2 and S3 Tables ) . In this study , using the KEGG and ExPASy databases , we determined that 20 genes from the set of miR-122 target genes directly encode enzymes listed in the Recon2-hepatocyte model . The target genes and their regulated reactions are shown in S4 Table . The elevated expressions of the 20 target genes induced by Mir122a deletion were applied to modulate the flux distributions in the normal and deficient states ( S2 Fig ) . We detected a group of 35 metabolites with significant variable importance for projection ( VIP ) scores > 1 ( S5 Table ) in the liquid chromatography–mass spectrometry ( LC/MS ) analysis . Of these , 12 metabolites had a decreased mass-to-charge ratio ( m/z ) , and 23 metabolites had an increased m/z ratio . Table 1 shows the similarity effect of the computational prediction for each miR-122 target gene compared with the data for the 35 metabolites . We observed that Ddc , the gene encoding 3 , 4-dihydroxy-L-phenylalanine ( L-DOPA ) decarboxylase ( DDC ) , exhibited the highest similarity ratio to the Warburg effect hypothesis ( 0 . 952 , S5 Table listed metabolites used for evaluation ) , and the experimental metabolomics profiling data ( 0 . 75 ) , as shown in Fig 2 . DDC , which is widely distributed throughout the body , is a pyridoxal-phosphate ( PLP ) -dependent enzyme that catalyzes L-DOPA to dopamine and 5-hydroxy-Ltryptophan ( 5-HTP ) to serotonin [26–28] . DDC primarily participates in the synthesis of amines that are involved in angiogenesis , cell proliferation , and differentiation [29 , 30] . Elevated DDC expression has been considered a potential novel biomarker for various cancer types , including neuroendocrine malignancies [31–33] , small-cell lung carcinoma [34 , 35] , neuroblastoma [36] , prostate cancer [37] , colorectal adenocarcinoma [38] and laryngeal cancer[39] . In this study , we investigated the role DDC in the metabolic reprogramming of cancer cells . As stated in the hypothesis of the Warburg effect , the production rates of metabolites in glycolysis , the tricarboxylic acid ( TCA ) cycle , and glutamine metabolism pathways can be altered by overexpression of a gene [1–8] . In this study , when DDC was fully overexpressed ( 100% ) , glucose uptake from the extracellular matrix and cellular pyruvate levels increased by fold changes ( FC ) of 3 . 15 and 1 . 17 , respectively ( Fig 3 ) . Most pyruvate was further converted into lactate ( 3 . 06-FC ) instead of being transported into the mitochondria ( 0 . 62-FC ) . Elevated DDC expression shifted liver metabolism toward glycolysis and lactate synthesis , which is in good agreement with the Warburg hypothesis ( aerobic glycolysis ) . Contrary to the Warburg effect , we detected a slightly increased production rate ( 1 . 02-FC ) of acetyl-coenzyme A ( acetyl-CoA ) in the mitochondria . The acetyl-CoA levels in the mitochondria were not affected possibly because of the conversion of other metabolites such as ketone bodies . Decreased oxaloacetate production ( 0 . 49-FC ) in mitochondria can potentially impair the TCA cycle and led to mitochondrial respiratory defects . In contrast , glutamine transported from the extracellular matrix was increased by 4 . 54-FC . Higher levels of glutamine were converted to glutamate ( 1 . 39-FC ) by glutaminase . This reaction occurs in tumor cells [23] and was detected in the experimental metabolomic profiling ( S5 Table ) . Glutamate was oxidized to α-ketoglutarate ( 1 . 52-FC ) , which then entered the TCA cycle generating higher citrate ( 1 . 15-FC ) , isocitrate ( 3 . 07-FC ) , and succinyl-CoA ( 1 . 12-FC ) levels and eventually , higher ATP levels . Such metabolic reprogramming indicates that the glutaminolysis pathway serves as an alternative pathway to compensate for the production of cellular ATP . Despite decreased production of oxaloacetate ( 0 . 49-FC ) , which is catalyzed by malate dehydrogenase , the malate level in mitochondria still increased by 1 . 51-FC . This result implies that malate can be converted to pyruvate by the malic enzyme , which has been confirmed to play a crucial role in glutamine metabolism in rapidly growing tissues and tumors [40–42] . Lipid metabolism plays a critical factor of metabolic reprogramming in tumorigenesis [23] . We observed an apparent increase in the intracellular cholesterol level and a decreased extracellular cholesterol level when Ddc was overexpressed . The computational prediction was consistent with the experimental result as observed from Tsai et al . [23] . Since miR-122 knockout mice have increased levels of DDC ( Fig 4C–4E ) , we then set up to determine the association between DDC and liver cancer . We used the database ( PORGgeneV2 , http://watson . compbio . iupui . edu/chirayu/proggene/database/index . php ) [43] to search for DDC in the liver cancer dataset and then performed the survival analysis . From the dataset of GSE10141 [43 , 44] , high expression of DDC is associated with a poorer prognosis for patients with liver cancer ( S4 Fig ) . A rational approach is to knock down DDC and then to perform microarray profiling of the knockdown cells to delineate the DDC-elicited signaling pathways . Alternatively , we can hypothesize that DDC knockdown cells may share similar gene expression patterns that result from certain drugs ( Fig 4A ) , which may potentially modulate DDC-elicited signaling . Thus , we accessed the Library of Integrated Network-based Cellular Signatures ( LINCS ) ( http://systemsbiology . columbia . edu/lincs ) , which contains 1 . 3 million L1000 microarray dataset of perturbational profiles spanning chemical compounds and gene knockdowns across multiple cell types . More importantly , LINCS provides a query interface to make inferences on the connections between the queries ( e . g . DDC shRNA ) and the internal ( e . g . chemical compounds ) gene expression profiles . We found that the gene expression profiles of several compounds had similar gene expression profiles with DDC shRNA . Of particular interest , withaferin-A and BTK inhibitor ( LFM-A13 ) , which share 91% and 92% identity , respectively , with the DDC knockdown gene expression profile ( Fig 4B ) . LFM-A13 , the BTK inhibitor in LINCS , is still in the pre-clinical development stage . Since the first FDA-approved BTK inhibitor is ibrutinib , we have also included ibrutinib in our assay . We examined the expression pattern of DDC in mir-122 knockout mice livers to explore the role of DDC . The results show upregulated profiles from 2 , 6 , and 11 months of mir-122 knockout mice liver data ( Fig 4C–4E ) . In addition , we also examined the role of BTK in the mir-122 knockout mice livers . Interestingly , P-BTK and BTK were upregulated in mir-122 knockout mice livers as early as 2 months of age . Moreover , LFM-A13 and ibrutinib are BTK inhibitors . Together , BTK inhibitors may be potential drugs for liver cancer therapy . We next first determined the IC50 values of two BTK inhibitors ( LFM-A13 and ibrutinib ) in Huh7 cells to test whether these compounds could modulate DDC expression level . The IC50 values of both drugs were >10 μM in Huh7 cells ( Fig 4F ) , whereas the IC50 of withaferin A in Huh7 cells was >2 μM ( Fig 4F ) . Treatment of Huh7 cells with LFM-A13 , ibrutinib , and withaferin A , but not sorafenib , which is the only FDA-approved drug for advanced HCC , could indeed result in downregulation of the protein expression level of DDC based on western blot analysis ( Fig 4G–4I ) . The Warburg effect , commonly observed in the metabolic reprogramming of cancer cells , is characterized by increased rate of glucose utilization and accumulation of lactate [45] . The findings of this study , which used 2-month-old Mir122a knockout mice for the modeling of metabolic reprogramming , addressed the disturbances in glucose utilization and accompanying pyruvate , lactate , and alanine metabolism at the pre-cancer stage ( Fig 3 ) . All the mice used in this work were male mice of 2-month old . It is an expansion of consideration of the ( so-called ) aerobic glycolysis and functional mitochondrial metabolism in supporting the energy-demanding biosynthetic pathways in cancer cells . Beyond that , this study also demonstrated that combined contribution of pyruvate and glutamine/glutarate/α–ketoglutarate was adapted and re-coordinated to drive TCA cycle for limited energy production ( including ATP and redox coenzymes formation ) ( Fig 3 and S3 Fig ) . In this metabolic reprogramming , biosynthetic pathways , such as cholesterol biosynthesis for tumor cell growth , were minimally retained . We selected the 20 genes listed in Fig 2 ( also in S4 Table ) to investigate other miRNAs that may co-regulate those genes . First , we identified experimentally verified miRNA-target pairs from the miRTarBase dataset ( http://mirtarbase . mbc . nctu . edu . tw ) and the starBase v2 . 0 ( http://starbase . sysu . edu . cn/ ) . Second , miRNA expression profiling of wild-type and Mir122a–/–mouse livers ( both 2-months old ) was performed using Small RNA sequencing [46] . We were able to identify miRNAs targeting 11 of the 20 genes with a total of 189 miRNA-target gene pairs . These genes are Acer2 , Cpox , Fech , Gys1 , Pafah1b1 , Pank3 , Pfkp , Rpia , Scd2 , Sgpl1 , Sptlc1 and Txnrd1 . Differentially expressed miRNAs ( expression ratio between Mir122a–/–and WT: 0 . 6≦KO/WT≧1 . 5 ) were found only in 40/189 pairs ( S6 Table ) . Most of the miRNAs in Mir122a–/–are expressed at low ( RPM<10 ) to moderate ( RPM 10–100 ) levels compared to high level of miR-122-5p in normal mouse liver ( RPM 21378 . 2 ) . Since miR-122 is a highly abundant liver-specific miRNAs , an imbalance of the miRNA homeostasis in Mir122a–/–liver is anticipated . In addition , multiplicity of miRNAs targeting one gene is well noted . Whether those low-to-moderate levels of miRNAs impacted on the gene expression is difficult to evaluate . Clearly our results favor the notion that miR-122 plays a major dominant role in regulating these target genes in normal liver . Ddc , PKM , and Urod exhibited the top three similarity ratios in Fig 2 . PKM encodes to pyruvate kinase which catalyzes the transfer of a phosphoryl group from phosphoenolpyruvate to ADP , generating ATP and pyruvate . This kinase exhibited the second high similarity ratio ( 0 . 857 ) to Warburg hypothesis ( metabolic reprogramming triggered by overexpression of Pkm was shown in S3 Fig ) ; this finding indicates that production rates for pyruvate and oxaloacetate in the mitochondria are consistent with the hypothesis . This enzyme exhibited a similarity ratio of 0 . 556 to the metabolic data . Urod provides instructions for the formation of uroporphyrinogen decarboxylase , which is involved in the production of heme . Heme is vital for all organs in the body , and it is most abundant in the blood , bone marrow , and liver . Heme is an essential component of iron-containing proteins called hemoproteins , including hemoglobin . From this computation , this enzyme achieved the second highest score ( 0 . 694 ) of the LC/MS experiment but exhibited the third highest ratio ( 0 . 810 ) of the Warburg effect . Furthermore , the computational prediction indicated that the secretion flux for cholesterol in the extracellular space to the extracellular matrix was also reduced due to overexpression of UROD and PKM , respectively . Four target genes in Fig 2 exhibited an infeasible solution for the computation when the genes were fully overexpressed . We were unable to attain a feasible solution for ALDOA if it was greater than 54% overexpressed to upregulate the corresponding reactions catalyzed by fructose bisphosphate aldolase . Its similarity ratio was 0 . 714 and 0 . 528 for the Warburg hypothesis and the experimental observation , respectively , with 54% overexpression . Pfkp encoded phosphofructokinase which catalyzes a rate-limiting step in glycolysis . It is highly regulated by small molecules for the promotion of glucose utilization for energy production , termination of glycolysis for gluconeogenesis initiation , or shunting hexoses into the pentose phosphate pathway . Phosphofructokinase should be downregulated due to the deficiency of miR-122a; otherwise , we could not obtain a feasible solution if it were assigned as upregulated . Its similarity ratio was 0 . 810 and 0 . 583 for the Warburg effect and the experimental observation , respectively , when Pfkp was 100% downregulated . Cpt1a could not up- or downregulate forward or backward reactions because it encodes as carnitine palmitoyltransferase 1A , which is present in the liver , to manipulate 85 fat acid oxidation reactions in the model . The Cpt1A enzyme is essential for fatty acid oxidation , a multistep process that breaks down fats and converts them into energy . Fatty acid oxidation takes place within mitochondria , which are the energy-producing centers in cells . Cpt1a needs to maintain oxidation-reduction at an equilibrium state if the forward reactions are upregulated , and its corresponding backward reactions should be upregulated simultaneously to maintain an equilibrium level . Here , Cpt1a was knocked out with fluxes of zero . Consequently , its similarity ratio was 0 . 714 and 0 . 583 for the Warburg effect and the experimental observation , respectively . Pank3 encodes a protein belonging to the pantothenate kinase family , which is highly expressed in liver and catalyzes the first committed step and is the rate-controlling enzyme in CoA biosynthesis in bacteria and mammals . Pantothenate is the essential precursor for CoA , which is a cofactor for a multitude of metabolic reactions including the oxidation of fatty acids , carbohydrates , pyruvate , lactate , ketone bodies , and amino acids . According to our computation , the regulatory action of Pank3 is similar to that of Cpt1a , which regulates the forward and backward reactions simultaneously to maintain CoA synthesis and catabolism in equilibrium . In this study , 21 metabolites , consisted of TCA cycle and glutamine metabolism pathways , were used to evaluate the Warburg effects ( S5 Table ) . Eighteen of these metabolites were obtained from hypotheses in the literature [1–8] . From the LC/MS experiments , three experimental metabolites , glutamine , glutamate , and alanine , were increased and consistent with Warburg hypothesis . From the computational prediction , glutamine transported from the extracellular matrix was increased ( 4 . 45-FC ) . A high level of glutamine was converted to glutamate by glutaminase . In addition , the increase of lactate and alanine was consistent with the results obtained from Hu et al . [47] that increased conversion of pyruvate to lactate and alanine by using hyperpolarized 13C-pyruvate in Myc-driven mouse liver cancer model . Furthermore , Pavlova and Thompson [48] described cancer-associated metabolic changes into six hallmarks . The article indicated that the import of an essential amino acid , leucine , through the plasma membrane localized neutral amino acid antiporter LAT1 , which is coupled to a simultaneous efflux of glutamine [49] . In such a manner , intracellular glutamine may facilitate the import of a broad range of LAT1 substrates , including leucine , isoleucine , valine , methionine , tyrosine , tryptophan , and phenylalanine [50] . We found that five amino acids , such as leucine , valine , methionine , tryptophan , and phenylalanine contained in the experimental metabolomics profiling data increased and were consistent with the model predicted . Using the online bioinformatics tool , LINCS , the gene expression profiles of withaferin A and BTK inhibitor share-gene expression profiles similar to the DDC knockdown profiles . Since LINCS has been terminated recently , similar result can be found in the new version of LINCS , CLUE ( https://clue . io/ ) . This analysis provides an opportunity to employ these available drugs ( or drug repurposing ) to target DDC expression . In fact , empirical evidence also suggests that withaferin A and BTK inhibitors can downregulate DDC , but not PKM2 , expressions ( Fig 4 ) . BTK inhibitors have emerged as crucial therapeutic agents for distinct cancer treatment . The first FDA-approved BTK inhibitor is ibrutinib . The indication for ibrutinib is for the treatment of patients with Mantle cell lymphoma , chronic lymphocytic leukemia , and one kind of non-Hodgkin’s lymphoma ( Waldenström’s macroglobulinemia ) . Moreover , there are still many innovative compounds in preclinical or clinical development , including GDC-0834 , CGI-560 , CGI-1746 , HM-71224 , CC-292 , ONO-4059 , and CNX-774 [51] , raising the possibility that some of these compounds might have effects similar to ibrutinib . Withaferin A has many functions , including antioxidative , anti-inflammatory , antiproliferative and apoptosis-inducing properties . Recently , many studies show that withaferin-A can reduce the growth of multiple tumor types in the mouse model [52] . To further elucidate the role of DDC , we knocked out DDC in Huh7 cell line via CRISPR/Cas9 system and then performed microarray profiling of the knockout cells . The differentially expressed gene signatures were used to query the ConsensusPathDB ( http://consensuspathdb . org/ ) [53] database to search for DDC-elicited signaling pathways . The metabolism pathway received the highest score than other pathways ( manuscript in preparation ) . Our data further extend the potential use of these drugs as metabolism regulators in liver cancer cells . One metabolic profiling dataset for human HCC [54] was also compared with the computational prediction of the Recon 2-hepatocyte model . According to the U . S . National Library of Medicine , the secretion rates of direct bilirubin and indirect bilirubin in humans are restricted by 0 ≤ vdirect_bilirubin≤ 5 . 13 mol/L/day and 5 . 13 ≤ vindirect_bilirubin≤ 27 . 36 mol/L/day , respectively . We applied 560 gene-encoded enzymes listed in the model to compute the flux distributions in the normal and cancer states . From the computation , 13 gene-encoded enzymes exhibited high similarity ratios to the Warburg effect ( S7 Table ) , and are shared by the Mir122a–/–mouse case and human HCC case . Four of them , DDC , PKM , ENTPD4 , and ALDOA , are miR-122 target genes . DDC scored the highest similarity ratio ( 0 . 905 ) to the Warburg effect and the experimental metabolomics profiling data ( 0 . 513 ) in human HCC case ( S7 Table ) . The metabolic reprogramming from the computation could be applied to predict the oncogenic behavior . A genome-scale human metabolic model can be applied to identify disease genes and disease pathways , offering more appropriate targets , such as DDC , for drug development . MicroRNAs mediate fine tuning of the genes that are directly or indirectly involved in cancer metabolism . In summary , this study integrated the genome-scale metabolic model of hepatocyte , namely Recon 2-hepatocye model , and experimental data of 2-month old Mir122a–/–mice to infer the metabolic reprogramming that was initiated in the early stages of cancer development . DDC has not only exhibited the highest similarity ratios to the biological hypothesis of Warburg effect and the experimental observation in Mir122a–/–mice , but also demonstrated its importance in human HCC cases . Moreover , the genome-scale metabolic model could be applied to rationally analyze flux distributions for the normal and dysregulated cell . Finally , the role of ibrutinib on metabolism in cancer warrants further investigation . The animal were euthanized by CO2 following the institutional guidelines . All the studies were conducted in accordance with the Guidelines for the Care and Use of Mammals in Neuroscience and Behavioral Research and were approved by Institutional Animal Care and Use Committee ( IACUC ) of National Yang Ming University . FBA is an in silico flux-based optimization model for predicting the metabolic flux distributions in genome-scale metabolic networks . Such an optimization problem usually includes a cellular objective , ( e . g . , maximization of cell growth ) . The biomass reaction actually contains in Recon 2-hepatocyte model , but it is a block reaction in the model . We therefore considered FBA with the maximization of ATP production as an objective in this study . {maxv ( cfTvf+cbTvb ) subjecttoN ( vf−vb ) =0vi=viReg , i∈ΩRegvjLB≤vj≤vjUB , j∉ΩReg ( 1 ) where vf and vb are the irreversible forward and backward fluxes , respectively , for the production of a metabolite such as ATP , N is an m×n stoichiometric matrix where m is the number of metabolites and n is the number of reactions , vjLB and vjUB are the positive lower and upper bounds of the jth flux , respectively , and viReg is the ith up- or downregulated flux due to the ith enzyme dysregulation . The value for the forward or backward flux is computed by the following equations: Up-regulationforvi , forvi , b:{vi , b/f=vi , b/fbasalvi , f/b=vi , f/bbasal+δ ( vi , f/bmax−vi , f/bbasal ) ( 2 ) Down-regulationforvi , forvi , b:{vi , b/f=vi , b/fbasalvi , f/b=vi , f/bbasal+δ ( vi , f/bmin−vi , f/bbasal ) ( 3 ) where vibasal is the basal flux , vimax and vimin are the maximum and minimum fluxes , respectively , at a normal state , and δ is the regulation strength parameter between 0 and 1 . The optimal flux distribution of the flux-balance problem expressed by Eq ( 1 ) is not unique , and there is a large set of alternative flux distributions with identical values for the objective function . We minimized the squared sum of all internal fluxes for FBA to ensure efficient channeling of all the fluxes through all pathways to eliminate the multiplicity of flux values due to the problem expressed in Eq ( 1 ) . The second optimization problem can be reformulated as the principle of flux minimization [55] if the equilibrium constant for each reaction is available . Such a problem is to using minimum enzyme activities to enhance cellular capacity . The minimizing Euclidean norm problem is expressed as: {minv∑i∈ΩInt ( vf , k ) 2+ ( vb , k ) 2subjecttoN ( vf−vb ) =0vi=viReg , i∈ΩRegvjLB≤vj≤vjUB , j∉ΩRegcfTvf+cbTvb≥z* ( 4 ) where z* is the maximum specific metabolite production rate obtained from the problem expressed in Eq ( 1 ) . The problem expressed in Eq ( 4 ) is a quadratic programming problem that can numerically achieve a unique solution . Flux balance equations in ( 1 ) and ( 4 ) omit the dilution term during cell growth . The dilution rate should be included in the mass balance equations of the intracellular metabolites to cope with cell growth [56 , 57] . The specific growth rate is generally in terms of a kinetic constant and concentration of uptake nutrients . Metabolite dilution flux balance analysis ( MD-FBA ) [58] and flux imbalance analysis [59] are applied to surmount such a weakness to predict flux distribution in genome-scale metabolic networks . Both methods can be applied to this study in order to improve predictability of flux distributions . However , the cell-growth rate in Recon 2-hepatocyte model is a block reaction so that the flux value is zero [10] . In the future , a liver-specific metabolic model has to be reconstructed to achieve a non-zero flux of cell growth rate to account for metabolite dilution . In the computational viewpoint , the production rate of a metabolite is involved in different compartments , and it can be calculated through a GSMM . However , this work applied an LC/MS experiment to obtain the metabolomic profiling for the normal and dysregulated cell . According to the protocol of LC/MS experiment , the liver tissues were minced in small chunks and were rapidly frozen in liquid nitrogen , and then the tissue was homogenized to prepare a sample to determine the metabolomic profiling . Such a homogenization was indicated that metabolites contained in different compartments was destroyed . As a result , LC/MC was applied to measure the homogenized metabolite concentrations . In order to compare with LC/MS experiments , the metabolite involved in different compartments has to sum up to yield the overall production rate of the metabolite which is an intracellular compound of the cell . The overall production rate ( rm ) of each intracellular compound at deficient and normal states is respectively evaluated as rm=∑i∈Ωc ( ∑Nij>0 , jNijvf , j−∑Nij<0 , jNijvb , j ) , m∈Ωm ( 5 ) where Nij is the stoichiometric coefficient for the ith metabolite participating in the jth reaction . An intracellular compound ( or metabolite ) exists in different compartments of the metabolic network; therefore , the rates for all compartments , Ωc , are summed to provide the production rate of the metabolite . The production rate is then applied to compute the fold change ( FC ) at deficient and normal states and to evaluate the similarity ratio between the computational results and experimental observations . The logarithmic FC ( LFCm ) for the mth metabolite and similarity ratio ( SR ) are respectively expressed as LFCm=log2 ( FCm ) =log2 ( rm , deficientrm , normal ) ( 6 ) SR=∑m=1NdataμmNdata ( 7 ) where the similarity indicator ( μm ) for each metabolite is defined as: μm={1 , sgn ( LFCm ) =sgn ( LFCmExp ) 0 , otherwise ( 8 ) where sgn is defined as the signum function . The similarity indicator is a qualitative comparison that we hypothesize the prediction is similar to the experiment if an increase/decrease of the overall production rates between deficient and normal states is consistence with the change for experimental results . The production rate of a metabolite obtained from the computation is not equal to the concentration of that metabolite achieved through LC/MS experiments . Rates of metabolites are in term of their regulated enzyme activities and metabolite concentrations . Such kinetic models can be used to predict concentrations if model parameters are given in advance . A genome-scale kinetic model is generally not available up to date . As a result , the constraint-based model can be applied to predict fluxes in the genome-scale metabolic network . In contrast to kinetic models of metabolism , a shortage of constraint-based approaches is the incapacity to predict metabolite concentrations , but it can be used to analyze the genome-wide flux distribution . In this study , we firstly compute the metabolite flux-sum distributions in the normal and deficient states , respectively . The flux-sum changes between these states are then compared with the changes of LC/MS metabolomics observations in the normal and cancer states . The similarity indicator in Eq ( 8 ) is used as a measure to inspect whether the trend of flux change is coincided with the trend of experimental observations and Warburg hypothesis , i . e . the similarity indicator is assigned to be one if the flux change in the normal and deficient states is similar to concentration change ( A toy example shown in S1 Table ) . The similarity ratio denotes the percentages of the computational predictions are similar to the experimental observations . As a result , the similarity ratio is used as an measure to explain variation of overall fluxes based on metabolite-centric approach alter from the normal state to the deficient situation . This study was not only used LC/MS metabolomic data of mice lacking Mir122a for evaluating the similarity ratio , Warburg hypothesis was also applied to compute the similarity ratio . Indeed , the Warburg effect accessed from literatures [1–8] hypothesizes that it could trigger the production rate of metabolite to be increase/decrease , not concentration . In this study , 21 metabolites , consisted of TCA cycle and glutamine metabolism pathways , were used to evaluate the Warburg effects ( S5 Table ) . We found three metabolites , glutamine , glutamate , and alanine , were also contained in LC/MS experiments , and their concentrations were increased and similar trend as Warburg hypothesis . Furthermore , Pavlova and Thompson [47] have recently reviewed cancer-associated metabolic changes to enhance the import of an essential amino acid , leucine , through the plasma membrane localized neutral amino acid antiporter LAT1 , which is coupled to a simultaneous efflux of glutamine . In such a manner , intracellular glutamine may facilitate the import of a broad range of LAT1 substrates , including leucine , isoleucine , valine , methionine , tyrosine , tryptophan , and phenylalanine . We found that five amino acids , i . e . leucine , valine , methionine , tryptophan , and phenylalanine contained in the mouse experimental metabolomics profiling data increased and were similar to the increasing fluxes of the hypothesis and model prediction . We additionally acquired metabolomics profiling data for human HCC [53] , and found that the trend of metabolic alternation was similar to Warburg hypothesis ( see S7 Table ) . All optimization problems were solved using the CPLEX solver accessed from GAMS on a 3 . 4 GHz Intel Core i7 CPU with 32 GB of RAM . The source code is available in the supporting information ( S1 File ) . A modified Folch’s method was used for hydrophilic and hydrophobic metabolite extraction [60] . Approximately 0 . 3 g of frozen liver tissue was homogenized in liquid nitrogen and transferred to a 20-mL glass tube . Subsequently , 6 mL of chloroform/methanol ( 2:1 , v/v ) solution and 1 . 5 mL of water were added . The mixture was vortexed four times for 30 s and subsequently centrifuged at 700 × g for 30 min at 4°C . The upper phases ( hydrophilic phase and water soluble phase ) were transferred to new glass tubes and then dried under a stream of nitrogen . The residues were collected and stored at −80°C . The residues were suspended in 100 μL of 95:5 water/acetonitrile and centrifuged at 14 , 000 × g for 5 min . The clear supernatant was collected for liquid chromatography–mass spectrometry ( LC/MS ) analysis . Liquid chromatographic separation was achieved on a 100-mm×2 . 1 = mm Acquity 1 . 7-μm C8 column ( Waters Corp . , Milford , USA ) using the ACQUITY UPLC system ( Waters Corp . , Milford , USA ) . The column was maintained at 45°C and a flow rate of 0 . 5 mL/min . Analytes were eluted from LC column using with a linear gradient: 0–1 . 25 min: 1%-50% B; 1 . 25–2 . 5 min: 50%-99% B; 2 . 5–5 . 0 min: 99% B; 5 . 1–6 min: 1% B for re-equilibration . The mobile phase was 0 . 1% formic acid in water ( solvent A ) and acetonitrile ( solvent B ) . The eluent was introduced into the Synapt G1 high-definition mass spectrometer ( Waters Corp . , Milford , USA ) operated in the positive ion mode . It is a time of flight mass spectrometer ( TOFMS ) and this system is less than 5 ppm mass error in specification . The specification was checked in every study to make sure the mass accuracy . The following conditions were used: the desolvation gas was set to 700 l/h at a temperature of 300°C , the cone gas was set to 25 l/h , and the source temperature set at 80°C . The capillary voltage and cone voltage were set to 3 , 000 V and 35 V , respectively . The MCP detector voltage was set to 1 , 650 V . The data acquisition rate was set at 0 . 1 s with a 0 . 02 s interscan delay . The data were collected in centroid mode from 20 to 990 m/z . For the long-term study , all analyses of the LCTOFMS were acquired using the lock spray to ensure accuracy and reproducibility . For accurate mass acquisition , a lock-mass of sulfadimethoxine at a concentration of 60 ng/mL and a flow rate of 6 μL/min ( an [M+H]s+ ion at 311 . 0814 Da in ESI positive mode ) were used . The lock spray frequency was set at 10 s . For the purpose of quality control ( QC ) in LC-MS performance was also prepared . As to the QC sample , 10 μl aliquot of supernatant that had been extracted of each sample was mixed and the LC-MS experiment was performed together with the samples and replicates from the same LC-MS condition . The QC sample was applied before and after injection of every 20 samples . Each sample was analyzed six replicates . We checked six replicates in the QC and each sample . Each sample including QC was shown highly reproducibility in principal component analysis ( PCA ) and orthogonal partial least square analysis ( OPLS-DA ) plots ( S5 Fig ) . Raw mass spectrometric data were processed using MassLynx V4 . 1 and MarkerLynx software ( Waters Corp . , Milford , USA ) . The intensity of each mass ion was normalized with respect to the total ion count to generate a data matrix including the retention time , m/z value , and the normalized peak area . The multivariate data matrix was analyzed by SIMCA-P software ( version 13 . 0 , Umetrics AB , Umea , Sweden ) . Orthogonal projection to latent structure-discriminant analysis ( OPLS-DA ) was carried out before the Pareto scaling was applied . This software had been used for multivariate data analysis and representation . Precise molecular mass data for metabolites , which showed significant differences between two groups , were then submitted for database searching , either using either an in-house database or online HMDB ( http://www . hmdb . ca/ ) or the METLIN ( metlin . scripps . edu/index . php ) database . For identifying specific metabolites , standards were subject to UPLC-MS/MS analyses under the conditions that were identical to those of the profiling experiment . MS/MS spectra were collected and confirmed by chemical standards or database match from HMDB or METLIN . The Huh7 cell line was obtained from Dr . Zhong-Zhe Lin , National Taiwan University Hospital , Taiwan . Huh7 cells were cultured in DMEM and supplemented with 10% fetal bovine serum ( FBS , Invitrogen ) , 10 U/ml penicillin , 1% nonessential amino acids and 2 mM L-glutamate in an incubator with 5% CO2 at 37°C . Cells ( 5 × 105 cells ) were seeded in 6-cm tissue culture dishes for overnight incubation and were then treated with ibrutinib ( Santa Cruz Biotechnology , sc-483194 ) , LFM-A13 ( Enzo , BML-EI295 ) , and withaferin A ( Enzo , BML-CT104 ) , respectively , for 24 hours . Mice liver tissues were harvested from C57BL/6 wildtype and mir-122 knockout mice at 2 , 6 and 11 months of age . All samples were lysed in lysis buffer ( 25 mM Tris-HCl pH 7 . 6 , 137 mM NaCl , 1 mM EDTA pH 8 . 0 , 1 mM EGTA pH 8 . 0 , 1% Triton X-100 , 2 mM sodium pyrophosphate , 25 mM β–glycerol phosphate ) supplemented with protease inhibitor and phosphatase inhibitor . All samples were denatured by heating at 95°C for 5 minutes . The total protein was electrophoresed on 10% , 12% SDS-polyacrylamide gel and transferred onto PVDF membranes ( Millipore ) . The membrane was blocked with 5% non-fat milk at room temperature for 1 hour . The membrane was incubated with the primary antibody at 4°C overnight . They were washed with TBST three times ( 10 minutes per time ) . The membrane was incubated with the HRP-conjugated secondary antibody at room temperature for 1 hour . They were washed with TBST three times ( 10 minutes per time ) . The proteins were detected using an enhanced ECL .
For almost a century , researchers have known that cancer cells have an abnormal metabolism and utilize glucose differently than normal cells do . Aerobic glycolysis or the Warburg effect in cancer cells involves elevated glucose uptake with lactic acid production in the presence of oxygen . MicroRNAs have recently been discovered to be key metabolic regulators that mediate the fine tuning of genes that are involved directly or indirectly in cancer metabolism . MicroRNA-122 ( miR-122 ) plays an important role in the regulation of liver metabolism , but its intrinsic physiological functions require further clarification . This study integrated the genome-scale metabolic modeling ( GSMM ) of hepatocytes and mouse experimental data with germline deletion of Mir122a ( Mir122a–/– ) to infer Warburg-like effects . In silico and in vivo observations indicated that DDC overexpression induced Warburg effect in hepatocyte . Furthermore , through a bioinformatics prediction , BTK inhibitors and withaferin A could downregulate DDC expression , suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "cell", "physiology", "carbohydrate", "metabolism", "medicine", "and", "health", "sciences", "metabolic", "networks", "enzymology", "cell", "metabolism", "glucose", "metabolism", "physiological", "processes", "metabolomics", "metabolites", "warburg", "effect", "network", "analysis", "enzyme", "metabolism", "energy", "metabolism", "in", "cancer", "cells", "pharmacology", "drug", "metabolism", "enzyme", "chemistry", "computer", "and", "information", "sciences", "energy", "metabolism", "pharmacokinetics", "biochemistry", "cell", "biology", "physiology", "biology", "and", "life", "sciences", "metabolism" ]
2017
Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a
Sand fly saliva plays a crucial role in establishing Leishmania infection . We identified adenosine ( ADO ) and adenosine monophosphate ( AMP ) as active pharmacologic compounds present in Phlebotomus papatasi saliva that inhibit dendritic cell ( DC ) functions through a PGE2/IL 10-dependent mechanism . Herein , we prepared a mixture of ADO and AMP in equimolar amounts similar to those present in the salivary-gland extract ( SGE ) form one pair of salivary glands of P . papatasi and co-injected it with Leishmania amazonensis or L . major into mouse ears . ADO+AMP mimicked exacerbative effects of P . papatasi saliva in leishmaniasis , increasing parasite burden and cutaneous lesions . Enzymatic catabolism of salivary nucleosides reversed the SGE-induced immunosuppressive effect associated with IL-10 enhancement . Immunosuppressive factors COX2 and IL-10 were upregulated and failed to enhance ear lesion and parasite burden in IL 10-/- infected mice . Furthermore , nucleosides increased regulatory T cell ( Treg ) marker expression on CD4+CD25- cells , suggesting induction of Tregs on effector T cells ( T eff ) . Treg induction ( iTreg ) was associated with nucleoside-induced tolerogenic dendritic cells ( tDCs ) expressing higher levels of COX2 and IL-10 . In vitro generation of Tregs was more efficient in DCs treated with nucleosides . Suppressive effects of nucleosides during cutaneous leishmaniasis were mediated through an A2AR-dependent mechanism . Using BALB/c mice deficient in A2A ADO receptor ( A2AR–/– ) , we showed that co-inoculated mice controlled infection , displaying lower parasite numbers at infection sites and reduced iTreg generation . We have demonstrated that ADO and AMP in P . papatasi saliva mediate exacerbative effects of Leishmania infection by acting preferentially on DCs promoting a tolerogenic profile in DCs and by generating iTregs in inflammatory foci through an A2AR mechanism . Leishmaniasis is a vector-borne disease transmitted exclusively by sand fly bites in which the host is inoculated with saliva and regurgitated parasites during the blood meal [1] . There is evidence that Phlebotomine saliva enhances the infectivity of many different Leishmania species [2–5] . This can be attributed to numerous substances within the saliva with pharmacologic properties that induce vasodilatation , anticoagulation , anti-inflammation , and immunoregulation [6] . These effects are associated with the capacity to selectively inhibit several macrophage functions , including Ag presentation and NO and hydrogen peroxide production , thus inhibiting the ability of macrophages to kill intracellular Leishmania major [7–13] . Furthermore , in naïve animals or those not previously exposed to sand fly bites , vector saliva inhibits production of protective type 1 cytokines such as IL-12 and IFN -γ [3 , 14 , 15] while it enhances production of IL-10 , IL-4 , IL-6 , and PGE2—all of which enhance the survival of Leishmania parasites [16–18] . Thus , identification of active salivary constituents could help to prototypes for use in development of vaccine strategies to control pathogen transmission . We are currently isolating bioactive compounds from saliva of several bloodfeeding arthropods including Phlebotomine vectors . Systemic pre-treatment of mice with salivary gland extracts ( SGE ) 3 from the Old World species Phlebotomus papatasi and Phlebotomus duboscqi inhibited neutrophil migration during OVA-induced immune peritonitis [19] . By exploring the specific mechanisms of saliva activity , we found that Phlebotomine saliva acted preferentially on APCs and thus inhibited the ability of dendritic cells ( DCs ) to present Ags to T cells . These anti-inflammatory effects seemed to depend on the sequential production of PGE2 and IL-10 by DCs , as both cytokines acted in an autocrine manner [19] . P . papatasi SGE could therapeutically control collagen-induced arthritis pathogenesis [20] . Adenosine ( ADO ) and AMP were purified and identified as the active pharmacologic components in SGE responsible for immunomodulatory activity . Indeed , ADO and AMP act preferentially on DCs to block their Ag-presentation function , which interferes with Th17 cell activation and consequently suppresses the inflammatory immune response [20] . DCs are key cells in induction of immune responses to Leishmania by acting as both host cells and APCs , modulating specific cellular immune responses and , after appropriate activation , also operating as effector cells for intracellular parasite killing [21–23] . DC-produced cytokines such as IL-1 , TNF-α , and IL-12p40 are needed for immune responses and appropriate control of Leishmania infections [24 , 25] . Moreover , release of mediators such as IL-10 and TGF-β by DCs and IL-4 by T lymphocytes might promote survival and multiplication of parasites in infected cells [26 , 27] . Interestingly , ADO has a broad range of effects on inflammatory leukocytes , including DCs: ADO downregulates production of pro-inflammatory mediators and expression of costimulatory markers , which diminish DC capacity to initiate and amplify inflammatory immune responses [28] . Thus , it is plausible that nucleosides present in P . papatasi SGs could play a central role in the establishment of Leishmania infections by modulating DC function . In the current study , we demonstrate that ADO and AMP in the same amounts found in a single pair of P . papatasi salivary glands facilitate establishment of Leishmania amazonensis infection in the vertebrate host . The exacerbative effect was strictly associated with generation of tolerogenic DCs ( tDCs ) and induction of regulatory profile in effector T cells ( Teffs ) through an A2AR-dependent mechanism . All experiments were conducted in accordance with the National Institutes of Health ( NIH ) guidelines on the welfare of experimental animals and with the approval of the Ethics Committee of the School of Medicine of Ribeirão Preto ( Number 196/2011 ) . Female C57BL/6 ( wild type; WT ) , C57BL/6-IL-10-/- , BALB/c , and BALB/c-A2AR-/-mice , 18–22 g in weight , were housed in the animal facility of the Department of Biochemistry and Immunology , School of Medicine of Ribeirão Preto , University of São Paulo ( Brazil ) , in temperature-controlled rooms ( 22°–25°C ) and received water and food ad libitum . Stationary-phase promastigote forms of Leishmania amazonensis ( 106 parasites or for some infections 103 parasites ) or Leishmania major ( 106 parasites ) were diluted in 10 μl of a mixture containing 1 nmol of ADO plus 1 nmol of AMP ( both from Sigma , St . Louis , MO ) in PBS , which are similar amounts to those present in the extract from one pair of P . papatasi SGs [20] . In some experiments , mice were infected with parasites in the presence of SGE diluted in PBS that was or was not pretreated with adenosine deaminase ( ADA; 4 . 3 U; Sigma ) . Ear lesion size—defined as the difference in thickness between the infected ear and the non-infected contralateral ear—was monitored weekly using digital calipers ( Mitutoyo , Suzano , SP , Brazil ) . Parasite load was determined by quantitative limiting dilution assay as previously described [29] . Ears from infected mice were collected and incubated at 37°C for 1 h in RPMI-1640 medium with 2 mM of L-glutamine , 100 U/ml of penicillin , 100 μg/ml of streptomycin ( all from Gibco , Grand Island , NY ) and 500 μg/ml of liberase CI ( Roche , Basel , Switzerland ) . Tissues were processed in Medcons by a Medimachine ( both from BD Biosciences , San Diego , CA ) . After processing , the cells were filtered through a 50-μm filter , viability was assessed by trypan blue exclusion , and cell concentrations were adjusted ( 1x 106 cells/ tube ) . Immunostaining was performed with anti-CD3 , anti-CD4 , and anti-CD25 Abs conjugated to FITC , PE , or PerCP fluorochromes . For regulatory T cell ( Treg ) phenotyping , CD4+CD25+ cells were stained with anti-FoxP3 , anti-CD103 , anti- CD39 , and anti-CD73 Abs conjugated to PECy7 , APC , or Alexa700 . For intracellular staining , cells were permeabilized with a Cytofix/ Cytoperm kit ( BD Biosciences ) according to the manufacturer’s instructions . For in vivo analyses of DC maturation , cells were harvested , stained with CD11c and MHC class-II Abs , conjugated to Alexa488 and PE or control isotypes , and characterized by flow cytometry to determine surface expression profiles . For all analyses , the results were compared to those obtained with cells stained with isotype control Abs ( all Abs were from BD Biosciences and eBiosciences , San Diego , CA ) . Cell acquisition ( ~ 2 x 105 cells / tube ) was performed on a FACSort flow cytometer with CellQuest software ( BD Biosciences ) . Data were plotted and analyzed with CellQuest and FlowJo ( Tree Star , Ashland , OR ) software . Single-cell suspensions of draining retromaxillary lymph nodes ( LNs ) were prepared aseptically , diluted to a concentration of 2 × 106 cells/ml , and dispensed into 48-well plates in a total volume of 500 μl of complete RPMI-1640 medium ( 1 × 106 cells/well; Gibco ) with or without soluble Leishmania Ag ( 5 μg/ml ) . Cell culture supernatants were harvested after 72 h of culture at 37°C in 5% CO2 , and levels of IL-10 in the supernatants were determined by ELISA with commercial kits ( BD Biosciences and R&D Systems , Minneapolis , MN ) . For the co-culture assays , CD4+CD25-or CD4+CD25+ cells from the draining LNs of the nucleoside- or PBS-treated groups were isolated using a CD4+CD25+ Regulatory T cell kit ( Miltenyi Biotec , Auburn , CA ) in accordance with the manufacturer’s instructions , and a purity of ~ 95% was obtained for each T subset . For the in vitro co-culture assays , CD4+CD25+ cells were added to or not wells of CD4+CD25-cells at a ratio of 5:1 ( CD4+CD25-: CD4+CD25+ ) ; the wells were subsequently stimulated with plate-bound α-CD3 ( 2 μg/ml ) plus α-CD28 ( 1 μg/ml ) or incubated in medium alone for 96 h in a total volume of 200 μl per condition . The supernatants were harvested to measure IL-10 production . Bone marrow-derived cells ( BMDC ) were isolated from 6- to 8-wk-old C57BL/6 naïve mice and cultured with murine GM-CSF ( 20 μg/ml; Peprotech , Rocky Hill , NJ ) . On d 3 , half of the supernatant was gently removed and replaced with the same volume of supplemented medium . On d 6 , non-adherent cells were collected and positively selected with anti-CD11c magnetic beads according to the manufacturer’s instructions ( Miltenyi Biotec ) to eliminate residual macrophage and granulocyte contamination . Flow cytometric evaluation of the purified BMDCs showed that 90% of cells expressCD11cinterim or high . BMDCs ( 1 × 106 /ml ) were incubated in RPMI-1640 supplemented with 10% FBS with or without ADO+AMP for 1 h . The cells were subsequently infected with GFP-expressing promastigote forms of L . amazonensis ( 1 × 107 parasites/ml ) . Supernatants were collected to measure TNF-α and IL-10 production by ELISA . BMDC treated with ADO+AMP or medium for 3 h were stimulated overnight with LPS ( 50 ng/ml ) and then cultured with freshly isolated naïve CD4+CD25-cells in the ratio of 1:10 ( DC:lymphocytes ) under polarizing conditions: rmTGF-β ( 5 ng/ml ) , rmIL-2 ( 100U/ml ) , anti-IFN-γ ( 10 μg/ml ) and anti-IL-4 ( 10 μg/ml ) at 37°C in 5% CO2 for 7 d . As differentiation control , natural Tregs ( nTregs ) ( CD4+CD25+ ) or Th0 ( CD4+CD25- ) were cultured in the presence of IL-2 ( 100 U/ml ) for T cell maintenance . Lymphocytes were then washed and phenotyped for expression of surface markers using mAb-specific against CD39 , CD73 , CD103 and FOXP3 ( BD Biosciences and eBioscience ) . Total RNA was isolated from ears of mice co-inoculated with ADO+AMP plus parasites at wk 11 post infection ( p . i . ) or BMDCs pre-incubated with ADO+AMP after 24 h of stimulation with L . amazonensis ( 5 parasites:1 cell ) using the Illustra RNAspin Mini ( GE Healthcare , Buckinghamshire , UK ) . Gene expression was normalized to expression of the GAPDH gene . COX2 primer sequences are as follows: GAPDH forward: 5ˊ-TGCAGTGGCAAAGTGGAG AT-3ˊ , reverse: 5ˊ-CGTGAGTGGAGTCATACTGGAA-3ˊ; COX2 forward: 5ˊ-GTGGAAAAA CCTCGTCCAGA-3ˊ , reverse: 5ˊ-GCTCGGCTTCCAGTATTGAG-3ˊ; IL-10 forward: 5ˊ-TGG ACAACATACTGCTAACCG-3ˊ , reverse: 5ˊ-GGATCATTTCCGATAAGG CT-3ˊ; TGF-β forward: 5ˊ-ACCGCAACAACGCCATCTAT-3ˊ , reverse: 5ˊ-TCAAAAGCAAGCCACTCA GGC-3ˊ; and IDO forward: 5ˊ-AAGCAATCCCCACTGTATCC-3ˊ , reverse: 5ˊ-CAATGCTTT CAGGTCTTGACG-3ˊ . To quantify A2A receptor ( A2AR ) and A2BR expression , total mRNA was extracted from DC culture harvested 24 h p . i . . A2AR forward: 5ˊ-TTCTTCGCCTGCTTT GTCCT-3ˊ , reverse: 5ˊ-ATACCCGTCACCAAG CCATT-3ˊ; and A2BR forward: CTGCTC ATAATGCTGGTGATCT , reverse: ATCAGTTCCATGCGCTGA . Data are expressed as the mean ± SEM and are representative of 2–4 independent experiments . Results from individual experiments were not combined because they were analyzed individually . The means from the different groups were compared by analysis of variance ( ANOVA ) followed by Tukey's honest significant difference ( HSD ) test . Statistical significance was set at p<0 . 05 . To investigate whether ADO and AMP present in P . papatasi saliva are constituents that may exacerbate leishmaniasis , C57BL/6 and BALB/c mice were intradermally infected in the ear with 1 × 106 promastigote forms of L . amazonensis in the presence or absence of equimolar amounts of ADO and AMP present in one pair of SGs . As reported by Ribeiro et al . [30] , in this salivary extract , ADO and AMP are detected on the order of 1 nmol per pair of glands . Co-inoculation of parasites with nucleosides exacerbated infection in both strains of mice when compared with the control group ( inoculated with parasite plus PBS ) ( Fig 1 ) . Animals co-inoculated with parasites and nucleosides showed a significant increase in ear thickness and ulcerative lesion starting at week 8 p . i . ( BALB/c , p<0 . 045; C57BL/6 , p<0 . 01 ) ( Fig 1A and 1D ) that progressed until the animals’ deaths at wk 12 p . i . ( Fig 1C and 1F ) . The number of parasites present in the ear lesion , as well as in draining LNs , was also greater in the group co-inoculated with parasite and nucleosides compared with the group co-inoculated with parasite and PBS ( Fig 1B and 1E ) . To determine the potential effect of nucleosides on the establishment of L . amazonensis infection , we infected BALB/c mice with low numbers of L . amazonensis ( 103 promastigote forms ) in the presence or absence of adenosine and AMP to mimic the natural model of infection . Lower numbers of parasites promoted reduced and delayed lesion development in mice coinoculated with ADO+AMP or PBS over time ( Fig 1G ) . Despite similar rates of edema in both groups ( ADO+AMP and PBS ) , mice that received nucleosides showed higher parasite titers in the ears and lymph nodes than mice inoculated with parasites in PBS ( Fig 1H ) . Our data are consistent with a previous study showing that Lutzomyia longipalpis SGE maintains the persistence of L . braziliensis within the skin without interfering with lesion size during low-dose infection [31] . P . papatasi is not a natural vector of L . amazonensis , but it is transmitted by the Lutzomyia genus and does not contain salivary nucleosides [30] . To address the impact of nucleosides on species that are normally transmitted by Phlebotomus papatasi , we infected BALB/c mice with L . major ( 106 parasites / mice ) and adenosine+AMP . The mixture of nucleosides promoted the exacerbative effect of saliva on L . major infection . During the first 6 weeks after infection , the ear lesions were similar between PBS and ADO+AMP coinoculated mice . Afterward , the lesions progressed in both groups , but they were clearly pronounced in the group that was coinoculated with ADO+AMP ( Fig 1I ) . The larger lesions found in nucleoside coinoculated mice were associated with impaired control of parasite growth; this group presented higher parasite loads in both ear lesions and draining lymph nodes at the 10th wpi ( Fig 1J ) . Thus , these data suggest that the amounts of ADO and AMP in one pair of SGs of P . papatasi are sufficient to establish cutaneous Leishmaniasis causing species . To verify whether both nucleosides are the salivary compounds responsible for vector-induced establishment of infection , SGEs ( 1 pair of glands/ear ) from P . papatasi—previously treated or not with ADA , an enzyme that catabolizes ADO [20 , 32]—were co-inoculated with the Leishmania parasite . As control groups , ADA or PBS was co-inoculated with L . amazonensis . We found that the sizes of lesions were significantly larger in mice co-inoculated with parasite plus SGE compared with those that received parasite plus PBS control ( Fig 2A ) and that they were correlated with the numbers of parasites present in the ear and draining LNs ( Fig 2B ) . Treatment of SGEs with ADA abolished the exacerbative effect of SGEs during L . amazonensis infection , resulting in reduced ear lesions ( Fig 2A ) as well as reduced parasite numbers in the ear and draining LNs ( Fig 2B ) . In addition , no differences were observed either in lesion or parasite burden among ADA , SGE-treated ADA , or PBS groups . Expression of IDO , arginase 1 , COX2 , and IL-10 have been reported to play a key mechanism that triggers several immunosuppressive effects and can be induced by ADO [20 , 28] . We therefore examined whether such factors are modulated by nucleosides during infection . The results reveal higher mRNA expression of IDO , arginase 1 , COX2 , and IL-10 for the ears of mice infected with parasites and PBS compared with those of uninfected mice ( Fig 3 ) . Furthermore , while IDO ( Fig 3A ) and arginase 1 ( Fig 3B ) expression levels were similar , COX2 ( Fig 3C ) and IL-10 ( Fig 3D ) mRNA levels were upregulated in ears of mice co-inoculated with parasite and ADO+AMP . Enhancement of mRNA for COX2 and IL-10 was 2-fold and two- to three-fold , respectively ( Fig 3C and 3D ) . We previously demonstrated that ADO—already present in saliva and/or generated by AMP metabolism by CD73 expressed in DCs—most likely accounts for most , if not all , anti-inflammatory activity presented by P . papatasi SGEs through a mechanism dependent on PGE2-induced IL-10 release [20] . In addition , IL-10 mRNA was upregulated in ears of mice infected with parasite plus nucleosides ( Fig 3D ) . Attempting to address the role of IL-10 in exacerbation of infection induced by nucleosides , we measured production of IL-10 in culture supernatant of total cells from draining LNs of C57BL/6 co-inoculated with parasites plus ADO+AMP or PBS and re-stimulated them in vitro with soluble Leishmania Ag ( SLA ) . Stimulation with SLA did not induce significant amounts of IL-10 in culture supernatant of draining LN cells from mice co-inoculated with PBS , compared with control ( medium ) ( Fig 3E ) . In contrast , the supernatant of draining LN cells from mice co-inoculated with parasites and nucleosides showed high levels of IL-10 after SLA stimulation , compared with the PBS-treated group ( Fig 3E ) . Co-inoculation of parasites and ADO+AMP in IL-10-/-mice resulted in lack of exacerbative effect by nucleosides during L . amazonensis infection , as observed by the reduction of lesion size ( Fig 3F and 3G ) and a decrease in the number of parasites present in the ear and draining LNs ( Fig 3H ) . Interestingly , despite the fact that infected IL-10-/-mice showed reduced ear lesion size , they developed a severe ulcerative and necrotic lesion even in the presence or absence of nucleosides ( Fig 3G ) , suggesting that the lack of regulation of the immune response induced by IL-10 favors ear cartilage destruction due to excessive inflammatory response triggered during infection by L . amazonensis . In fact , we did not detect parasites in the ears of IL-10-/-mice with or without nucleosides ( Fig 3H ) . Together , our data suggest that IL-10 released at the site of infection strongly contributes to exacerbative activity of nucleosides during Leishmania infection . Further investigating the mechanism by which nucleosides exacerbated L . amazonensis infection , we evaluated the phenotype of T cells isolated from the ears of mice inoculated with parasites and ADO+AMP or PBS . Nucleoside treatment did not interfere in expression of CD4+ T cells compared with the control group ( Fig 4A ) . A similar effect was observed regarding the CD4+CD25+ population ( Fig 4A ) . Expression of Treg phenotypes such as FoxP3 , CD103 , CD39 , and CD73 ( Fig 4B ) in the CD4+CD25+ cell population was likewise similar in both groups . Unexpectedly , expression of markers characteristic of Tregs in the CD4+CD25-population was significantly increased , as observed by the higher expression of CD103 , CD39 , and CD73 in nucleoside-treated animals compared with the PBS-treated group ( Fig 4C , S1 Fig ) . These data suggest that nucleosides from P . papatasi saliva may induce the Treg phenotype in effector T lymphocytes . Because salivary nucleosides potentiated IL-10 production ( Fig 3D and 3E ) and mediated susceptibility to the infection ( Fig 3F–3H ) , we addressed whether the CD4+CD25-expressing Treg markers in the CD4+CD25-population could contribute to nucleoside-induced IL-10 production . Therefore , purified CD4+CD25-T cells from draining LNs were cultured with plate-bound αCD3 ( 2 μg/ml ) plus αCD28 ( 1 μg/ml ) or medium with or without CD4+CD25+ . As expected , CD4+CD25-T cells from infected mice stimulated with plate-bound anti-CD3 induced showed enhanced production of IL-10 ( Fig 4D ) . Furthermore , the culture supernatant from CD4+CD25-T cells from mice infected and treated with nucleosides produced higher levels of IL-10 after polyclonal stimulation than cultures that lacked nucleosides ( Fig 4D ) . The addition of autologous CD4+CD25+ cells to CD4+CD25- cultures potentiated IL-10 production when the cells were derived from the nucleoside group but not when they were isolated from the PBS group . These observations indicate that iTregs may contribute to the immunosuppressive effects of nucleosides through IL-10 release . We also evaluated the in vitro effect of nucleosides on the replicative ability of parasites when cultured with DCs . In the presence of ADO+AMP , parasite growth was enhanced ( Fig 5A ) . The increase was approximately 33% compared to the control ( PBS ) group ( Fig 5A ) . Moreover , production of pro-inflammatory mediators such as TNF-α was reduced , whereas production of IL-10 was enhanced in cultured DCs infected with the parasite in the presence of nucleosides when compared with the PBS–treated group ( Fig 5B ) . Conversely , the exacerbative effect of salivary nucleosides in neither parasite growth ( Fig 5C ) nor the inhibitory effect of TNF ( Fig 5D ) were observed in IL-10-\-mice . As several factors—including IL-10 , TGF-β , IDO , and PGE2—might modulate DC function by promoting differentiation into a tolerogenic profile [33 , 34] , we evaluated expression of factors related to a tolerogenic profile such as IDO , TGF-β , IL-10 , and COX2 . Administration of nucleosides in BMDC culture significantly increased levels of COX2 and IL-10 mRNA expression ( Fig 5E ) , which correlated with in vivo data ( Fig 3C and 3D ) . This increase was approximately 89% for COX2 and 88% for IL-10 when compared with the control group ( infected with parasite only ) . In contrast , IDO levels were not changed , and TGF-β mRNA levels were downmodulated during infection independently of presence of nucleosides . Furthermore , DCs isolated from draining LNs from mice co-inoculated with nucleosides and parasites exhibited an immature phenotype , showing a reduction in percentage and numbers of MHC-II molecules on the surface of CD11c+ cells compared with the PBS control group ( Fig 5F; S1 Fig ) . We further tested whether tDCs generated by nucleosides have the potential to induce Tregs . As expected , under Treg-polarizing conditions , CD4+CD25-cultured with BMDC/PBS upregulated their CD39 , CD73 , CD103 , and FoxP3 expression when compared with Th0 cells . Interestingly , the proportion of CD39 , CD73 , and CD103 was found to increase without affecting FOXP3 expression when CD4+CD25-cells were cultured with BMDC/ADO ( Fig 6 ) . The enhancement was similarly likewise observed on nTregs that expressed not only CD39 , CD73 , and CD103 but also FoxP3 ( Fig 6 ) . Altogether , the data suggest that nucleosides may modulate tDCs capable of inducing iTreg generation . Among ADO receptors , A2AR and A2BR mediate immunosuppressive effects by coupling to a G-protein and activating adenylyl cyclase , thereby generating the second messenger cyclic AMP that downregulates host cell activation [35] . Thus , mRNA levels of A2AR and A2BR were analyzed in the ears of infected mice . Transcripts for A2AR were upregulated in the ears of mice infected only with parasites and were highly expressed in ears of mice co-inoculated with parasite plus nucleosides ( Fig 7A ) . The transcript profile of A2BR mRNA was not altered in either the nucleoside- or PBS-treated group , suggesting that ADO mediates immunosuppressive action through the A2AR . To further examine the role of A2AR on the suppressive effect of salivary nucleosides , we infected mice lacking A2AR with L . amazonensis in the presence of ADO+AMP or PBS . Absence of A2AR abrogates the exacerbative effect of nucleosides on mice during disease , as observed by ear lesion development ( Fig 7B ) and harboring fewer parasites in lesion and draining lymph node ( Fig 7C ) . In addition , no changes were observed in lesion or parasite burden among BALB/c-PBS , A2AR-/--PBS , or A2AR-/--ADO+AMP groups ( Fig 7B and 7C ) . The lack of an exacerbative effect of nucleosides in the A2AR-/-group was followed by a committed induction of Treg markers in the CD4+CD25-population . While a slight reduction of CD73 and CD39 expression was observed in A2AR-/--ADO+AMP compared with BALB/c-ADO+AMP , there was a remarkable decrease in CD103 expression , although that remained enhanced compared with A2AR-/--PBS ( Fig 7G ) . Interestingly , the percentage of the CD4+CD25+ subset was reduced in A2AR-/-independently of nucleosides ( Fig 7D ) , suggesting the involvement of A2AR signaling on nTreg generation ( 35 ) . Several studies have shown that sand fly saliva plays a key role in the establishment of Leishmania infections in vertebrate hosts through inhibition of several immune functions [1] . Among the pharmacologic substances involved in this inhibition , we recently identified ADO and AMP as the P . papatasi saliva constituents that inhibit activation and function of DCs [20] . Thus , we addressed whether ADO and AMP were the P . papatasi saliva components responsible for establishment of Leishmania infections in vertebrate hosts . Co-inoculation of parasites with nucleosides promoted the same disease exacerbation profile as total saliva , which suggests that these could be the constituents involved in establishment of Leishmania sp infections . Deamination of salivary nucleosides with ADA—an enzyme that catabolizes ADO—markedly abolished the exacerbative effects of SGEs during leishmaniasis . Despite the fact that P . papatasi not being a natural vector of L . amazonensis , which is transmitted by Lutzomyia flaviscutellata , this vector can transmit L . amazonensis under laboratory conditions . Salivary gland extract from other species , such P . papatasi and P . sergenti , could establish Leishmania amazonensis infection by promoting lesions as rapidly and as large in size as those produced by L . longipalpis [36] . Furthermore , proteins from Lutzomyia longipalpis , LJM11 and LJM19 , induce immunity against different species of Leishmania sp ( L . major , L . infantum and L . braziliensis ) [37] . Our data showed that , similar to L . amazonensis infection , adenosine and AMP also promote an exacerbative effect during L . major infection . We do not rule out the possibility of other salivary components ( such as proteins , prostaglandins , etc . ) that may contribute to the exacerbative role of saliva in leishmaniasis , but we believe that the strongest immunomodulatory effects of P . papatasi saliva are at least partly mediated by nucleosides . Although different species present different salivary constituents , some anti-inflammatory properties may be similar among them . For example , the saliva from the Old World species Phlebotomines P . papatasi and P . duboscqi acts mainly on dendritic cells and induces the production of IL-10 by a mechanism dependent on PGE2 . In turn , PGE2 acts in an autocrine manner to reduce the antigen-presenting ability of DCs [19] . Previous studies have also shown in vitro and in vivo examples of Lutzomyia longipalpis saliva promoting IL-10 , PGE2 and TGF-β production by macrophages and T cells , which exacerbates Leishmania infection [38] . Moreover , the genetic ablation of IL-10 prevents the detrimental effect of Lutzomyia longipalpis SGE on both Leishmania major and L . amazonensis infections [39 , 40] . Our data showed that a significant increase in IL-10 production was observed in culture supernatants of draining LNs from animals co-inoculated with parasites and nucleosides . Furthermore , IL-10 deficiency ( IL-10-/-mice ) reversed the immunosuppressive effects of salivary nucleosides during infection; however , ablation of IL-10 promoted significant tissue damage independently of nucleoside treatment . This damage did not correlate with parasite numbers but instead resulted from an excessive inflammatory response . Studies have shown the potent anti-inflammatory effects of IL-10 by demonstrating several functions including the ability to limit tissue damage during infections and the ability to regulate the duration and intensity of immune inflammatory reactions [41] . Thus , understanding how the substances present in P . papatasi saliva , such as AMP and adenosine , are involved in the exacerbation of infection in a fully experimental model may explain the consistent exacerbative role of saliva in leishmaniasis . Tregs limit the magnitude of effector responses against Leishmania spp . , which can result in a failure to properly control parasitic infections [42] . Tregs express high surface levels of CD39 and CD73 , and ADO generation is a mechanism by which Tregs exert their suppressive effects [43] . NECA ( a synthetic ADO analog ) or an A2AR agonist could increase expression of Treg markers FoxP3 , CD39 , CD73 , and CTLA-4 in the CD4+CD25-population in addition to expanding the FoxP3- , CD39- , CD73- , and CTLA-4-expressing CD4+CD25+ cell population [44] . We present evidence that the nucleosides from sand fly saliva could generate iTregs at the infection site . Co-inoculation of parasites plus nucleosides did not increase the numbers of nTregs ( CD4+CD25+FoxP3+ ) but increased the levels of CD103 , CD73 , and CD39 expression on CD4+CD25-cells . The high surface levels of CD39 and CD73 on Teffs ( CD4+CD25- ) help to generate ADO in the extracellular compartment by cleaving AMP in P . papatasi saliva , thus contributing to exacerbation of Leishmania infections as a consequence of IL-10 production . Indeed , IL-10 was substantially produced by iTregs generated in response to nucleosides , and this phenotype was pronounced when these cells were co-cultured with autologous nTregs . iTregs could suppress the proliferation of effector T cells in a cell contact–independent fashion . Key cytokines that have been associated with the suppressive activity of iTregs include IL-10 [45] and TGF-β[46] , which are crucial for continuous suppression of the effector T cells [47] that are involved in pathogen restriction , such as Th1 and Th17 [48] . IL-10 released peripherally by iTreg cells can sustain tolerance by converting naive T cells to the next generation of FoxP3+cells [47] . Thus , it is possible that IL-10—when secreted by salivary nucleoside-generated iTregs—contributes to the exacerbation of leishmaniasis . iTreg generation depends on activation of conventional CD4+ T cells by tDCs . tDCs are characterized by low surface expression of costimulatory molecules such as MHC-II , CD80 , CD86 , and CD40 and high expression of CD39 [33] . tDCs promote alterations in the immune system by inducing anergy or deletion of autoreactive T lymphocytes or even by inducing Treg generation [49 , 50] . tDC co-cultured CD4+ T cells exhibited increased levels of CD25 , CTLA-4 , FoxP3 , and CD39 expression and responded weakly when stimulated with Ag [34] . Of interest is that a similar tDC phenomenon was observed when DCs were incubated with ADO+AMP plus parasites , thus establishing a direct relationship between salivary nucleosides , Treg generation and , ultimately , the exacerbation of leishmaniasis . Previously , we demonstrated that ADO from P . papatasi SGE could upregulate CD73 surface expression and downregulate MHC-II and CD86 surface expression on DCs both in vitro and in vivo [19 , 20] . In the present study , DCs from draining LNs of animals co-inoculated with nucleosides and parasites exhibited a semi-mature phenotype with downregulated surface MHC-II expression and reduced production of pro-inflammatory cytokines . Furthermore , administration of ADO on DC culture promoted generation of regulatory markers on the CD4+CD25-subset . Several factors—including IL-10 , prostaglandin E2 , TGF-β , and vitamin D3—modulate DC function and favor tDC differentiation [34 , 51 , 52] . PGE2 , a lipid mediator synthesized by COX2 , promotes DC-mediated production of several suppressive factors such as IL-10 and IDO [53] . Interestingly , our data show that parasite infection in the presence of nucleosides did not alter IDO and TGF-β levels but induced expression of IL-10 and COX2 mRNA both in vitro and in vivo . We previously reported that P . papatasi SGEs inhibit immune peritonitis by sequential production of PGE2 and IL-10 , which acted in an autocrine manner on DC function [19] . Likewise , ADO and AMP in P . papatasi SGE exhibited anti-inflammatory activities against collagen-induced arthritis by blocking DC Ag presentation and secretion of pro-inflammatory cytokines . Strikingly , we demonstrated that ADO could enhance PGE2 production from LPS-stimulated BMDCs [20] . Thus , it is plausible that P . papatasi ADO-induced secretion of SGE IL-10 and PGE2 could induce a tDC profile , thus inhibiting DC function and ultimately contributing to establishment of an infection . ADO effects are mediated by four surface receptors—A1R , A2AR , A2BR , and A3R—which are present on many cell types . Among these , A2AR and A2BR regulate multiple physiologic responses including the anti-inflammatory and immunosuppressive effects of ADO . In fact , genetic ablation or pharmacologic inhibition of A2AR or A2BR leads to excessive immune responses [54 , 55] . Here we show that A2AR , but not A2BR , was highly expressed in the ears of mice co-inoculated with parasites and nucleosides . The immunosuppressive activity of ADO during leishmaniasis is mediated through an A2AR-dependent-mechanism , indicated by genetic deletion of the receptor , which leads to abrogated intensification of the infectious process mediated by salivary nucleosides . This phenomenon strictly correlated with a lack of induction of Treg generation . Although we did not evaluate the sequential production of PGE2/IL-10 as a result of A2AR signaling on DCs , we have strong evidence to support this pathway . We previously reported that blocking A2AR with a selective antagonist ( 8 , 3 , cloroesterylcafeine ) prevented inhibitory effects of SGEs on DC function during collagen-induced arthritis [20] . Furthermore , both ADO and an A2AR agonist enhanced PGE2 and IL-10 production by LPS-stimulated BMDCs [20] . Therefore , it seems likely that A2AR is responsible for the effects of ADO on DCs . Likewise , it was recently demonstrated that an ADO A2AR agonist attenuated acute kidney injury by inducing tDCs [56] . In conclusion , the results presented here indicate that ADO and AMP—which are present in P . papatasi SGEs—mediate the immunosuppressive effects of saliva during leishmaniasis . ADO and AMP act through A2AR to induce a tDC profile by sequential production of PGE2 and IL-10 . Both mediators could also act in a paracrine manner to induce Tregs from Teff populations , thus leading to suppression of the immune response . Understanding the molecular mechanisms induced by salivary components such as ADO and AMP—which lead to suppression of effector responses against pathogens—will help not only to understand disease pathogenesis but also to develop new vaccine strategies for cutaneous leishmaniasis .
Leishmania parasites are transmitted to their vertebrate hosts by infected Phlebotomine sand flies during the blood meal of the flies . During the Leishmania transmission , the saliva is inoculated together with parasites and exhibit several pharmacological compounds that facilitate blood feeding , interfering on homeostasis and avoiding inflammation . Thus , these compounds allow the establishment of pathogen infection . We recently identified adenosine ( ADO ) and adenosine monophosphate ( AMP ) as major immunomodulatory compounds present within the Old World sand fly species Phlebotomus papatasii , which protected mice from extreme inflammatory insults . ADO limits the magnitude of immune response by displaying a potent anti-inflammatory activity . Here , we demonstrated that ADO and AMP present in Phlebotomus papatasi saliva are involved in the establishment of parasite infection . Such nucleosides act through adenosine A2A receptor ( A2AR ) , inducing a tolerogenic profile on dendritic cells ( tDC ) that may generate regulatory T cells differentiation , thus leading to suppression of the immune response and parasite survival . The identification of the active salivary constituents could serve as a strategy for the development of new vaccines to control pathogen transmission .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[]
2015
Nucleosides Present on Phlebotomine Saliva Induce Immunossuppression and Promote the Infection Establishment
Buruli ulcer ( BU ) is a cutaneous infectious disease caused by Mycobacterium ulcerans . The exact mode of transmission remains elusive; yet , some studies identified environmental , socio-sanitary , and behavioral risk factors . The purpose of this study was to assess the association of such factors to contracting BU in Tiassalé , south Côte d’Ivoire . A case-control study was conducted in 2012 . Cases were BU patients diagnosed according to clinical definition put forth by the World Health Organization , readily confirmed by IS2404 polymerase chain reaction ( PCR ) analysis prior to our study and recruited at one of the health centers of the district . Two controls were matched for each control , by age group ( to the nearest 5 years ) , sex , and living community . Participants were interviewed after providing oral witnessed consent , assessing behavioral , environmental , and socio-sanitary factors . A total of 51 incident and prevalent cases and 102 controls were enrolled . Sex ratio ( male:female ) was 0 . 9 . Median age was 25 years ( range: 5–70 years ) . Regular contact with unprotected surface water ( adjusted odds ratio ( aOR ) = 6 . 5; 95% confidence interval ( CI ) = 2 . 1–19 . 7 ) and absence of protective equipment during agricultural activities ( aOR = 18 . 5 , 95% CI = 5 . 2–66 . 7 ) were identified as the main factors associated with the risk of contracting BU . Etiologic fractions among exposed to both factors were 84 . 9% and 94 . 6% , respectively . Good knowledge about the risks that may result in BU ( aOR = 0 . 3 , 95% CI = 0 . 1–0 . 8 ) and perception about the disease causes ( aOR = 0 . 1 , 95% CI = 0 . 02–0 . 3 ) showed protection against BU with a respective preventive fraction of 70% and 90% . Main risk factors identified in this study were the contact with unprotected water bodies through daily activities and the absence of protective equipment during agricultural activities . An effective strategy to reduce the incidence of BU should involve compliance with protective equipment during agricultural activities and avoidance of contact with surface water and community capacity building through training and sensitization . Buruli ulcer ( BU ) is an infectious skin disease caused by the environmental mycobacterium , Mycobacterium ulcerans . It is the third most common mycobacterial disease in the world in immunocompetent individuals , after tuberculosis and leprosy [1–3] and the second one in Côte d’Ivoire after tuberculosis [4] . It occurs at any age but the majority of sufferers are children aged below 15 years [5–7] , mainly in tropical and subtropical regions , in rural marshy areas [8–11] . According to the World Health Organization ( WHO ) , the countries most affected by BU in the past 10 years were Benin , Côte d’Ivoire , and Ghana in Africa; French Guyana in Latin America; and Australia and Papua New Guinea in Oceania [12] . The reservoir of M . ulcerans seems to be environmental , but the exact mode ( s ) of disease transmission remain to be elucidated [13 , 14] . There are multiple endemic foci of BU in Côte d’Ivoire , distributed throughout the country . The total number of cases reported between 2004 and 2014 was 19 , 145 [12] . In 1997 , during the first national survey , 10 , 382 cases were identified with a mean national prevalence of 0 . 32 per 1 , 000 inhabitants [4] . Data suggest that national strategies for the management of BU do not reach the most heavily affected rural communities . Areas around cities such as Bouaké in central Côte d’Ivoire , Daloa in the west-central part of the country , and Tiassalé in the southern part are particularly affected . In 1998 , a high prevalence of BU ( up to 22% ) was found in some villages of Bouaké and Daloa [4] and from 2004 to 2007 , 112 cases of BU were recorded in a single village ( Sokrogbo ) of the district of Tiassalé [15] . Several epidemiologic studies have been conducted in Africa and some other parts of the world to identify risk factors for M . ulcerans disease . Frequently reported risk factors are the contact of individuals with stagnant or slow flowing surface water through swimming , fishing , laundry , washing dishes , water supply , etc . [16–20] , wearing short clothes during agricultural activities [21 , 22] , and agricultural land use [23] . Protecting factors have also been identified by those studies . BU risk reduction was associated with the use of protected water sources , hygiene practices such as the use of bath soap , alcohol use for wound care and for cleaning body areas concerned by insect bites , and wearing long clothing ( long-sleeved shirts and pants , boots , and gloves ) for agricultural activities [24 , 25] . In Côte d’Ivoire , very few studies [5 , 8] on risk factors associated to BU have been conducted . Ahoua et al . [5] showed in 2009 in the regions of Bouaké , Man , and Daloa that the occurrence of BU was significantly associated with the use of unprotected water ( ponds , creeks , rivers and dams ) and living or practicing agricultural activities nearby aquatic ecosystems . Earlier in 1995 , Marston et al . [8] revealed the association of BU to agricultural activities in the region of Daloa . Wearing long pants was a protecting factor . In addition to the aforementioned risk factors , the role of insect bites in the transmission of M . ulcerans has been extensively studied worldwide and in Africa [11 , 15 , 17 , 21 , 26 , 27] . In Côte d’Ivoire , for example , Doannio et al . [15] revealed the molecular signatures of M . ulcerans in the tissues of two water bugs ( genera Micronecta and Diplonychus ) identified as potential vectors in the transmission of M . ulcerans in the village of Sokrogbo ( Tiassalé district ) . In Benin , from a 1-year mosquitoes and aquatic insects sampling and analysis by qPCR , M . ulcerans was detected in around 8 . 7% of aquatic insects but never in mosquitoes ( larvae or adults ) or in other flying insects [27] , although previous studies [17 , 21 , 26] indicated a role of mosquitoes as vectors in the transmission of BU . Another 1-year longitudinal sampling and analysis of aquatic macro-invertebrates and vertebrates in Cameroon [11] showed the presence of M . ulcerans in nearly all taxonomic groups of the aquatic community and it was approximately evenly distributed among the whole community . To date , the precise mode of transmission of BU remains elusive . It has been assumed that the pathogen is transmitted to humans by direct contact of injured skin with contaminated water or through biting of some aquatic insects . Against this background , identification of risk factors associated with the onset of BU are crucial for prevention and control of BU . Those risk factors may vary from one region to another based on environmental , socio-economic , and behavioral patterns . The region of Tiassalé is located in the forest-savannah transition zone in southern Côte d’Ivoire , crossed from North to South by two main rivers ( i . e . , Bandama and N’zi ) . The region , which , before 1980 , was ranked among the minor zones of BU , gradually became an important focus of BU shortly after the construction of a hydroelectric dam in the late 1970s . Indeed , Tiassalé became a wetland , characterized by subsistence farming , including lowland rice cultivation and swamps . Generally speaking , there are only few epidemiologic studies pertaining to BU in Côte d’Ivoire [5 , 8] . In the region of Tiassalé , apart from one study on the potential vectors of BU [15] , no investigations on risk factors were carried out . The ecologic or environmental characteristics ( wet , marshy areas ) and behavioral patterns ( agriculture , water access for household ) of that region might explain the high endemicity of BU . The main goal of the current study was to deepen our understanding of the transmission process of BU in Tiassalé for an efficient control of the disease . Specific objectives were ( i ) to assess risk factors of BU in the district of Tiassalé; ( 2 ) to determine etiologic and preventive fractions among exposed groups; and ( 3 ) to suggest efficient control strategies . This research was carried out in the frame of a project entitled “Ecohealth approach in water and health management under climate change: adaptation strategies to drought and flooding events in four countries in West Africa” , implemented from 2009 to 2013 . In Côte d’Ivoire , the National Ethics Committee cleared the research protocol ( reference no . 5383/MSHP , dated 28 October 2009 ) . In addition , agreement and a letter of support were obtained from the district medical officer at Tiassalé to collect data in the health centers of the district . Due to high illiteracy rates among rural dwellers in Tiassalé , oral informed consent was obtained from adults ( cases and controls ) or from parents ( or legal guardians ) of any individual aged below 18 years ( cases and controls ) , in the presence of an eye witness ( health worker ) before enrolment and interview . The ethics committee explicitly approved this consent procedure . Participation was voluntary , and hence , people could withdraw anytime without further obligation . In Côte d’Ivoire , the treatment of BU is free of charge according to national guidelines [28 , 29] and cases were recruited and interviewed when they came for their daily free treatments . A case-control study was conducted in the district of Tiassalé . Incident and prevalent cases were recruited between18 August and 10 September 2012 at the hospital and rural health centers of the district while they were seeking care . Cases were defined as any BU patient diagnosed according to WHO clinical definition [14 , 30] and confirmed by IS2404 polymerase chain reaction ( PCR ) analysis conducted at the Institut Pasteur in Abidjan . Patients of all ages and both sex were enrolled , most of whom lived in the district of Tiassalé and presented at the local health centers or the hospital . Controls were defined as patients with diseases other than BU who were seeking care at the same hospital or health centers as the cases . Controls were randomly selected and matched to cases to the nearest 5 years , sex , and type of residency ( rural or urban ) . Two controls were selected for each case . The district of Tiassalé is located in southern Côte d’Ivoire , extending from latitude 5°32' N to 6°24' N , and from longitude 4°29' W to 5°14' W . The district is composed of two sub-prefectures: Tiassalé and Taabo . In Taabo , a hydroelectric dam was constructed across the Bandama River in the late 1970s that formed an impoundment of approximately 69 km2 [31–33] ( Fig 1 ) . According to the General Census of Population and Housing of 2014 , the total population of the district of Tiassalé was 263 , 495 [34] . The climate is tropical and humid . The average annual rainfall is 1 , 740 mm with an average annual temperature of 26 . 6°C [35 , 36] . The population of the Tiassalé district is predominantly rural and people are mainly engaged in subsistence farming . The size of the sample was estimated using EpiInfo ( version 3 . 5 . 3 ) sample calculation tool . We considered an unprotected surface water exposure frequency of 25% [5 , 8]; set alpha to 5% , and a power to 80% [22] . Our aim was to identify risk factors with an odds ratio ( OR ) of 3 or higher . Hence , a minimum of 50 cases and 100 controls were required . Cases were recruited at the hospital of the city of Tiassalé and at the health centers of the villages of Taabo , Ahondo , Kotiéssou , Léléblé , N’Doucy , N’Zianouan , and Sokrogbo , all located in the district of Tiassalé . At the hospital of Tiassalé , the research team met the district medical officer who introduced them to the coordinator of BU control in the district , also responsible of the treatment of cases at the hospital , and to nurses in charge of BU treatment in the villages . In each health center , the research team came in the morning ( from 7 a . m . to noon ) , stayed with the BU treatment team and recruited within persons coming for their daily treatment . For each case , two controls were recruited in the same center at the reception desk , by a two-stage sampling method [5 , 37 , 38] . Having explained the purpose of the study to case-matched patients waiting for consultation at the desk , numbers were associated to each patient having accepted to participate in the study . The two controls were chosen at random within the patients with numbers . When only two case-matched patients were available at the moment of selection , they were selected . In case of absence of matching patients , they were recruited when new patients came or the following days . Patients were interviewed after their consultation and care . After having obtained oral informed witnessed consent , with the BU care givers as witness , a pre-tested questionnaire was administered to cases and controls to collect information on their socio-demographic status ( e . g . , age , sex , education , and marital status ) and their knowledge , attitude , and practices ( e . g . , agricultural practices , wearing protective clothing during such activities , swimming , fishing , living and working place , source of drinking water , vaccination against Bacilli Calmette-Guérin ( BCG ) , etc . ) . BCG vaccination was assessed by identifying the presence of the scar on the left shoulder around the deltoid region . Clinical features of cases were also assessed , including clinical forms and categories , location of lesions , signs , and symptoms . A questionnaire was administrated by trained field enumerators either in French or translated to one of the local languages ( i . e . , Baoulé and Malinké ) . If need be , a community health worker assisted the field enumerators during the interviews . Data quality control was systematically conducted on all questionnaires . Data were processed and analyzed using EpiInfo , version 3 . 5 . 3 ( Centers for Disease Control and Prevention; Atlanta , United States of America ) . BU was the dependent variable , while socio-demographic factors , knowledge , attitude , and practices of participants , environmental patterns of their living and working places were independent variables . All variables were described through proportions . Univariate analysis was used to describe the association between BU and independent variables . Statistical significance was determined by consulting 95% confidence intervals ( CIs ) , checking whether or not 1 was included for the observed ORs . Multiple conditional logistic regression analysis using a step down backward elimination process was performed to identify the factors that are significantly associated with BU firstlyand secondly to control possible confounding factors . At each regression , factors associated to BU with a p-value of the Wald test ( Z statistic ) greater 0 . 25 were eliminated . We then removed , one by one , the explanatory variables with p-values between 0 . 05 and 0 . 25 until the final model with variables associated to BU with a p-value less than or equal to 0 . 05 . The etiological fraction among people exposed to risk factors ( EFe ) and the preventive fraction among people exposed to protective factors of BU ( PFe ) were estimated . Table 1 shows the main socio-demographic and clinical characteristics of cases . Among the 51 BU cases , 24 ( 47 . 1% ) were males , thus the sex ratio ( male/female ) was 0 . 9 . The age of the BU cases ranged between 5 and 70 years with a median age of 25 years . About half of the BU cases were in the age range of 15–35 years . Among adult BU cases , the main socioeconomic activity is subsistence farming . The proportion of agricultural activities among controls was significantly lower ( 45 . 1% versus 28 . 4%; p<0 . 05 ) . Among the 51 BU cases interviewed , 29 ( 56 . 9% ) had no formal school education . The respective proportion among controls ( 39 . 2% ) was significantly lower ( p<0 . 05 ) . Most cases of BU recruited ( 96 . 0% ) were prevalent cases ( Table 1 ) . We found that 64 . 7% of cases were vaccinated against BCG . The first symptom of BU in most of cases interviewed ( 86 . 3% ) was the appearance of a small hard nodule on the skin . Oedematous forms , as another early sign of BU , were cited by another 13 . 7% of the cases . The main observed lesions at time of data collection were ulcers ( 96 . 1% ) , most frequently located on the lower limbs ( 76 . 5% ) or upper limbs ( 17 . 5% ) with a predominance of lesions of category II ( 51 . 0% ) , characterized by a lesion diameter of 5–15 cm ( Fig 2 ) . Most of BU patients ( 84 . 3% ) reported that their care through the existing health system in the district of Tiassalé was provided free of charge , while 15 . 7% of cases reported specific costs incurred for medical bandages and compresses . The majority of cases ( 90 . 0% ) used traditional medicine as the first means of care . Two-third ( 36/51; 66 . 6% ) of BU cases came at a health center for their first consultation more than 2 months after the onset of the disease; 29 . 4% between 1 and 2 months , and only 5 . 8% reached a health center less than 1 month after disease onset . Regular contact with unprotected water points ( i . e . , pond , creek , river , and dam ) was associated with the occurrence of BU ( adjusted OR ( aOR ) = 6 . 5 , 95% CI = 2 . 1–19 . 7 ) with an etiologic fraction ( EFe ) of 84 . 9% ( Table 3 ) . This contact with the water points is made through agriculture activities and fishing ( aOR = 6 . 3 , 95% CI = 1 . 8–21 . 9 ) ( S2 Fig ) and washing/bathing/swimming activities ( aOR = 7 . 5 , 95% CI = 2 . 0–27 . 8 ) ( S3 Fig ) with respective EFe of 84 . 1% and 86 . 7% . Also the absence of protective equipment ( e . g . , boots , gloves , long sleeved shirts , and pants ) for agricultural activities or in contact with surface water was associated with a higher risk of contracting BU ( aOR = 18 . 5 , 95% CI = 5 . 2–66 . 7 ) and an EFe of 94 . 6% . A good knowledge of people on the risk factors of BU ( aOR = 0 . 3 , 95% CI = 0 . 1–0 . 8 ) and a good perception about BU causes ( aOR = 0 . 1 , 95% CI = 0 . 02–0 . 3 ) were protective against the disease with respective preventive fractions ( PFe ) of 70% and 90% . Our study showed that the main risk factors for BU in the region of Tiassalé in south Côte d’Ivoire is the contact with unprotected water bodies through daily activities such as agriculture ( e . g . , rice cultivation and fishing ) , laundry , and bathing . A good knowledge on the disease transmission process and the disease causes is likely to protect against it . Compliance with protective equipment during agricultural activities and/or contact with surface water and community capacity building through training and sensitization on BU emerge as key strategies for the prevention of BU in the district of Tiassalé and potentially elsewhere in Côte d’Ivoire . Importantly , these measures could help avoid up to 95% of BU cases .
In Côte d’Ivoire , West Africa , Buruli ulcer ( BU ) is the second leading cause of mycobacterial infection after tuberculosis . Moreover , Côte d’Ivoire is one of the most affected countries worldwide by BU . Studies suggest that the reservoir of this mycobacterial infection is environmental , but the exact mode of disease transmission is still not known . The main strategy for the control of BU is early detection of cases and to treat them with antibiotics . In order to improve our understanding of the risk for contracting BU , which would allow primary prevention of the disease , a case-control study was conducted in 2012 in the district of Tiassalé , located in the southern part of Côte d’Ivoire , where the rain forest meets the savannah . We found that regular contact with unprotected surface water was an important factor associated with the risk of contracting BU . Such water contacts occur during agricultural activities , as well as washing , bathing , and swimming practices . An effective strategy to prevent BU in the district of Tiassalé–and perhaps in other endemic areas–will have to focus on improved access to clean water at the household , and sensitization and education for better practices in subsistence agriculture .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[]
2016
Socio-Environmental Factors Associated with the Risk of Contracting Buruli Ulcer in Tiassalé, South Côte d’Ivoire: A Case-Control Study
Rabies is a neglected zoonotic disease . There is a sparsity of data on this disease with regard to the incidence of human and animal disease in many low and middle income countries . Furthermore , rabies results in a large economic impact and a high human burden of disease . Kazakhstan is a large landlocked middle income country that gained independence from the Soviet Union in 1991 and is endemic for rabies . We used detailed public health and veterinary surveillance data from 2003 to 2015 to map where livestock rabies is occurring . We also estimate the economic impact and human burden of rabies . Livestock and canine rabies occurred over most of Kazakhstan , but there were regional variations in disease distribution . There were a mean of 7 . 1 officially recorded human fatalities due to rabies per year resulting in approximately 457 Disability Adjusted Life Years ( DALYs ) . A mean of 64 , 289 individuals per annum underwent post exposure prophylaxis ( PEP ) which may have resulted in an additional 1140 DALYs annually . PEP is preventing at least 118 cases of human rabies each year or possibly as many as 1184 at an estimated cost of $1193 or $119 per DALY averted respectively . The estimated economic impact of rabies in Kazakhstan is $20 . 9 million per annum , with nearly half of this cost being attributed to the cost of PEP and the loss of income whilst being treated . A further $5 . 4 million per annum was estimated to be the life time loss of income for fatal cases . Animal vaccination programmes and animal control programmes also contributed substantially to the economic losses . The direct costs due to rabies fatalities of agricultural animals was relatively low . This study demonstrates that in Kazakhstan there is a substantial economic cost and health impact of rabies . These costs could be reduced by modifying the vaccination programme that is now practised . The study also fills some data gaps on the epidemiology and economic effects of rabies in respect to Kazakhstan . Rabies is a fatal viral zoonotic disease largely transmitted to humans from bites by infected animals . Rabies is currently registered in over 100 countries in all continents except Australia and Antarctica . The disease is characterized by neuroencephalitis with 100% case fatality ratio once clinical signs present . Over 55 , 000 people and over 1 million animals die from rabies annually throughout the world . Direct losses from rabies amount to over EURO 4 billion each year [1] . Human rabies presents a serious public health threat in Kazakhstan . It is a reportable disease and public heath data is available to quantify numbers of cases . Kazakhstan is an upper middle income country . Previous published data suggested that between 2007 and 2011 , 44 cases of human rabies were recorded or a mean of 9 cases per year . Of these 40 were the result of contact with dogs , 3 cases from contact with cats and 1 case from a fox . The incidence of dog bites was reported as 3700 per million population in 2010 and 4130 per million population in 2011 . Post exposure prophylaxis was given to 57 , 000 individuals in 2009 , 59 , 000 in 2010 and 67 , 000 in 2011 [2] . Like many endemic countries , animal rabies is registered annually within Kazakhstan . There is also a programme of vaccination of domestic dogs , cats and agricultural animals and a limited programme to vaccinate foxes through the distribution of vaccine impregnated baits . However a reduction in the disease incidence in animals has not been observed . Thus , one of the objectives of this study was to better understand the epidemiology of rabies by examining the geographical distribution of rabies amongst animals in the country and to evaluate control measures[3] . The economic and disease burden of rabies has also not been previously estimated specifically for Kazakhstan , although estimates , based on modelling , are available from the global burden of rabies study ( GBR ) [1] . Surveillance data on the number of cases of human rabies , the incidence of animal bites and the numbers of individuals undergoing post exposure prophylaxis ( PEP ) were used to obtain more precise estimates of the burden of disease . In addition , data from the number of bites received from confirmed rabid animals was used to estimate the burden of disease avoided by the use of PEP and its cost effectiveness . Finally the economic effects of the disease was estimated from the costs of the animal vaccination programme , the costs of control of potentially rabid animals , the costs of PEP , the loss of income through premature death and the cost of livestock lost to rabies . Suspect animal rabies cases were examined at regional branches of the national veterinary laboratory services . To confirm the diagnosis of rabies , first the brain was removed . Samples were taken from the hippocampus and the cerebellar cortex for further examination . Tissue was examined using the direct fluorescent antibody test or for PCR using the VeTek RV Detection kit ( iNtRON Biotechnology , Inc , Jungang Induspia V , Sangdaewon-Dong , Joongwon-Gu , Seongnam , Gyeonggi-Do , 462–120 KOREA; www . intronbio . com ) . In suspect cases where these tests proved negative bioassays were undertaken in mice . Briefly , material was homogenized , centrifuged and the supernatant inoculated intra cerebrally into mice . The mice were observed for up to 30 days . Rabies was confirmed by histology of brain samples from the mice showing negri bodies and/or Babes nodules consisting of glial cells . All confirmed cases of animal rabies were recorded in terms of animal species and exact geographical coordinates of the origin of the animal . Data was extracted from diagnostic results provided by regional branches of the Republican Veterinary Laboratory and statistical data from the Ministry of Agriculture , Veterinary Control and Monitoring Committee reports . This data included the numbers of animals which were confirmed as rabies according to species . The GIS coordinates of every confirmed animal rabies cases was recorded from 2003 to 2013 . An outbreak of rabies was defined as 2 or more cases found at the same time with the same GIS coordinates . The numbers of animals vaccinated against rabies was also reported and the expenditures associated with the capture and destruction of stray dogs for 2010–2015 . The data used is provided in the supporting information S1 Dataset ( compressed file archive ) . Total livestock populations were derived from statistical data of the Ministry of Agriculture . The number of human rabies cases was as reported by Republican Veterinary Laboratory and statistical data from the Ministry of Agriculture , Veterinary Control and Monitoring Committee reports from 2010 to 2015 and earlier from 2007 [2] . Likewise the numbers of individuals who suffered animal bites and were given post exposure prophylaxis ( PEP ) were also available from government statistics for this period . The population of Kazakhstan is reported as 17 . 1 million in 2010 rising to 18 . 2 million in 2015 [4] . One of the mechanisms for disrupting transmission of rabies is the use of vaccination [5 , 6] . Thus , in order to prevent rabies all 14 regions where the disease has been registered , annual regular vaccination of cattle , sheep and goats , horses , camels , dogs , and cats is undertaken . Data for the number of livestock and domestic pets vaccinated was recorded by the Ministry of Agriculture , Veterinary Control and Monitoring . Vaccines used were either Raksharab ( Indian Immunologicals Ltd . Hyderabad , India ) or Schelkovo-51 strain inactivated vaccine ( Schelkovo Biocombinat , Moscow , Russia ) . Serum samples were obtained from 70 cattle and 30 sheep and goats vaccinated against rabies 3 months following vaccination to investigate antibody levels of vaccinated animals . Blood samples were taken and an indirect enzyme immunoassay for the quantitative determination of antibodies in sera was used ( SERELISA Rabies Ab Mono Indirect , Synbiotics Europe ( Lyon ) , France ) to determine vaccine efficacy . Control measures were evaluated based on changes in annual animal rabies occurrences . Starting in 2012 , a vaccination programme of wild life was initiated using baits impregnated with live vaccine . To investigate the results of oral immunization in wild carnivores , tetracycline uptake from labelled vaccine baits was used [7] . The total number of doses of vaccine used by species and type of the vaccine depends on the total number of susceptible livestock . This is calculated based on the epidemiological situation specific to that district . For high risk areas , the present policy is to vaccinate all susceptible livestock and have a constant monitoring and vaccination of domestic and stray dogs and cats . It is also aimed to distribute vaccine widely to wildlife . In medium risk areas local vaccinations are undertaken in places where rabies had been registered in the last 3 years and monitoring of domestic and wild carnivores and local distribution of vaccine to wild life . In low risk areas where no rabies cases reported but thought to be possible , there is permanent monitoring of rabies in all species and control of domestic and wild carnivores . In very low risk areas where rabies is thought unlikely and is not recorded there is limited epidemiological screening and monitoring for evidence of rabies . Costs were estimated as the sum of the cost of animals vaccinations , funds allocated for the capture and destruction of stray and wild animals , livestock losses due to clinical rabies , the costs of PEP , losses of income whilst seeking treatment and of life time loss of income due to premature mortality . The direct and indirect cost of PEP was not available in the data base and we were not able to obtain them from other sources . Therefore we used the data from GBR [1] . For Kazakhstan , this estimates the direct costs of PEP to be $1 . 95 million ( CIs $0 . 99 -$4 . 3 million , travel costs for treatment , and additional $146 , 000 ( $134 , 000-$566 , 000 ) and $5 . 55 million ( $2 . 8million-$12 . 6 million ) for lost income whilst seeking treatment . Using the uncertainty limits reported we fitted each of these cost items this to a betaPERT distribution using the R package “prevalence” [8] . The GBR study gave a mean estimate of 45620 ( 95% CIs 23 , 421 to 99 , 821 ) for the incidence of PEP treatment in Kazakhstan . This was also fitted to a betaPERT distribution . The we summed the total costs by taking random draws and dividing each by a random draw for the incidence of PEP . This was repeated 10 , 000 times and gave the estimated the cost per case of PEP as $147 ( 95% CIs $74-$258 ) . This cost per case treated by PEP was therefore based on the incidence of PEP treatments estimated by the GBR study . However we then applied this cost to the higher incidence of PEP treatments in our data , again using a Monte-Carlo simulation . The cost of deaths from clinical rabies was the same as the capital approach used in the GBR study [1] . This method estimates the lifetime value of the lost income that would have accrued , from the age of death , were the individual not to have suffered from premature death . The mean annual income was estimated to be the annual gross domestic income per head . In 2014 this was reported by the World Bank to be US$11860 for Kazakhstan [9] The values of animal production for cattle , small ruminants , horses and camels was taken from data from the FAO ( available from http://faostat3 . fao . org ) . The loss in animal production was estimated to be the proportion of animals lost to rabies multiplied by the value of animal production for each species . The costs of animal vaccination was the unit cost of vaccination multiplied by the numbers of animals vaccinated . The costs allocated for the capture and destruction of stray and wild animals were directly available in the data bases and are provided in the supplementary information ( S1 Dataset ) . These were estimated using standard techniques [10–13] without discounting or age weighting . The normative life table used for calculating years of life lost ( YLLs ) was based on the projected frontier life expectancy for 2050 , with a life expectancy at birth of 92 years [13] . This is believed to be the average achievable life expectancy in the absence of disease or injury . Every country has a life expectancy at birth which is currently lower than this . The difference represents the mean YLLs lost due to injury or disease . As clinical rabies has a 100% case fatality ratio , YLLs were estimated from the numbers of reported cases of clinical human rabies . As only total human rabies cases were available and no breakdown according to age , the age of these cases was assumed to follow the same distribution as the age of bite victims . As a scenario a disability weight of 0 . 108 with a mean duration of 60 days was used to estimate YLDs for those patients who suffered bite injuries and underwent post exposure prophylaxis [1] . The numbers of human rabies cases averted were estimated from the data on total number of bite injuries , the anatomical distribution of bite injuries and data on confirmed rabies cases of animals inflicting the bite injury . The probability of rabies occurring in an individual who is exposed to rabies through a bite from an infected animal is from [14] . Thus bites to the head have a probability of 0 . 55 ( CIs 0 . 28–0 . 79 ) of transmitting rabies , bites to the upper extremity a probability of 0 . 22 ( 0 . 12–0 . 38 ) , to the trunk 0 . 09 ( 0 . 05–0 . 38 ) and to the lower extremity 0 . 12 ( 0 . 06–0 . 23 ) . As an alternative scenario rather than using the proportion of bite injuries that were confirmed as being inflicted by an animal with rabies , we estimated the probability of being bitten by a rabid animal from the proportion of animals who were tested for rabies which subsequently were proven to be positive . This was because only a small proportion of animals that bit humans were available for rabies investigation and this could give an alternative estimate of the probability of an animal having rabies given that it has bitten a human . In both scenarios we assumed that PEP , if given appropriately , is close to 100% effective in preventing rabies [15] . The geographical distribution of rabies cases was analysed by mapping the incident cases in animals onto relevant coordinates using Global Position System receivers ( eTrex Legend , Global Sat GH-801 and Shturman SVG-40 ) . The distribution and density of total rabies cases was analysed by kernel density [16] and displayed using the function smoothScatter in the R graphics package [17] . Calculations of economic losses and disease burden were also undertaken in R . All estimates incorporated uncertainty using Monte-Carlo simulations . Thus random draws from appropriate probability distributions were made . These were summed for DALY or cost estimates and repeated 10 , 000 times . Mean and 95% percentiles were then calculated from the results of the 10 , 000 simulations . To explore the hypothesis that foxes may be the principal reservoir hosts , we also analysed the total number of cases in agricultural animals and humans by oblast in a generalized linear model ( GLM ) with numbers of confirmed cases in foxes and dogs as independent variables . Exploratory data analysis indicated that the mean number of cases per oblast ( for every species ) was much lower than the variance of the mean and , because the data is also left bounded by zero , a negative binomial regression model seemed to be the most appropriate statistical model for this analysis . We used the glm . nb function from the MASS package in R for this analysis . The R code and data for all analyses is provided in the supplementary material ( S1 Dataset ) . There has been a steady increase in the number of animals vaccinated . For example 473 , 000 cattle were vaccinated in 2010 , rising to 1 . 6 million in 2015 . In 2010 275 , 000 dogs were vaccinated , rising to 830 , 000 by 2015 ( Fig 5 ) . A total of 18 pathological samples were collected from wild carnivorous in East Kazakhstan , West Kazakhstan , and Kostanay regions . Of these , 8 animals had consumed baits containing vaccine and tetracycline ( 44 . 4% , exact binomial 95% CIs 21 . 5%-69 . 3% ) . The study results demonstrated that there were no antibodies precipitating rabies virus antigen in any of the blood serum samples collected from animals vaccinated by Raksharab . In blood serum samples of animals vaccinated by Russian Schelkovo-51 vaccine , antibodies in 0 . 32–0 . 6 ME/ml and 1–2 ME/ml have been identified , which demonstrates a modest level of immunity . There were 216 cases of animal rabies registered in 2011 , 139 in 2012 , and 174 in 2013 , 163 in 2014 and 187 in 2015 which indicates that there is little change in rabies incidence following widespread use of vaccination . From 2010 to 2015 a total of 388 , 807 animal bite injuries were recorded . This equates to a bite incidence of 368/100 , 000 per year . Of these 386 , 785 were recommended for post exposure prophylaxis ( PEP ) with 385 , 733 completing the treatment ( a mean of 64 , 289 per year ) . A small number refused PEP . There was a significantly increased risk of children between the ages of 6–14 years of age receiving a bite injury . There were 95 , 185 bite injuries in this age group . If they had received the number of bite injuries according to the population size of this age group , there should have been 50 , 501 ( Chi Square , p<0 . 0001 ) . Thus this group received 24 . 5% of all bite injuries , but represented only 13 . 0% of the total population . Of the 388 , 807 animal bite injuries reported between 2010 to 2015 , the lower extremities were the most likely to suffer a bite injury accounting for 49 . 7% of all injuries . The forearm , hand and fingers accounted for 28 . 5% of bite injuries , with the head , face and neck for 5 . 2% of injuries . The shoulders and trunk had 9 . 7% of injuries . Multiple injuries accounted for 3 . 7% . Subjects reported being licked by a suspect animal rather than a penetrating bite in 3 . 1% of cases . There were a total of 50 human fatalities from 2009 to 2015 inclusive . This was an average of 7 . 1 cases per year . ( Poisson 95% CIs 5 . 3–9 . 4 ) This ranged from a maximum of 14 seen in 2009 to a minimum of 3 seen in 2014 . There was no evidence of any trend in the data or any significant differences in the number of cases recorded each year ( Poisson regression , p>0 . 1 ) . These rabies cases resulted in a disease burden of 457 DALYs ( 95% CIs 338–594 ) per year . This is the equivalent to approximately 64 DALYs per case of rabies . In total 385 , 773 bite injuries were recommended for PEP treatment . This resulted in approximately 1140 YLDs per year . Of the 388 , 807 bite injuries , a diagnosis of rabies was confirmed in 3067 biting animals ( 0 . 78% ) . In the absence of PEP , this would have expected to result in an additional 713 ( 95% CIs 440–1121 ) cases of rabies or 118 ( 95% CIs 74–185 ) per annum . This would have resulted in 7657 DALYs ( 95% CIs 4723–12041 ) annually . With an estimated cost of PEP of $9 . 1 million per annum , the cost per rabies case averted is $76908 ( 95% CIs $34412-$166350 ) , with the cost per DALY averted of $1193 ( 95% CIs $534-$2581 ) . The observed number of cases was 36 from 2010 to 2015 . It is not recorded if the cases of human rabies received any PEP , were members of the group who refused PEP or failed to seek any treatment following a bite . However , 1052 individuals over this period were bitten but refused to complete the recommended PEP . Assuming that they had a similar probability of being bitten by a rabid animal ( 0 . 78% ) , this would result in 8 people potentially exposed to the rabies virus but not undergoing treatment , with an expectation that perhaps 2 would have died of rabies . This indicates that at least 34 of the 36 cases of human rabies seen occurred in individuals who failed to seek any medical advice following their bite injury . In total between 2010 and 2015 inclusive , 3820 dogs were investigated for rabies of which 242 were confirmed positive ( 6 . 3% ) . The total of other species investigated for rabies during this time period was 4492 of which 874 ( 19 . 5% ) were confirmed as rabies . We therefore applied a mean probability of 0 . 063 to those individuals suffering dog bites and 0 . 195 to bite injuries from other species as the probability they were bitten by a rabid animal Most bite injuries were caused by dogs ( 340907 of 388807 bite injuries or 87 . 7% ) followed by cats ( 8 . 2% ) , cattle ( 1 . 1% ) , horses ( 0 . 44% ) , foxes ( 0 . 24% ) , wolves ( 0 . 07% ) with the remainder unspecified . Assuming the transmission probabilities dependent on the anatomical location of the bite injury , this would have resulted in 1184 cases of rabies per annum ( 95% CIs 729–1869 ) or 76318 DALYs ( 95% CIs 47000–120470 ) . In this scenario the cost per DALY averted is US$119 ( 95% CIs $52-$256 ) , whilst the cost per case averted is US$7653 ( 95% CIs $3395-$16531 ) Under this scenario , there is also a much higher probability that the 1052 individuals refusing PEP were actually bitten by a rabid animal . This would result in a mean of approximately 3 cases of rabies ( 95% CIs 2–5 ) or 207 DALYs ( 95% CIs 127–326 ) per annum . This is approximately half the observed number of human cases . In this scenario with the higher probability of the animal inflicting the bite having rabies it suggests that 19 people refusing PEP would go on to develop rabies and 17 individuals failed to seek medical advice . The total costs ( direct and indirect ) of seeking PEP treatment was estimated at $ 9 . 1million per annum ( 95% CIs $4 . 7 million- $16 . 6 million ) . Production losses from premature deaths were estimated as $5 . 4 million per annum ( 95% CIs $4 . 0 million- $7 . 1 million ) . A mean of $3 . 4 million per annum ( range $2 . 5 million–$4 . 5 million ) was allocated for the catching and destruction of stray and wild animals suspected to be affected by rabies . Vaccine was purchased at a cost of $0 . 35 per dose for use in livestock , dogs and cats . Oral baits containing vaccine for distribution to wildlife was purchased at $0 . 97 a dose . A mean of 4 . 7 million domestic animals per annum between 2013–2015 were vaccinated at a cost of $1 . 7 million per annum . Of this , $1 . 4 million was spend on vaccinating livestock with the remainder on dogs and cats . A mean of 736 , 000 baits per annum were distributed for wildlife at a cost of $719 , 000 per annum . Livestock losses were relatively low , based on the value of livestock affected by rabies . Thus the losses attributed to cattle affected by rabies was US$ 20651 ( 95% CIs 18996–22442 ) per annum , sheep $627 ( 95% CIs $515-$755 ) , camels $114 ( 95% CIs $59–193 ) and horses $2194 ( 95% CIs $1628-$2878 ) . Total livestock losses were estimated as $23581 per annum ( 95% CIs $21818-$25512 ) . The total economic costs of rabies in Kazakhstan when adding up the costs from all sectors and the losses is approximately US$ 20 . 9 million per annum ( 95% CIs $15 . 7 million- $28 . 2 million ) . The relative contribution to these costs are illustrated in Fig 6 . The negative binomial GLM gave a highly significant association with the numbers of cases per oblast reported in agricultural animals and the numbers of confirmed diagnoses in foxes per oblast ( Table 1 ) . The relationship between the number of rabies diagnoses in dogs and agricultural animals was less highly significant with a smaller effect size . The numbers of cases in humans showed a significant relationship with numbers of cases diagnosed in dogs , but no relationship with cases in foxes . The results of this study give a detailed overview of the distribution and burden of rabies in Kazakhstan . The results are largely based on detailed surveillance and budgetary data provided by the veterinary and public health services in Kazakhstan , although some data used in the estimates were borrowed from the GBR study . This study also demonstrates that rabies has a substantial economic effect in Kazakhstan . Direct measures to prevent the disease in humans , notably PEP appear to be cost effective , even though PEP itself does not prevent transmission . Other measures such as widespread vaccination of livestock appear to be less cost effective with near $1 . 4 million invested in vaccinating farm livestock with no evidence of a change in animal incidence . Thus these resources might be better targeted towards greater vaccination of the reservoir hosts to prevent transmission
Kazakhstan is a large central Asian country that was part of the Soviet Union until 1991 . The country is endemic for rabies . This study shows that there are areas of Kazakhstan such as the north and south east of the country where outbreaks of animal rabies are concentrated . Cattle , dogs and foxes are the animals most frequently confirmed with rabies . A mean of 7 . 1 human deaths annually due to rabies occurred between 2009 and 2015 inclusive in Kazakhstan resulting in 457 disability adjusted life years . A mean of 64 , 801 people each year are recorded as suffering bite injuries from animals , mainly due to dogs . Children are at higher risk of being bitten . However , the widespread use of post exposure prophylaxis ( PEP ) prevents at least 118 and possibly up to 1184 fatalities per annum of people bitten by rabid animals . The economic costs of this disease are high: exceeding $20 million per annum . However , the widespread use of PEP is cost effective in reducing the burden of disease .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[ "livestock", "medicine", "and", "health", "sciences", "ruminants", "immunology", "tropical", "diseases", "geographical", "locations", "vertebrates", "dogs", "animals", "mammals", "vaccines", "preventive", "medicine", "rabies", "neglected", "tropical", "diseases", "vaccination", "and", "immunization", "veterinary", "science", "public", "and", "occupational", "health", "infectious", "diseases", "veterinary", "diseases", "zoonoses", "agriculture", "people", "and", "places", "kazakhstan", "asia", "biology", "and", "life", "sciences", "viral", "diseases", "cattle", "europe", "amniotes", "bovines", "organisms" ]
2016
Rabies in Kazakhstan
Arboviral infections have repeatedly been reported in the republic of Djibouti , consistent with the fact that essential vectors for arboviral diseases are endemic in the region . However , there is a limited recent information regarding arbovirus circulation , and the associated risk predictors to human exposure are largely unknown . We performed , from November 2010 to February 2011 in the Djibouti city general population , a cross-sectional ELISA and sero-neutralisation-based sero-epidemiological analysis nested in a household cohort , which investigated the arboviral infection prevalence and risk factors , stratified by their vectors of transmission . Antibodies to dengue virus ( 21 . 8% ) were the most frequent . Determinants of infection identified by multivariate analysis pointed to sociological and environmental exposure to the bite of Aedes mosquitoes . The population was broadly naïve against Chikungunya ( 2 . 6% ) with risk factors mostly shared with dengue . The detection of limited virus circulation was followed by a significant Chikungunya outbreak a few months after our study . Antibodies to West Nile virus were infrequent ( 0 . 6% ) , but the distribution of cases faithfully followed previous mapping of infected Culex mosquitoes . The seroprevalence of Rift valley fever virus was 2 . 2% , and non-arboviral transmission was suggested . Finally , the study indicated the circulation of Toscana-related viruses ( 3 . 7% ) , and a limited number of cases suggested infection by tick-borne encephalitis or Alkhumra related viruses , which deserve further investigations to identify the viruses and vectors implicated . Overall , most of the arboviral cases' predictors were statistically best described by the individuals' housing space and neighborhood environmental characteristics , which correlated with the ecological actors of their respective transmission vectors' survival in the local niche . This study has demonstrated autochthonous arboviral circulations in the republic of Djibouti , and provides an epidemiological inventory , with useful findings for risk mapping and future prevention and control programs . Arboviral fevers are a threat to the global population and warrant a continuous surveillance and monitoring , especially in tropical and subtropical regions , where most of the low income countries are located [1] . Viruses from families of Togaviridae and Bunyaviridae , and from genus Flavivirus are responsible for the majority of human arboviral infection cases . The observed geographical dispersion of arboviral diseases is strongly correlated with the ecological factors and human activities [2] . For example , dengue virus ( DENV ) , Yellow fever ( YFV ) , and Chikungunya ( CHIKV ) infections tend to spread to all regions where their Aedes transmission vectors are present ( potentially affecting two thirds of the global human population ) [3] . The tick-borne encephalitis virus ( TBEV ) is endemic in Europe , Russia and Asia in forest , moorland and steppe ecosystems hosting abundant transmission rodent hosts and Ixodid vectors . The warm African eco-climates support abundant mammalian hosts , reservoir birds and vectors , which are favourable factors for arboviral transmission [1] . To some extent , the same characteristics apply to the WHO Eastern Mediterranean region ( WHO-EMR ) [2] , [3] , to which our study area , Djibouti , belongs . A combination of limited surveillance capabilities for early detection and a lack of routine preventive medicine programs , in part explains why limited information regarding arboviral fevers is available in Djibouti . Nevertheless , the scientific literature provides evidence that essential vectors for arboviral diseases are endemic in the republic of Djibouti . These include some mosquito vectors ( e . g . , Aedes , Culex and Anopheles species ) [4]–[6] , ticks ( Ixodes , Rhipicephalus , Amblyomma , Hyalomma species ) [7] and sandflies [8] , [9] . In addition , potential animal reservoirs such as nomadic pastoralists' livestock [10] , migratory birds [11] , and rodents [12] , are present . This evidence corroborates the existing risk of outbreaks , since a number of arboviral pathogens have been detected to be in local circulation [4]–[6] , [13] , [14] . However , the recent information and the associated risk predictors to human exposure are limited or poorly documented . For example , at the time of submission , there were only two reports on Djibouti local causal association of vector transmission to arbovirus: that of mosquitoes vectors to the WNV [15] and DENV [5] . Other reports have either separately documented the vectors of transmission ( courtesy of entomological studies ) [8] , [9] or indirectly documented the detection of arbovirus exposure via biomarkers ( courtesy of serological studies ) [5] , [16] . This study therefore , is an attempt to bridge the existing knowledge gap , based on the Djibouti city general population . It is a cross-sectional analysis nested in a household cohort , which investigates the arboviral infection prevalence and risk factors , stratified by their vectors of transmission . Attention was given to Culex- ( WNV ) , Aedes- ( DENV , YFV and CHIKV ) , RVF ( diverse transmission mechanisms ) , sandfly- ( Toscana ( TOSV ) and related phleboviruses ) and tick- ( TBEV and related flaviviruses ) borne viruses . The essential purpose was to provide an epidemiological inventory , with useful findings for risk mapping and future prevention and control programs . Households were enrolled into the study after the ethical approval was granted by both this Consortium , which was based at the EHESP French School of Public Health , Rennes France , and the Ethical Review Committee at the National Institute of Public Health ( INSP ) Ministry of Health , Republic of Djibouti . A household was defined as two or more persons staying in the same house , sharing meals and living room space , with or without familial relationship [17] . For a household to be enrolled , all subjects belonging to it were required to give a written consent before participation . Minors below 18 years were to give their consent through their parents or guardians . This consent also provided for specimen usage in other studies , apart from the CoPanFlu program . This was a Djibouti cohort of pandemic influenza ( CoPanFlu ) study that investigated the sero-epidemiology and vaccination intention of 2009 pandemic influenza ( H1N1pdm09 ) in the republic of Djibouti [18] . The study was based on the WHO-EHESP CoPanFlu International Consortium core protocol [19] . The study was conducted in four administrative districts of Djibouti city , Republic of Djibouti , which is one of the 22 member states of the WHO Eastern Mediterranean region [20] . It is situated in the horn of Africa , at the Gulf of Eden of the Red Sea , bordering Somalia , Ethiopia , and Eritrea . It covers 23 , 200 km2 with 818 , 159 inhabitants , with majority of them , 70 . 6% ( 577 , 933 ) residing in urban areas [21] . Of those who live in urban , the largest proportion , 58 . 1% ( 475 , 322 ) are inhabitants of the capital , Djibouti city . Eco-geographically , the country is largely arid and semi arid , with perennial flooding during winter ( November to April ) and prolonged summers for the rest of the year . Fig . 1 shows an illustrative map of the study area , Djibouti city , together with the spatial distribution of participating households by Quartier ( location ) in the four administrative districts . The District 1 hosts the city center and there is a progressive decline in the urbanization , from District 2 towards District 4 . The protocol and samples used in this study were derived from the Djibouti Cohort of Pandemic Influenza ( CoPanFlu ) program [18] , [19] , as mentioned above . After receiving authorization from relevant government departments , 1 , 045 individuals from 324 households were enrolled randomly , between 11th November 2010 and 15th February 2011 , from a pool of 1 , 835 households , which were derived from two sources: 1 , 335 households were from the 2009 Hajj Pilgrim database and 500 households were from the community of health workers ( CHW ) cognisance list of vulnerable households . The initial project was designed as a seroprevalence study and therefore no specific clinical information was used for recruitment . Complete households were included , whatever the medical history of each family member . Information was given to household members and enrollment was conducted only when all members could be included . Participants or their legal representatives were “a priori” required to give informed consent . Only households meeting the following criteria were enrolled in our cohort: all members of the household shared one roof , they shared meals and living area , and consented to participate ( including blood sampling and responding to questionnaires ) . On an appointed date , the capillary blood samples ( ∼100–500 µL ) were collected and the assisted response to standardised French questionnaires was completed , using the local dialect to translate questionnaires whenever necessary . This questionnaire collected information on subjects' and households' profiles , occupation and academic background , and residential environment characteristics ( see Table 1 for details ) . Because of the initial purpose of the cohort , information relating to yellow fever vaccination was not collected . After completion of the CoPanFlu program , the current study was performed using the biological samples that remained available , i . e . , those of 1 , 045 subjects recruited in 324 households . The spatial distribution of the enrolled households by Quartier ( location ) is illustrated in Fig . 1 [18] . The screening of antibodies ( IgG ) against various pathogens was performed using two different Enzyme Linked Immuno-Sorbent Assay ( ELISA ) protocols . In the first protocol , in-house kits ( in which antigen derived from whole-virion particles in non-inactivated cell culture supernatants ) were used to test for YFV , TOSV , RVFV and CHIKV antibodies . In the second protocol , commercial kits were used for detection of DENV ( PanBio , Brisbane , Australia ) , WNV and TBEV ( EuroImmun , Lübeck , Germany ) antibodies . Positive and negative control sera were provided by the French National Reference Centre for Arbovirus or by the kits' manufacturers . For each serologic assay , a minimum of three positive controls was included , alongside three negative controls and three blank controls ( normal saline ) , in accordance with the established standard protocols [22] . Additional sero-neutralisation experiments were conducted in which wild-type laboratory-adapted viral strains were used , with exception of the YFV , in which the D17 vaccine strain was used . Appropriate cell culture lines and reagents were used in accordance to the established Standard Operating procedures and Good Laboratory Practice protocols of the laboratory . All experiments were conducted in Biosafety level 3 laboratory containment facilities , at the EPV UMR_D 190 research laboratory , or at the French National Reference Centre for Arboviruses , Marseille France . For consistence , all samples were tested in duplicates using common serum controls ( negative and positive ) for all plates in a specific pathogen assay . The values of all plates for a given test were subsequently normalised according to values of negative and positive controls . In addition , a panel of 176 true negative samples was tested using the in-house and commercial kits protocols . This panel included sera from a previous study of French blood donors that tested negative for antibodies to all pathogens studied here using sero-neutralisation techniques . For both in-house and commercial assays , sera with normalised absorbance values above the cut-off value ( defined as [mean of normalised true negatives+two standard deviations] ) were considered to be positive . The positivity ratio ( normalised absorbance value of the sample/cut-off ) was used for ELISA interpretation with ratios ≤0 . 9 associated with negative results; ratios between 0 . 9 and 1 . 1 with equivocal results; and ratios ≥1 . 1 with positive results . A virus neutralisation assay ( VNT ) was performed for all viruses , but dengue to check the performance of the ELISA assays . In brief , 50 µL of heat-inactivated ( 56°C , 30 minutes ) serum dilution ( 5 to 1280 in PBS ) was added to 50 µL of viral suspension ( representing 100 TCID50 ) in flat bottomed 96-well cell culture Microplates ( Nunc ) followed by 100 µL of Vero cell suspension ( 2×105 cells/ml ) in MEM culture medium supplemented with 8% fetal bovine serum and antibiotics . The plates were then incubated at 37°C in CO2 incubator and virus multiplication was measured after 3–5 days by observing a cytopathic effect ( CPE ) or by quantifying the amount of viral genome in the culture supernatant by using real-time RT-PCR techniques in the case of TBEV and Alkhumra virus ( AHFV ) ( below is the protocol ) . Absence of CPE or real-time RT-PCR cycle threshold above 37 was considered a positive reaction . The final arbovirus infection status ( seropositivity ) of the subjects was determined by the VNT positive status , which was set at a cutpoint titer of ≥10 [23] . The TBEV ELISA seropositives samples were tested for neutralising antibodies against TBEV and AHFV in the VNT assay . For each , the VNT culture was used for RNA extraction for TBEV and AHFV qRT-PCR assay . The RNA extraction was performed using the NucleoSpin 96 RNA virus kit ( Macherey-Nagel ) in accordance to the manufacturer's instructions . The TaqMan NS3 primers and probes sequences used for amplification were as follows: ALKV-Forward ( CCA GTT GTY TCC ATG GAT GG ) , ALKV-Reverse ( GCC GCC AAC CQA CAQ TGG ) and ALKV-Probe ( FAM-CAA TGT AGC TAG CCT GAT AAC T-TAMRA ) ; TBEV-Forward ( GGA MGR ACM GAT GAA TAC AT ) , TBEV-Reverse ( GYG CYT CYT TCC AYT GCA ) and TBEV-Probe ( CTC TGG ACA GTG TGA TGA TGA TGA ) . The probes were labeled with fluorescent 6-carboxyfluorescein ( FAM ) as the reporter dye at the 5′ end and with a quencher of the minor groove binder ( MGB ) at the 3′ end . The PCR reaction kit constituted of the one-step SuperScript III Platinum QRT-PCR System with Rox ( Invitrogen ) and the reaction was performed in the Applied Biosystems 7900 Real-Time PCR System . A total of 20 µL reaction volume was used , consisting of 0 . 5 µL of Superscript III RT/Platinum Taq Mix , 10 µL of Reaction mix with ROX , 0 . 5 µL of Reverse primer , 0 . 5 µl of Forward primer , 3 µL RNA template , 0 . 3 µL of the probe and 5 . 2 µL of water . The reaction condition entailed 60°C for 15 minutes for RT , 95°C for 2 minutes and 40 cycles of amplification ( 95°C for 30 sec; 60°C for 30 sec ) . Wells with cycle threshold lower than 37 were considered to have a negative result for neutralising antibodies , otherwise were considered positive . Data entry and management was performed in the FileMaker Pro Advanced 11 ( FileMaker ) environment . From the 19 household ownership properties , the principle component analysis was used to create three socioeconomic status ( SES ) , the Upper SES , the Middle SES and the Lower SES [24] . The criterion used to differentiate the three SES levels was based on rank score of household property ownership , and as described in details elsewhere by Vyas et al . [24] and Nauta [25] . The 19 household properties used for SES determination , included the ownership of Vehicle , Music System , Washing Machine , Sealing Air Fan , Bicycle , Toilet , Telephone , Television , Separate Seating/Lounge Room , Radio , Motor Cycle , House Owner , Fridge , Electricity , DVD Video Player , Gas Cooker , Electric Cooker , Air Conditioner System , and running tap water . In some cases , this information was missing and therefore the SES level was documented as ‘unknown’ ( Table 1 ) . A descriptive analysis was performed on variables in preliminary evaluation . For public health importance , the infection status ( seropositivity ) was stratified for analyses as ( a ) individual pathogens or according to their ( b ) transmission vectors , namely: Culex-borne viruses ( WNV ) , RVF ( diverse transmission mechanisms ) , Aedes-borne viruses ( YFV , DENV and CHIKV ) , sandfly-borne viruses ( TOSV ) and tick-borne viruses ( TBEV and AHFV ) ; or ( c ) virus taxonomy , namely: Flaviviruses ( DENV , WNV , TBEV , AHFV , YFV ) , Phleboviruses ( RVF and TOSV ) and Togaviruses ( CHIKV ) . Evaluation of heterogeneity of the seropositivity proportions in different independent variables such as districts , age groups , occupation and SES , was done by Chi square ( χ2 ) test or Fisher's exact test . Analysis of trend to establish the potential systematic increase or decrease of infection status across the variable was also performed . At the time of study , no specific information regarding specific exposure risk to the different vectors was available to the authors . Therefore the determination of socio-demographic and environmental predictors to infection status were performed in the generalised estimating equation ( GEE ) models , which accounted for the household clustering effect among the enrolled subjects . Variables with p-value ≤0 . 25 in bivariate model were included in multivariate analysis in a backward stepwise reduction protocol , those with p-value ≤0 . 15 were retained in the final model and those with p-value ≤0 . 05 being considered statistical significance [26] . Effect modification and interaction between variables on subjects' seropositivity were assessed . The use of GEE model in measurement of association , did not allow for the institution of post estimation validity evaluation [27] . All analyses were conducted in Stata Statistical Software Release 13 ( StataCorp College Station , TX: StataCorp LP ) . Demographic information for the 1 , 045 subjects belonging to 324 families involved in this study is shown in Table 1 , a detailed profile has been provided elsewhere [18] . Briefly , the participants were drawn from different age groups , gender , residential districts , ethnicity , occupation and socio-economic background in Djibouti city . Their diversity was manifested also in living conditions ( housing space ) and neighborhood environment , which included: housing materials , domestication of animals , exposure to birds , sleeping habits ( out in the open at night ) , and the proximity to the following: market , abattoir , open sewage , dumpsite and river bank , respectively . The performance of the different ELISA tests was examined with reference to sero-neutralisation results for all viruses studied except DENV . Due to capillary sampling , there was limited amounts of serum and therefore we could not perform more biological tests on DENV ( and some ELISA positive subjects ) than those described in the article . However , from past studies [5] , DENV circulation had been broadly recognised in Djibouti , and there was little doubts that DENV represented the most frequent arbovirus transmitted . But for the rest , for each test , a selection of ELISA negative samples and all available samples with a positive ELISA result were tested . For those viruses which had been previously identified in East Africa ( YFV , WNV , CHIKV and RVFV ) results are summarised hereafter and available in Table 2 and Table 3: ( i ) for YFV , 11 out of the 14 ELISA-positive samples were available for VNT . The Positive Predictive Value ( PPV ) of the ELISA test ( ratio ≥1 . 1 ) was 0 . 64 and the Negative Predictive Value ( NPV , calculating after gathering negative and equivocal results ) was 1 . We therefore tested other ratios for the definition of positives and identified an optimised ELISA ratio at 1 . 5 , associated with a PPV at 0 . 91 and a NPV at 0 . 88 . ( ii ) For WNV , 4 out of the 5 ELISA-positive samples were available for VNT . The ELISA PPV ( ratio ≥1 . 1 ) was 0 . 56 and the NPV was 1; an optimised ELISA ratio at 1 . 3 was associated with a PPV at 0 . 75 and a VPN at 0 . 80; ( iii ) for CHIKV , 23 out of the 24 ELISA-positive samples were available for VNT . The ELISA PPV ( ratio ≥1 . 1 ) was 1 and the NPV was 0 . 86; ( iv ) for RVFV , 18 out of the 20 ELISA-positive samples were available for VNT . The ELISA PPV ( ratio ≥1 . 1 ) was 0 . 83 and the NPV was 1 . For viruses never isolated in the region , the results were as follows: ( i ) for TOSV , 33 out of the 34 ELISA-positive samples were available for VNT . The ELISA PPV and NPV ( ratio ≥1 . 1 ) were 0 . 94 and 0 . 90 , respectively , suggesting previous contact with genuine TOSV or a closely related phlebovirus ( see below ) . ( ii ) for TBEV , all of the 5 ELISA-positive samples tested negative for other flaviviruses tested ( DENV , YFV , WNV ) , which rules out the hypothesis of cross-reactivity with one of these pathogens . Since only two samples were available for additional seroneutralisation tests , reliable PPVs could not be calculated . The first sample was negative in seroneutralisation for TBEV and also for AHFV , a tick-borne flavivirus that has been previously shown to circulate in Saudi Arabia and in the south of Egypt [28] , [29] . The second sample was positive for TBEV ( titre 20 ) and AHFV ( titre 40 ) , suggesting possible contact with the latter virus . The sample was from a 13 yo girl belonging to a family with a low socioeconomic status , and living nearby an abattoir . Her age and socioeconomic status make unlikely a previous travel to known AHFV endemic areas such as Saudi Arabia ( e . g . for the Hajj ) . Using the aforementioned optimised ELISA positivity criteria , mosquito-borne virus infections were predominant , with 23 . 6% of the population testing positive for at least one Aedes-borne virus ( DENV , YFV and/or CHIKV ) and 0 . 6% to WNV; 3 . 7% tested positive for sandfly-borne viruses ( TOSV ) ; 0 . 6% tested positive for tick-borne viruses ( TBEV ) ; 2 . 2% tested positive for RVFV . Detailed results are provided in Tables 2 and Table 3 . All subsequent statistical analyses were performed using ELISA results ( with reference to optimised positivity ratios ) . First , we analysed double-positives ( i . e . , samples with positive results for two different tests ) and the issue of possible ELISA antigenic cross-reactivity between the different flaviviruses tested ( DENV , YFV , WNV and TBEV ) was addressed . No significant statistical association between serological results for flaviviral species was observed , confirming the good PPV of the ELISA tests for most of flaviviruses tested . The same analysis was performed for phleboviruses and a strong association was observed ( p<0 . 00001 ) between TOSV and RVFV results . This is intriguing since TOSV and RVFV are antigenically very distant . A refined analysis of ELISA results for double-positives identified no relationship between the positivity ratios of TOSV and RVFV ELISA positives . Moreover , in double-positives , VNT geometric mean titers ( GMTs ) were high for both viruses ( >20 for RVFV , >30 for TOSV ) . Altogether , this suggests that an epidemiological relationship rather than an antigenic cross-reactivity should be invoked . Second , we examined possible associations that might be explained by exposure to a common vector . An obvious association ( p<0 . 00001 ) was identified between DENV and CHIKV ( 70 . 8% of CHIKV positive samples are also DENV positive ) . This is evocative of a shared exposure to the bite of Ae . aegypti , which represents the most probable vector of both CHIKV and DENV . The same link was not identified between YFV and CHIKV or DENV , despite their common vector . However , since YFV is not endemic in Djibouti , the most probable explanation to YFV positive results is either immigration from an endemic country or vaccination ( as recommended for Hajji Pilgrims and for travels in Ethiopia , see below ) . Third , a triangular significant association ( p<0 . 00001 ) was observed between YFV , TOSV and RVFV . Since there is no antigenic relationship between YFV and phleboviruses , and different vectors transmit all three pathogens , the existence of a subpopulation gathering a variety of risk factors represents the most plausible explanation ( see supplemental data in S1 Table ) . Univariate and –when authorised by numbers– multivariate analyses ( UVA and MVA , respectively ) were performed to assess the relationship between serological results to subject and household profiles' , occupation and academic background , and the residential environment characteristics ( see S2 Table and Table 4 ) . Statistical analysis indicated that DENV and CHIKV positives share a number of risk factors: ( i ) living in District 1 ( i . e . , city centre; MVA , p<0 . 001 ) and sleeping outside at night ( MVA , p<0 . 001 ) . Sleeping out is a common practice among those families with no air conditioner machine . This is because during the summer period in Djibouti , the ambient temperature and humidity are in the extreme . This often compels them at night , to literally sleep outside their houses , in the open air , many of whom , without bednets , so as to catch some sleep . Both ( CHIKV and DENV ) are most probably linked with exposure to the common vector ( Ae . aegypti ) , which is likely , in the warm and dry Djiboutian setting , to find a favourable environment in the urban areas of Djibouti , as previously reported in other locations [30] and can bite in the evening and the beginning of the night . ( ii ) living in large families ( four or more persons; MVA , p<0 . 001 ) . This may reflect favourable conditions for maintaining a population of Aedes mosquitoes in/around the household . In accordance with this observation , MVA indicates that keeping a domestic animal at home ( which indeed may be part of the feeding resources available for female Aedes mosquitoes ) is also associated with an increased risk for dengue ( MVA , p<0 . 001 ) . Amongst residential environment parameters , living nearby a river was associated with an increased risk for dengue ( MVA , p<0 . 001 ) . Running water is seasonal in Djibouti and , in the extreme context of the local climate , which is associated with limited vegetation , the presence of plant cover , puddles and water holes on the river banks is likely to offer an alternative to urban households as a source of larval sites for Aedes mosquitoes . Living nearby meat-markets ( mostly located in peripheral poorly urbanised areas; MVA , p<0 . 001 ) and having a high socioeconomic status ( MVA , p<0 . 001 ) were found to be protective for DENV and CHIKV , respectively . It is important to note that these findings do not account for the population dynamism within and without the Djibouti city administrative districts . Finally , the distribution of sero-prevalence in age groups showed that the highest incidences were in young adults ( 20–39 yo ) for both DENV ( 22 . 2% ) and CHIKV ( 3 . 0% ) , see Table 5 . This profile suggests that DENV virus circulation in Djibouti is not under a regimen of hyper-endemicity as observed in Southeast Asia; here , in contrast , it is suggestive of probable episodic spillovers into a population that was broadly naïve in all age groups . An important consequence is that dengue is not a specifically paediatric disease in Djibouti . Regarding CHIKV , these numbers indicate that when this study was performed ( November 2010 to February 2011 ) , the Djiboutian population was massively naïve towards Chikungunya . The O'nyong-nyong ( ONNV ) and CHIKV are the two alphaviruses previously observed in the region [31] , [32] , with potential antigenic cross-reactivity . However , the measure of ONNV specificity to CHIKV in immuno-fluorescence and haemagglutination inhibition techniques gave limited ( if any ) cross reaction using monoclonal antibodies [31] . This was consistent with Chanas et al . [32] observations , that the antibodies to ONNV are quite specific and poorly seroneutralise CHIKV . Therefore , we are confident that we detected mostly antibodies to CHIKV because: ( i ) we used non-inactivated viral antigen that allows to favour a specific selection of antibodies to envelope glycoproteins , which are the most divergent antigens between the two species , and ( i ) our ELISA results were broadly confirmed by seroneutralisation . Regarding other viruses , the low sero-prevalence rates did not allow to identify major risk factors . ( i ) In the case of TBEV , UVA suggested migrants as a target population ( p = 0 . 01 ) , which may reflect specific exposure to tick bites , presumably through long periods of time spent in a rural environment and/or contact with livestock . In the case of WNV , children under the age of 13 , not sent to school nor employed appeared to be at risk ( UVA , p = 0 . 01 ) , possibly reflecting low socioeconomic status . ( ii ) In the case of YFV , no strong correlate was identified . ( iii ) In the case of TOSV , positives were more frequent in District 1 ( MVA , p = 0 . 004 ) , and this may guide future investigations for identifying the vector and deciphering the transmission cycle in Djibouti . ( iv ) In the case of RVFV , MVA identified an elevated risk of infection amongst the young below 19 yo ( p = 0 . 0150 ) and individuals of Arab descent ( p = 0 . 0160 ) . Of note was that about a half ( 48 . 3% ) of those in upper SES class were of Arabian ethnicity , and that the young Arabs were at least risk compared to their contemporaries ( although not statistically significant ) . This may reflect a link with animal sacrifice related activities during Islam feasts or travel in countries of high endemicity , since upper SES Arabian adult populations could afford such foreign trips , compared to majority of other tribes [33] . Regarding triple exposure to TOSV , RVFV and YFV , the best correlates identified by MVA were the age under 19 yo ( p = 0 . 02 ) and the Afar ethnic origin ( p = 0 . 02 ) , possibly reflecting specific risk factors such as transhuman pastoralism , contact with livestock ( this age group is commonly in charge of the animals ) and travels in Ethiopia ( for which YF vaccination may be required ) since the largest Afar populations reside in the Danakil Desert in Ethiopia . This study reports arboviral sero-prevalence values and risk predictors in the winter of 2010 , in Djibouti city . Of the total participants , over a quarter ( 27 . 4% ) had evidence of infection with at least one of the eight studied arboviruses . Studying simultaneously a variety of pathogens allowed us to weight serological cross-reactions . With reference to sero-neutralisation assays , it was minimal , reflecting our choice of giving priority to the Positive Predictive Value of the tests used ( with the possible consequence of slightly under-estimating actual prevalence rates ) . Of interest was the conspicuously high burden of mosquito-borne viruses , especially , those transmitted by Aedes mosquitoes . DENV was found to have the largest and with widest distribution across the different residential Districts of the city . It was first reported in the outbreak of 1991–1992 [5] , then remained steadily in circulation and was subsequently detected in survey studies [14] . So far DENV serotypes 1 , 2 and 3 are documented to have circulated in Djibouti [5] , [14] . whereas the presence of DENV Serotype 4 has not been reported . Our results suggest that dengue is present but still circulating at low levels compared with countries of high endemicity , resulting in limited immune protection of the population and infections distributed in age groups ( i . e . , not predominantly impacting the paediatric population ) . Determinants of DENV infection identified by multivariate analysis point to sociological and environmental exposure to the bite of Aedes mosquitoes . At the onset of this study , conducted in winter of 2010 , contrary to DENV , CHIKV had never been reported in Djibouti . We report here a 2 . 6% sero-prevalence rate , with epidemiological determinants of infection very similar to those identified for dengue . It is worth noting that a CHIKV outbreak occurred in Djibouti during the year 2011 ( personal communication Dr Ammar Ahmed Abdo , Ministry of Health Djibouti ) and that , in our study , a majority of individuals with specific antibodies ( >80% ) were living in District 1 . The most probable scenario is therefore that the virus had been circulating at low rate in 2010 in the city centre where exposure to Aedes bite appears to be the highest in Djibouti . The epidemic burst occurred in 2011 and this scenario was reminiscent of the Indian Ocean outbreak: CHIKV had been circulating at low level in 2005 in the naïve population of Reunion Island before an impressive burst in 2006 [34] , [35] . Therefore , a consideration for the 2011 CHIKV outbreak followup study is desirable , so as to complement and or validate our observations . The predominance of DENV and CHIKV most probably reflects the fact that they are transmitted by the same peri-domestic vector , Aedes aegypti , which easily invades , spreads and colonises human habitation [30] . Regarding YFV ( also transmitted by Aedes aegypti ) , the low prevalence numbers observed , the absence of epidemiological relationship with other Aedes-borne viruses and the lack of reported cases over the last decades in Djibouti suggest the identification of vaccinated individuals rather than the existence of local yellow fever foci . Unlike Aedes-borne viruses , viruses potentially transmitted by Culex mosquitoes ( WNV ) were less represented in this study and no strong risk factors could be identified . The circulation of WNV in Djibouti has been previously documented ( i ) in horses , by the detection of specific antibodies ( ELISA followed by PRNT or Western blot ) [36] and ( ii ) in mosquitoes , by the molecular detection of WNV genotype 2 RNA in pools of Culex pipiens spp . torridus and Culex quinquefasciatus [15] . Faulde and collaborators identified WNV RNA-positive mosquito pools in site ML4 ( airport , positive pools were Culex quinquefasciatus ) and ML5 ( market place , positive pools were Culex pipiens spp . torridus ) . Remarkably , of the 5 individuals that tested positive for WNV antibody in the current study , one was living in the ML4 area and three in the ML5 area . Therefore , our results are in accordance with Faulde's findings , but they also confirm the classical discrepancy between the circulation of WNV in mosquitoes and birds and the number of cases of infection in dead-end hosts such as humans and horses ( which in addition include a vast majority of asymptomatic or mild cases that do not draw medical attention ) . The sites ML4 and ML5 are cited from Faulde et al . [15] study areas , and correspond to two Quartiers in the current study area ( Fig . 1 ) , namely , Quartier 1 ( City Centre ) and Ambouli ( Airport area ) , respectively . Regarding RVFV , its circulation in livestock has been repeatedly reported in the region [37]–[40] . However , it is noticeable on the one hand , that Djibouti was not in previous studies [38] , [39] , recognised as a regional hot spot for transmission but a “potential epizootic area” , and on the other hand , that no human case has been reported in Djibouti . In our study , antibody to RVFV was not associated with any epidemiological or environmental parameter that would suggest the implication of mosquitoes . This most probably reflects the predominance of non-arboviral transmission , due to contaminated aerosols ( e . g . , from contact with livestock , in particular in case of miscarriage , manipulation of carcasses , or ritual sacrifice ) . Another important observation was the significant infection rate due to sandfly-borne viruses ( 3 . 7% ) . These infections accounted for the second most prevalent incidences , with a magnitude equal to that of CHIKV . This result , together with the high GMT titres observed using TOSV for neutralisation tests , is highly suggestive of the circulation in Djibouti of TOSV or a closely related virus . This is in agreement with the reference 1976 sero-survey by Tesh and collaborators [13] which identified a 3 . 1% seroprevalence in Djibouti ( “Territory of Afars and Issas” ) using a PRNT technique and the prototype Sandfly fever Naples virus strain . Juxtaposing 1976 and 2010 serological results indicate that viruses belonging to the Naples serocomplex have been circulating for decades in Djibouti and do not represent an emerging pathogen in the region . However , because of the limitation of serological data , a complementary study on sandfly vectors , with a subsequent TOSV virus and related virus isolation and characterization would be of confirmatory importance . In a 1995 article , Fryauff and collaborators proposed an inventory of sandflies in Djibouti [8] . In the coastal plain habitat zone ( in which Djibouti city is located ) the predominant phlebotomine flies were Phlebotomus alexandri and Phlebotomus bergeroti . P . alexandri belongs to subgenus Paraphlebotomus and is closely related to P . sergenti , which has been recently associated with TOSV in Essaouira , Morocco [41]; it therefore represents a credible potential transmission vector for viruses of the Naples serogroup . In Fryauff and collaborators' study , it was found all year long , with a peak during the cool-wet season ( Jan–Feb ) . P . bergeroti is related to P . papatasi , a vector of viruses belonging to the Naples and the Sicilian serogroup . It has never been associated with TOSV , but is the historical vector of Naples virus and Sicilian virus , that caused huge outbreak in military corps stationed in the Mediterranean , the North African and the Middle-East theatres of operations during World War II , and also proved to circulate in the 1970's in Sudan , Ethiopia and Somalia [42] . Most individuals with specific antibodies to TOSV were living in District 1 . Since sandflies occupy very focal habitats , ≤1 km from their breeding sites [43] , this provides robust information for future investigations aiming at formally identifying virus ( es ) and vector ( s ) implicated . Finally , the identification of one individual with high titre VNT antibody to the Alkhumra virus extends the potential distribution area of the virus . This probable constitutes the first suspected autochthonous case in the horn of Africa . Contamination of humans may occur following the bite of ticks ( e . g . , Ornithodoros savignyi , Hyalomma dromedarii but also as a consequence of non-arboviral transmission ( e . g . , after manipulating carcass of infected animals or drinking contaminated raw milk [44]–[46] . A case-control study in Najran , Saudi Arabia , identified animal contact , neighbouring farms , and tick bites in the multivariate modelling whereas univariate analysis retrieved that contact with domestic animals , feeding and slaughtering animals , handling raw meat products , drinking unpasteurised milk , and being bitten by a tick were associated with Alkhumra virus infection [47] . This seropositive case deserves further investigations to clarify the epidemiological risk factors of infection in Djibouti . The lack of complementary information on the subject , such as her travel history and seropositivity profile of ambient host vectors or animals constitute obvious limitations and a follow up investigation will be necessary to complement our data findings . In conclusion , our work strongly suggests autochthonous circulation of arboviral pathogens in Djibouti city , consistent with the past entomological and virological studies done in the same study area [5] , [9] , [15] in which some of the investigated pathogens , such as DENV , WNV , had been isolated and confirmed to be in circulation . The impact of Aedes-borne viruses ( DENV and CHIKV ) was found to be significant and therefore recommended a reinforcement of vector control in urban areas . We also confirmed that the exposure to Culex-borne viruses ( WNV ) was at low rate but deserves a sustained surveillance because of its epidemic potential . Though sandfly- and tick-borne viruses have never been isolated and described previously , this study provides evidence for their circulation ( i . e . risk of exposure ) in Djibouti and advocates for further investigations that would characterise and discern their vectors and their ecological cycles . Overall , the evidence adduced here are resourceful for the Djibouti Citys' Health Department in an effort to customise arbovirus prevention and control programs , that would build on the gains made by the Roll Back Malaria Program [48] .
The arboviruses are a group of viruses transmitted by arthropods such as mosquitoes , ticks , or sandflies . These pathogens have complex life cycles and depend on both arthropods and vertebrate hosts for survival and transmission . Recent global increase in cases confirms that they are of great public health concern . In this study , conducted in the winter of 2010 , the seroprevalence and determinants of infections were investigated in the republic of Djibouti , Horn of Africa . The highest seroprevalence values were observed for mosquito-borne diseases , in particular dengue ( transmitted by Aedes mosquitoes ) ; antibodies to dengue virus were found in a fifth of the sampled population . Most Djiboutians were initially unexposed to Chikungunya virus ( also transmitted by Aedes mosquitoes ) , but a few months later , many got infected , resulting in an outbreak . Of the few West Nile virus seropositive cases detected , the majority were in places where WNV had been previously identified in Culex mosquitoes . In addition , seropositive cases of Toscana-related viruses ( transmitted by sandflies ) , and tick-borne encephalitis virus or Alkhumra-related viruses ( transmitted by ticks ) were also observed . In this study , the risk of arboviral infections was mostly associated with environmental and behavioural risk factors , with highest risk prevailing in the city centre ( District 1 ) . Overall , the results suggest a likely exposure to the local circulation of arboviruses , rather than infections acquired outside the study area . This knowledge , therefore , confirms the impact of arbovirus infections in Djibouti , and is essential for prevention and control programs .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "public", "and", "occupational", "health", "infectious", "diseases", "medicine", "and", "health", "sciences", "epidemiology", "biology", "and", "life", "sciences", "immunology", "microbiology", "tropical", "diseases", "parasitic", "diseases" ]
2014
A Sero-epidemiological Study of Arboviral Fevers in Djibouti, Horn of Africa
The odorant receptor ( OR ) genes constitute the largest mammalian gene family and are expressed in a monogenic and monoallelic fashion , through an unknown mechanism that likely exploits positive and negative regulation . We devised a genetic strategy in mice to examine OR selection by determining the transcriptional activity of an exogenous promoter homologously integrated into an OR locus . Using the tetracycline-dependent transactivator responsive promoter ( teto ) , we observed that the OR locus imposes spatial and temporal constraints on teto-driven transcription . Conditional expression experiments reveal a developmental change in the permissiveness of the locus . Further , expression of an OR transgene that suppresses endogenous ORs similarly represses the OR-integrated teto . Neurons homozygous for the teto-modified allele demonstrate predominantly monoallelic expression , despite their potential to express both copies . These data reveal multiple axes of regulation , and support a model of initiation of OR choice limited by nonpermissive chromatin and maintained by repression of nonselected alleles . Olfactory sensory neurons are activated by odors in the periphery and transmit neural signals centrally to produce the perception of smell . On a molecular level , the diversity of odorous molecules is accommodated by a large number of G-protein-coupled odorant receptors ( ORs ) , which form the largest gene family in mammals [1] . In rodents , individual olfactory sensory neurons select a single OR from more than 1 , 300 encoded in the genome [2]–[4] , and choose one allele at random from which to transcribe it [5] . Neurons expressing the same OR are found scattered in broad zones that stretch across the olfactory epithelium [6] , [7] and project their axons to a pair of discrete loci in the olfactory bulb , forming glomeruli at stereotypical positions [8]–[10] . Activation by odor results in a sparse pattern of activity in the olfactory bulb [11]–[13] . In this way a map is formed in the olfactory bulb in which odor identity may be encoded by unique patterns of glomerular activity . The OR molecules themselves play a prominent role in the positioning of the glomeruli , with subtle changes in the amino acid sequence of the ORs altering their glomerular location [10] . The biological rationale for the extreme transcriptional selectivity of OR regulation may in part be to take advantage of the sensitivity of the system to OR sequence heterogeneity: greater neuronal diversity allows greater olfactory discrimination . Thus , the OR selection process generates on the order of 2 , 500 different sensory neurons and is a critical first step in the generation of the olfactory circuit from the nose to the brain . The process of olfactory receptor choice may be conceptually divided into two phases: an initiation stage , followed by a maintenance period , in which the expression of a single OR gene is preserved for the life of the neuron [14] . It is critical that the selected OR be the stable choice of the neuron , as a change in receptor would alter the ligand sensitivity of the neuron and confound the sensory map in the bulb . Several groups have examined the stability of receptor choice and found that expression of an OR gene is maintained by a feedback signal elicited by functional receptor [15]–[17] . The effect of the feedback on OR choice is thought to involve either the stabilization of a unique transcriptional machinery on the selected OR allele , or the prevention of activation of additional ORs by suppression [17]–[19] . Evidence for suppression has emerged from experiments with transgenes in which the OR coding region was suggested to be the cis-acting substrate for feedback repression [19] . It is possible that elements of both models function during the feedback process . The mechanism of initiation of OR choice is less well understood but has been proposed to involve a process that limits expression to only a single allele at a time . In one model a unique transcriptional apparatus or transcriptional factory [20] has been suggested to activate just one OR allele at a time [17] , [21] , [22] . Recent DNA fluorescent in situ hybridization experiments have demonstrated that OR genes are clustered in discrete loci surrounding pericentromeric heterochromatin [23] . Intriguingly , a single allele of a unique genomic region on Chromosome 14 harboring a locus-control-region-like sequence termed H [16] , [24] , [25] was found to co-localize in trans in the nucleus with the one expressed OR [22] . This finding provided an attractive candidate for such a singular selection machinery . However , the functional significance of this co-localization remains unclear , as knock-out studies have found that H is only able to function in cis [26] . In a different model of initiation , a kinetic mechanism is invoked to limit the initial activation of OR alleles to one [14] , [17] , [27] . This model proposes that receptor genes share regulatory elements but that OR gene transcription is initially so inefficient that only one allele is likely to be activated during a given window of time . Indeed , recent studies have demonstrated that OR genes bear the hallmarks of repressed chromatin [27] . In either model , the successful expression of an OR leads to a feedback mechanism that halts the process and maintains the expression of a solitary member of the OR repertoire . In the kinetic model of OR choice , repressive receptor gene chromatin may be invoked to slow the activation process . However , if a singular apparatus does choose receptor genes , OR chromatin may need to be permissive to allow access to the machinery . In the maintenance phase of OR regulation , the feedback signal could initiate the formation of OR heterochromatin and prevent the activation of additional receptors in a cell . Thus , an assessment of the functional state of an endogenous OR locus at different stages during the expression of the OR repertoire in the olfactory epithelium would further our understanding of the mechanisms involved in this gene regulatory process . We devised a genetic strategy to examine the functional state of an endogenous OR gene in vivo by examining its permissiveness to transcription . In this approach we inserted the tetracycline-dependent transactivator responsive promoter ( teto ) [28] , at the transcriptional start site of the P2 OR gene [21] , by homologous gene targeting in mouse embryonic stem cells ( ES cells ) , to make a series of alleles subject to conditional activation . With these modified P2 alleles we may functionally “interrogate” the OR locus in vivo by attempting to activate its transcription with the tetracycline-dependent transactivator ( tTa ) [28] . As all of the flanking P2 sequences sufficient for regulation are preserved in these minimally modified alleles ( unpublished data ) , we anticipate that regulatory constraints imposed upon the endogenous OR promoter will similarly impinge upon the exogenous tet operator . Further , this strategy lets us take advantage of the conditional activation of the tTa system to probe temporal changes in OR chromatin , by staged administration of doxycycline [28] , [29] . Using this approach we have revealed important parameters of OR gene regulation . It is possible to activate the OR from within its locus , and we observe zonal regulation of the teto , suggesting that this hallmark of OR gene expression is accomplished by repression . Within the P2 zone , the tet-modified allele is sparsely expressed in young mice but slowly increases in frequency over time . Remarkably , pre-activation of these alleles with tTa results in a stable , tTa-independent over-expression . Using staged administration of doxycycline to regulate the activation of the tet-modified alleles , we observe a developmental change in permissiveness that is concurrent with the maturation of the epithelium and is not dependent on the presence of the coding region of the receptor . Despite the continuous presence of tTa , the tet-operator-linked P2 gene is suppressed by the pervasive expression of an OR transgene previously demonstrated to repress the endogenous repertoire [18] , an effect that is independent of the OR open reading frame . Finally , in mice homozygous for the tet-modified alleles , the tTa-driven expression of the OR is observed to be largely monoallelic , despite the genetic potential for biallelic activation , suggesting the existence of a functional asymmetry in the OR alleles . Together these experiments lend support for a kinetic model of OR choice , governed by limited initial activation and maintained by the feedback repression of nonselected receptor genes . We used a gene targeting approach to examine the transcriptional permissiveness of a mouse OR gene , P2 , in its chromosomal locus in vivo . In this strategy we inserted teto into the 5′ region of the endogenous P2 gene , to allow tTa [28] to functionally “interrogate” the locus by attempting to drive transcription across the P2 gene ( Figure 1A–1C ) . Using homologous recombination in mouse ES cells , we generated a genetically modified mouse line ( tet-P2 ) in which the teto was inserted at the start site of transcription of the P2 gene [21] , while retaining the 5′ upstream regions required for endogenous P2 expression ( unpublished data; Figure 1A ) . The green fluorescent marker protein GFP , linked to an internal ribosomal entry site ( IRES ) , was inserted into the 3′ noncoding region of the P2 gene [30] to monitor its transcriptional activation ( Figure 1A ) . Thus , all neurons that express the tet-P2 allele would synthesize a bicistronic mRNA allowing the translation of both the P2 receptor and GFP . To examine the role of the OR coding region in the initiation or maintenance of singular OR choice , we also generated tet-P2Δ , a mouse line bearing a modification of the P2 locus analogous to the tet-P2 allele , except for the deletion of the P2 coding region ( Figure 1B ) . To accurately assess the transcriptional permissiveness of the teto-bearing P2 alleles , it is critical that tTa be pervasively expressed across the olfactory neuroepithelium . We therefore used two mouse lines that express tTa in olfactory sensory neurons , as shown in Figure 1C: OMP-IRES-tTa and CaMKII-tTa [29] , [31] . The olfactory marker protein ( OMP ) is expressed in all mature olfactory sensory neurons [32] . Correspondingly , the OMP-IRES-tTa line co-expresses OMP and tTa in mature olfactory sensory neurons through an IRES element linked to the tTa gene and inserted into the 3′ UTR of OMP [31] . The CaMKII-tTa strain bears a transgenic construct in which the production of tTa is directed by the CaMKII gene promoter [29] . To determine the frequency of expression of tTa in the olfactory epithelium of CaMKII-tTa mice , we examined tissue by immunohistochemistry ( IHC ) with antiserum directed against the VP16-derived activation domain of the tTa protein . We observed pervasive expression of tTa in olfactory sensory neurons ( >95% ) of CaMKII-tTa mice , compared to controls ( Figure 1D versus 1E , and data not shown ) . To confirm that CaMKII-tTa mice can indeed activate teto-linked genes in the olfactory epithelium we crossed the CaMKII-tTa line with a previously generated strain ( M71-tg ) that harbors a transgenic construct in which the OR M71 and the marker protein tau-lacZ are under the control of the tet operator; this transgene can be activated in the vast majority of olfactory sensory neurons by OMP-IRES-tTa [18] . We verified that CaMKII-tTa similarly drives expression of the M71-tg in >95% of the olfactory neurons ( Figure 1F–1H ) , confirming that CaMKII-tTa provides high-frequency expression of tTa . Importantly , as both the P2 and OMP genes reside on Chromosome 7 [21] , it is not feasible to generate mice bearing both OMP-IRES-tTa and homozygous modification of the P2 alleles . To circumvent this problem we used the CaMKII-tTa line to allow the generation and analysis of homozygous tet-P2 animals . In initial experiments we crossed mice carrying the tet-P2 or tet-P2Δ allele with the OMP-IRES-tTa line , and the resulting compound heterozygous animals were analyzed for GFP expression in whole-mount preparations . Activation of the tet-P2 allele by tTa results in sparse expression across the olfactory epithelium at P14 , as observed by whole-mount fluorescent microscopy ( Figure 1J ) . In comparison to control animals bearing a P2-IRES-GFP allele [30] , in which GFP is expressed from the P2 locus under the control of the endogenous promoter , tTa elicits only a ∼5-fold increase in the frequency of expression of the tet-P2 allele ( from 0 . 1% to 0 . 5% of the cells ) in OMP-IRES-tTa/tet-P2 animals ( Figure 1I and 1J , and data not shown ) . In the control P2-IRES-GFP animals , GFP+ axons project to the olfactory bulb and form a glomerulus at a stereotypical position [10] . Axons from tet-P2-expressing neurons in P14 OMP-IRES-tTa/tet-P2 animals form multiple glomeruli , clustered in a region of the bulb corresponding to that of the wild-type P2 glomerulus ( Figure 1I , arrow ) , as well as scattered at ectopic positions ( Figure 1J ) . In adult ( >P60 ) OMP-IRES-tTa/tet-P2 animals , tTa-driven tet-P2 transcription becomes more pervasive , with expression seen in the main olfactory epithelium and in the vomeronasal organ ( VNO ) ( Figure 1K , arrow ) and a concomitant increase in the extent of innervation of the olfactory bulb ( Figure 1K ) . Similar expression is observed when OMP-IRES-tTa drives activation of the deletion allele tet-P2Δ , with expression in the main olfactory epithelium and VNO and broad innervation of the olfactory bulb ( Figure 1L ) . The overall frequency of tTa-driven expression of the tet-P2 and tet-P2Δ alleles in the olfactory epithelium in adult animals was determined by immunohistochemical analyses of neurons dissociated from the olfactory epithelium . We observed in bulk-dissociated cells from the olfactory epithelium that 55% of all OMP+ cells ( n = 629 ) express the tet-P2 allele and 47% express the tet-P2Δ deletion allele ( n = 452 ) in adult mice ( data not shown ) . We observed comparable frequencies of expression of the teto-driven allele in coronal sections through the VNOs of OMP-IRES-tTa/tet-P2 and OMP-IRES-tTa/tet-P2Δ adult animals ( Figure 1M and 1N ) . Analyses of the patterns of transcription of OR genes has revealed that individual OR genes are expressed in neurons found in broad zones running across the neuroepithelium [6] , [7] , [33]; the expression of ORs is spatially restricted . The presence of such patterns of OR choice may reflect the positive effect of spatially restricted trans-acting factors that activate OR genes in a zonal manner . Alternatively , a common regulatory machinery may be at work across the neuroepithelium , with spatial restriction arising from the repression of OR genes outside of their zones . We have used the tet-modified P2 alleles to examine the phenomenon of zonal restriction of ORs , analyzing expression of tet-P2 and tet-P2Δ driven by tTa across the zones of the olfactory epithelium . A schematic of the olfactory epithelium depicting the P2 zone ( shaded region ) is shown in Figure 2A . In coronal sections of control P2-IRES-GFP lines ( at P14 ) subject to IHC for GFP , the expression of P2 is characteristically restricted to the zone II/III region ( Figure 2B and 2D ) , with the wild-type frequency of P2 expression in this zone ∼7% ( Figure 2D ) . Neurons choosing the P2 receptor outside of its zone are rarely observed [10] . Despite the uniform presence of tTa across the neuroepithelium , we observed a zonal restriction of tTa-driven tet-P2 expression in coronal sections of OMP-IRES-tTa/tet-P2 mice at P14 ( Figure 2C and 2E ) , similar to the pattern of wild-type P2 expression . Compared to wild-type controls ( Figure 2B and 2D ) , the frequency of tTa-driven tet-P2 expression in the P2 zone is elevated to ∼14% of the cells ( Figure 2C and 2E , and data not shown ) . Analysis of epithelia from both tet-P2 and tet-P2Δ animals revealed a graded frequency of tTa-driven tet-P2 allele expression , despite the uniform and pervasive presence of the activating tTa transcription factor . Coronal sections of epithelia of adult CaMKII-tTa/tet-P2 mice examined in different zones ( boxed areas shown in Figure 2A ) reveal a frequency of choice of 74% from within the P2 zone ( Figure 2G ) , 22% from a more dorsal position ( Figure 2F ) , and 10% from the indicated ventral zone ( Figure 2H ) . Analogous results were obtained for the tet-P2Δ allele , which lacks the P2 coding region . We observed tet-P2Δ expression in 60% of the neurons in the P2 zone ( Figure 2J ) , in 16% of more dorsal neurons ( Figure 2I ) , and in 10% of neurons in the ventral region ( Figure 2K ) . In control experiments , we observed that the tet-M71 transgene , which is pervasively activated by OMP-IRES-tTa [18] , is similarly activated across all zones in the olfactory epithelium by tTa expressed from the CaMKII-tTa transgene ( Figure 2L–2N ) . This result confirms the uniform expression across the epithelium of tTa from the CaMKII transgene and suggests that the zonal restriction of tet-P2 expression is not a consequence of the limited availability of tTa . Further , we observed an analogous zonal restriction of tet-P2 when tTa expression was driven by OMP-IRES-tTa . In coronal sections subject to two-color RNA in situ hybridization with riboprobe for OMP and GFP transcripts , pervasive expression of OMP is observed from both the P2 zone ( II/III ) and the more ventral zone IV ( Figure 2P and 2S ) . However , GFP RNA from the tet-P2 allele is observed in 80% of the cells in the P2 zone ( Figure 2O ) and in only 15% of the neurons in the more ventral region ( Figure 2R ) . This zonal restriction of activation of the tet-P2 allele is specific for the tet operator inserted into the P2 locus , and has not been observed for tet-operator-driven OR transgenes , nor non-OR-containing transgenes [18] , [19] , [31] . The permissiveness of the tet-P2 allele is thus graded across the zones of OR expression in the olfactory epithelium , with the most frequent expression observed from within the wild-type P2 zone . Taken together , these results suggest that the spatial restriction observed for OR gene expression may be due to increasing levels of repression of the OR locus away from its zone ( see Discussion ) . In addition to the spatial regulation imposed on the tet-P2 allele , we observed a temporal change in the frequency of activation by tTa in the epithelia of OMP-IRES-tTa/tet-P2 mice . We examined coronal sections of OMP-IRES-tTa/tet-P2 mice at different ages ( Figure 2U–2Z ) and observed an increase in the frequency of expression of tet-P2 , within the P2 zone , from 11% to approximately 96% over time . These data suggest a kinetic component to the activation of the locus , in which tTa may activate tet-P2 in an increasing proportion of the cells over time . Taken together these results imply that the zonal expression observed in OR regulation is due to graded repressive effects and that the OR coding region is not required for this spatial repression . These data support a model in which zonal control of receptor expression is mediated by repression of the OR promoter and depict a scenario in which the transcriptional permissiveness of the OR locus could dictate its frequency of choice . The apparent repressed state of OR chromatin , revealed through our functional in vivo studies of the tet-P2 allele ( Figure 2 ) and described biochemically elsewhere [27] , suggests that the OR selection mechanism could utilize the permissiveness of the OR locus to control the frequency of OR choice . In this scenario , we reasoned that pre-activation of the tet-P2 locus may alter its frequency of choice by the endogenous selection machinery by increasing the permissiveness of the locus . To test this possibility , we pre-activated the tet-P2 locus with tTa , then followed with a doxycycline treatment , which ablates tTa binding and thus transcriptional activation of the locus [28] . This approach is feasible because the tet-P2 allele retains its endogenous control sequences , moved 5′ by the insertion of the tet operator ( Figure 1A ) yet still functional . We can detect the use of the endogenous promoter ( versus the tet operator ) by monitoring the use of the endogenous transcriptional start site , upstream in the tet-P2 allele , using RNA in situ hybridization ( Figure 3B ) . If the endogenous promoter is active , the tet-P2 transcript will contain both GFP ( Figure 3B , green probe ) and tet operator sequences ( Figure 3B , red probe ) . In initial experiments we performed two-color RNA in situ hybridization on coronal sections of olfactory epithelium from tet-P2 mice , with RNA probes for tet operator and GFP sequences . Neurons expressing the tet-P2 allele are identified by riboprobes for GFP ( Figure 3D ) . Consistent with transcription directed by the endogenous promoter ( and initiated upstream of the tet operator ) , these neurons are also detected by riboprobes for tet operator sequence ( Figure 3C and 3E ) . In the absence of doxycycline , CaMKII-tTa drives massive over-expression of the tet-P2 allele , as demonstrated by RNA in situ hybridization with riboprobes for GFP ( Figure 3G and 3H ) . However , we did not observe the use of the endogenous start site , upstream of the tet operator , unlike in the transcription of the tet-P2 allele on its own . This is demonstrated by the absence of RNA in situ signal generated by the tet operator probe ( Figure 3F and 3H , within the P2 zone ) or outside of the P2 zone ( data not shown ) . These data are consistent with transcription initiation being directed by the tTa bound to the tet operator . Significantly , after 48 h of doxycycline treatment in mice bearing CaMKII-tTa and tet-P2 , we observed that transcription of the tet-P2 allele persists at an over-expressed frequency in the P2 zone ( Figure 3J and 3K ) , as well as outside this zone ( data not shown ) . Concomitant with the persistent expression of tet-P2 is a switch in start site usage from the tet operator start site to the start site associated with the endogenous P2 promoter , as indicated by the detection of tet operator sequence included in the tet-P2 transcript ( Figure 3I and 3K ) . The continued expression of the tet-P2 allele in the absence of tTa binding , coupled with the switch to the upstream transcriptional start site , suggests that the endogenous P2 promoter is active to direct transcription of the OR in doxycycline-treated mice . These observations suggest that after an initial activation of the tet-P2 allele by tTa the P2 promoter is active on the gene . Further , these experiments imply that the frequency with which the endogenous expression machinery may assemble on an OR gene may be altered by the prior transcriptional state of that gene , which may influence the chromatin state of the locus . These data are consistent with a model in which the frequency of selection of an OR allele is proportional to the transcriptional permissiveness of its locus . Once chosen , the expression of a functional OR may elicit a signal that feeds back and terminates the selection process , to maintain singular receptor choice in the neuron [15]–[17] . The mechanism by which the feedback process suppresses the expression of additional OR genes is unknown , but one model proposes that feedback induces a generalized repression of nonselected receptor alleles , making them inaccessible to the selection machinery [14] . To examine this stage of the OR selection process , we used conditional control of transcription of the tet-P2 alleles through doxycycline ablation of tTa binding [28] . By using staged administration of doxycycline we sought to determine changes in the transcriptional permissiveness of the tet-P2 locus at different times during the expression of the OR repertoire ( Figure 4A ) . Using this approach we examined the permissiveness of the tet-P2 and tet-P2Δ alleles to tTa-mediated activation during different windows of time during development . In control experiments , olfactory epithelia from OMP-IRES-tTa/tet-P2 mice were examined at P30 for tet-P2 expression , as revealed by detection of GFP . We observed tet-P2-expressing neurons in the P2 zone at frequencies consistent with previous analyses ( Figures 4D and 2U , and data not shown ) . We next administered doxycycline-infused food to OMP-IRES-tTa/tet-P2 mice from embryonic day 0 ( E0 ) to P5 , via maternal feeding , and then maintained the animals without doxycycline to P30 . In these mice we observed a dramatic decrease in the number of cells expressing tet-P2 and a basal shift in their distribution in the neuroepithelium ( Figure 4E ) . To quantify this distribution we analyzed the relative position of tet-P2 cells in the olfactory epithelium . In olfactory epithelia of OMP-IRES-tTa/tet-P2 animals maintained without doxycycline , the mean relative position of tet-P2+ cells ( normalized to the height of the epithelium ) was 0 . 424 ( Figure 4G , purple ) , whereas in olfactory epithelia of OMP-IRES-tTa/tet-P2 animals maintained on doxycycline from E0 to P5 , and then released from doxycycline treatment from P5 to P30 , the mean relative position of tet-P2+ cells was 0 . 304 ( Figure 4G , orange , p<0 . 0001 ) . In a final doxycycline administration regimen , OMP-IRES-tTa/tet-P2 animals were fed doxycycline from E0 to P30 , a point in time at which the majority of olfactory sensory neurons have chosen an OR to express [34] , and then discontinued doxycycline-mediated inhibition of tTa from P30 to P60 . In these mice we observed virtually no induction of the tet-P2 allele by tTa above that observed in the absence of tTa ( Figure 4F ) . Taken together , these experiments provide evidence for a developmental change in the permissiveness of the locus to transcription directed by the tet operator and tTa concomitant with the development of the olfactory epithelium . This repression may be the result of the feedback signal elicited by functional ORs and could provide a mechanism for the maintenance of OR expression . Previous studies have suggested that the sequence of the OR coding region itself plays a prominent , cis-acting role in feedback suppression of OR genes [19] . We therefore examined the transcriptional permissiveness of the tet-P2Δ allele , in which the coding region of P2 has been deleted , at a point in time at which the tet-P2 allele no longer allows tTa-directed transcription of the locus ( Figure 4F ) . In control experiments the OMP-IRES-tTa/tet-P2Δ line was examined for tTa-driven expression of the tet-P2Δ allele by IHC at P60 . Consistent with previous results , we observed high-frequency activation of the allele in the olfactory epithelium within the P2 zone ( Figure 4B ) . However , when fed doxycycline from E0 to P30 and then analyzed after 30 additional days in the absence of doxycycline , we observed a dramatic decrease in the ability of tTa to induce expression of the tetP2Δ allele ( Figure 4C ) , comparable to the level of suppression observed in analogous experiments with tet-P2 ( Figure 4F ) . The developmental repression of the modified P2 alleles is specific to the P2 locus and was not observed for other tTa-driven transgenes in the olfactory epithelium . Importantly , when the M71-tg transgenic line was treated with doxycycline from E0 to P30 and analyzed after an additional 30 days in the absence of doxycycline , expression of the transgene was robustly induced ( data not shown ) . These results strongly suggest that unselected OR loci undergo developmental repression as olfactory sensory neurons mature and choose an OR . These data also demonstrate that this change in permissiveness of the locus does not require the participation of the OR coding region sequences . Together these data suggest that the OR promoter sequences are the sole mediators of this level of regulation . These data further suggest that there is a developmental window , terminating soon after the onset of OMP expression , during which OR loci are relatively permissive and after which they become highly repressed ( see Discussion ) . The developmental change in the transcriptional permissiveness of the tet-P2 locus suggests a mechanism of feedback control of OR choice mediated by the OR promoter elements and effected through repression . To further examine this process we asked whether the tet-P2 allele would be subject to the suppressive effects of a ubiquitously expressed OR transgene ( M71-tg ) that we previously described [18] . This line carries an M71 transgenic construct , driven by teto/tTa , that expresses the OR M71 and the marker protein tau-lacZ in greater than 95% of the olfactory sensory neurons . The pervasive expression of M71 suppresses the endogenous OR repertoire [18] . If M71-tg were to similarly suppress tet-P2 , it would do so despite the continued presence of tTa . This would suggest a causal link between the change in transcriptional permissiveness observed at the P2 locus , and the feedback suppression exerted by the expression of the M71 transgene . We therefore crossed OMP-IRES-tTa/tet-P2 lines into mice bearing the M71 transgene and analyzed the tTa-driven expression of both teto-linked loci . Coronal sections through the olfactory epithelia of OMP-IRES-tTa/M71-tg mice subject to immunohistochemical detection of lacZ reveal the pervasive expression of the M71 transgene ( Figure 5D ) . Coronal sections through the olfactory epithelia of OMP-IRES-tTa/tet-P2 mice subject to immunohistochemical detection of GFP reveal typical frequencies of tTa-driven tet-P2 expression in the P2 zone at P30 ( Figure 5B and 5C ) . In the OMP-IRES-tTa/tet-P2/M71-tg neuroepithelia , the M71 transgene is pervasively expressed ( Figure 5D and 5F ) , while the expression of tet-P2 is markedly reduced ( Figure 5E and 5F ) . We extended this experiment to the tet-P2Δ allele , observing typical frequencies of tTa-driven tet-P2Δ expression in the OMP-IRES-tTa/tet-P2Δ line ( Figure 5H ) , while the expression of the M71 transgene similarly suppressed the tet-P2Δ allele ( Figure 5J–5L ) in a manner similar to that observed for tet-P2 . The suppression of the tet-P2 loci is not due to competition for limited amounts of tTa , as we observed that the expression of other teto-driven alleles remained unaffected by tet-M71 expression [18] . Thus teto-linked P2 alleles are subject to the suppressive effects elicited by the pervasive expression of the M71 transgene similarly observed for the endogenous OR repertoire . The M71-transgene-mediated suppression occurs despite the continued presence of tTa and is observed at the tet-P2 locus even in the absence of the P2 coding region , further supporting a model of feedback suppression mediated by OR control elements rather than the OR open reading frame . It is interesting to note that the tet-P2 allele fails to suppress the M71 transgene , which implicates the cis-acting elements present in the endogenous OR locus that are absent from the M71 transgene in the feedback process ( see Discussion ) . The expression of mammalian OR genes is monogenic , whereby only one member of the gene family is selected per cell , and monoallelic , with only one of the two copies of the gene transcribed [2] , [5] . Monoallelic expression of ORs is not the result of an absolute inactivation of one of the two alleles , as lineage-marking studies have demonstrated their successive activation , known as “switching” [17] . OR genes are asymmetrically copied during S phase , with one allele duplicated early and one late [5] . It is possible that this staggered replication timing reflects differential epigenetic marking , biasing the likelihood of expression of one allele over the other . To explore the possibility of a functional nonequivalence between OR alleles , and to extend our analysis of the permissiveness of OR loci , we next asked whether tTa could drive biallelic OR expression in homozygous tet-P2 animals . To conduct this experiment we constructed an additional tet-P2 allele in which the fusion protein tau-lacZ was used as a marker to allow us to distinguish expression of each of the two tet-P2 alleles ( Figure 6B ) . We generated a genetically modified mouse line ( tet-P2Z ) , by homologous recombination in mouse ES cells , identical to the tet-P2 line except that the fusion marker protein tau-lacZ , linked to an IRES , was inserted into the 3′ noncoding region of the P2 gene ( Figure 6A ) . Thus , all neurons that express the tet-P2 allele would synthesize a bicistronic mRNA allowing the translation of both the P2 receptor and tau-lacZ proteins . Similarly to the GFP-marked tet-P2 allele , tet-P2Z expression driven by tTa was observed in comparable numbers of neurons in the main olfactory epithelium and the VNO ( Figure 6C and 6D ) . To examine the possibility of biallelic OR expression , we generated a mouse line carrying the CaMKII-tTa transgene and compound heterozygous for the tet-P2 modification: one allele marked with GFP and the other with tau-lacZ ( Figure 6B ) . We analyzed expression of the tet-P2 alleles by immunohistochemical detection of GFP and lacZ in coronal sections of the olfactory epithelium of CaMKII-tTa/tet-P2/tet-P2Z animals . Both tet-P2 alleles were expressed in the epithelium at roughly equal frequencies , yet , remarkably , despite the genetic potential to express both , we observed that the vast majority of olfactory sensory neurons transcribed only one of the two tet-P2 alleles , with biallelic expression observed in only ∼3% of the neurons ( Figure 6E–6G and 6E′–6G′ ) . We further analyzed these data by measuring the height of double ( tet-P2+tet-P2Z+ ) and single positive ( tet-P2+ or tet-P2Z+ ) neurons in the epithelium and observed a difference between the two populations: double positive neurons were found lower in the epithelium than the single positives , with mean relative positions ( normalized to the height of the epithelium ) of 0 . 424 and 0 . 501 , respectively ( Figure 6H , p = 0 . 0068 ) . These results indicate that biallelic expression of an OR gene from its endogenous locus is possible but very infrequent , and may indicate a functional nonequivalence between the alleles . In this scenario an asymmetry exists between the two P2 alleles in which one has an increased likelihood of being activated over the other: the first allele activated would trigger the feedback process , repressing the other allele , which would lose the ability to be activated by tTa . Intriguingly , the distribution of cells expressing tet-P2 from both alleles is skewed basally , suggesting that allelic inclusion more often occurs in the younger sensory neurons ( see Discussion ) . One of the hallmarks of OR regulation is the localization of neurons expressing a given OR to a diffuse but restricted region , or zone , across the olfactory epithelium [6] , [7] , [33] . We have observed that the expression of the tet-P2 allele is similarly restricted , with the highest frequency of activation seen within the endogenous P2 zone , and diminishing frequency away from this region . We have demonstrated the pervasive expression of the tTa protein throughout the epithelium , and the restricted transcription of the tet-P2 gene . While it is a possibility that a positive-acting factor , localized to the P2 zone and acting in concert with the pervasively expressed tTa , could defeat repression at the OR locus in a zonal fashion , the most parsimonious explanation for this observation is that the OR gene is repressed outside of its zone . Further , the zonal repression observed for the tet-P2 allele does not possess sharp boundaries , but rather appears to exist as a gradient . In this scenario an OR zone may thus correspond to a local minimum of repression for the OR gene , and it is possible that a continuous gradient of chromatin states exists across the olfactory epithelium , such that OR genes exhibit a region of maximal permissiveness wherein they are most likely to be activated . In this model , each OR may have its own unique micro-zone , a scenario that would aid in the distribution of the OR repertoire across the epithelium and that is consistent with detailed analyses of OR zonal expression [33] . Activation of the tet-P2 allele in olfactory sensory neurons by tTa is initially sparse , despite the pervasive expression of tTa across the epithelium ( driven either by OMP or CaMKII ) . We observed that the frequency of expression of tet-P2 increases slowly over time , a phenomenology of expression that is in contrast to that seen for the M71 transgene , whose robust frequency of expression matches that of the tTa that drives it [18] . This finding immediately suggests that the P2 locus imposes a constraint on the tet operator that lowers the probability of its expression . The integration of this probability over time accounts then for the gradual increase in the appearance of tet-P2-positive neurons in the neuroepithelium . The probability of expression is not uniform across the epithelium , but rather has a maximum within the observed zone of the receptor and tapers off outside of this region . This view of the initiation of OR selection is analogous to the “accessibility hypothesis” invoked to explain the regulation of V ( D ) J recombination [35] , [36] , and the limited permissiveness of the P2 locus we observed could provide a mechanism by which the initiation of OR expression could be tuned to a level where only one OR may be expressed in a given window of time . We have observed that the tet-P2 allele may continue to be over-expressed in the olfactory epithelium after initial tTa activation , despite ablation of tTa binding to the tet operator by doxycycline treatment ( Figure 3 ) . The tTa-independent over-expression is highest from within the P2 zone and tapers off away from it , in proportion to the tTa-driven frequency . Intriguingly , concomitant with the tTa-independent over-expression , we also observed a switch in start site usage in the transcription of the tet-P2 allele , upon doxycycline treatment , from the +1 of the tet operator to the endogenous start site ( retained in the construct ) . These data may indicate that the endogenous OR selection machinery assembles on the P2 promoter and takes over expression of the gene when tTa-driven transcription is stopped by doxycycline . It is possible then that the endogenous machinery assembles on the P2 promoter , at higher than wild-type frequency , due to a change in the accessibility of the tet-P2 locus generated by the activation of the tet operator by tTa . Such a phenomenon is believed to be operant in Igκ gene rearrangement , where germline transcription alters chromatin structure and facilitates access of the recombination machinery [35] . Together these data are consistent with a mechanism in which the permissiveness of the OR locus limits access to the transcriptional machinery , to dictate the frequency of initial OR choice . Recent work from the Lomvardas lab [27] has revealed biochemical hallmarks of OR chromatin that are consonant with our functional studies . Magklara et al . found that OR chromatin is enriched in histone H3 lysine 9 trimethylation and histone H4 lysine 20 trimethylation , consistent with features of both facultative and constitutive heterochromatin [27] . Further , they found that OR chromatin is compacted in the olfactory epithelium , a finding consistent with the limited transcriptional permissiveness to activation by tTa that we observed for the tet-P2 allele . Thus , the biochemical basis for the limited permissiveness observed for the OR locus may be the result of heterochromatization of OR loci . Finally , a recent analysis of OR promoters reveals the enrichment of IKZF1 binding sites within 100 bp of the transcriptional start site , a finding that could explain the targeting of repressive machinery to OR chromatin [37] . The selection of a single OR gene by the olfactory sensory neuron is maintained by a feedback signal generated by functional receptor . We used the conditional expression afforded by the teto/tTa system , through the staged administration of doxycycline , to examine OR maintenance , and observed a developmental change in the permissiveness of the tet-P2 locus . Our experiments demonstrate that by P30 , tTa is effectively unable to activate the tet-P2 allele , suggesting that the tet-P2 locus , which allows activation of tet-P2 early , becomes fully repressed . The timing of this change in permissiveness is consistent with the age at which the olfactory epithelium has mostly completed maturation and OR expression has reached a plateau [38] . This repression of the OR locus may be the functional consequence of the feedback mechanism [16] , [17] , [39] . Previous studies have reported that the activation of teto by tTa is inefficient in certain populations of neurons in the central nervous system of adult mice , and it has been proposed that teto undergoes nonspecific silencing [40] . However , we , and others , have observed highly efficient activation of multiple teto-driven transgenes in olfactory sensory neurons [18] , [19] , [30] , [31] , [41] . Thus , we argue that the developmental repression of the tet-P2 alleles reflects specific , physiological changes in the OR chromatin state . A developmental repression of OR transgene expression has been reported in experiments in which the tet operator was used to drive transcription of OR coding regions [19] . In this study , the onset of OMP expression in the olfactory epithelium appeared to mark the point after which the OR transgene became repressed , and the authors argued that the OR coding region itself was the cis-acting sequence necessary for this phenomenon . However , our previous studies similarly examining the expression of teto-regulated OR transgenes showed no such repressive effect [18] . In the present experiments , we used homologous recombination to allow an examination of the transcriptional permissiveness of an OR gene in its endogenous locus , with all flanking DNA elements preserved . In this more defined genomic context , we observed an increase in repression of the locus over time ( Figure 4 ) . We also observed repression of the tet-P2 alleles in the context of the M71 transgene ( Figure 5 ) . Importantly , neither the change in permissiveness nor the sensitivity to suppression by M71-tg was dependent on the OR coding sequences , as we observed similar effects with the tet-P2Δ allele , which lacks the P2 coding region . Thus , it is highly likely that the cis-acting elements that govern repression reside in the flanking DNA , including regions that have previously been defined as necessary for transcription of an OR locus [42] , and that are similarly required for P2 locus expression ( unpublished data ) . Our experiments using the staged administration and withdrawal of doxycycline reveal a developmental window during which OR loci retain the ability to be activated ( Figure 4E , and analysis in Figure 4G ) . The end of this period is likely demarcated by the developmental stage shortly after the onset of OMP expression . This window is revealed in Figure 4E , where tet-P2 may be activated by tTa supplied by OMP-IRES-tTa in younger OMP+ neurons , but not in the older OMP+ cells that reside more apically in the epithelium . Interestingly , this window is analogous to the time period during which we have previously observed OR “switching” prior to stabilization of OR choice [17] . It is important to note that the olfactory epithelium continually regenerates and thus consists of a heterogeneous mix of neurons born at different times . The olfactory sensory neurons occupy positions in the epithelium corresponding roughly to age: a developmental stratification in which newly born neurons are located more basally and move up to more apical layers as they age . Maximal neurogenesis is observed in the first postnatal weeks and slows after a month to maintain the population of sensory neurons throughout the life of the animal . The activation of tet-P2 observed after doxycycline withdrawal therefore may occur either in cells that were OMP+ before withdrawal or those added to the OMP+ population after withdrawal . The marked inability of tTa to activate tet-P2 in older OMP+ neurons , when doxycycline is discontinued at P5 , clearly shows that tet-P2 is repressed in this population . The subpopulation of cells that allows activation of tet-P2 by tTa in the lower OMP+ stratum may be composed of neurons previously resident in this layer , or added to it subsequent to the discontinuation of doxycycline treatment . In either scenario , it is clear that in the older neurons that are apical to this region , tet-P2 has lost the ability to be activated by tTa . Olfactory neurons choose one OR and express it randomly from one allele [5] , [43] . Unlike the random and heritable inactivation of one of the two X chromosomes , both OR alleles can be activated in the same neuron , albeit sequentially , especially if the first allele chosen is nonfunctional [17] . We have examined the phenomenon of monoallelic OR expression using two tet-P2 alleles marked with two different reporter proteins ( lacZ and GFP ) . Despite the genetic potential of cells to express both tet-P2 alleles , we observed biallelic expression only 3% of the time . As the overall frequency of expression of the tet-P2 allele is roughly 50% , we should expect to see both alleles transcribed in the epithelium 25% of the time . What could account for this discrepancy ? It is possible that the low permissiveness to transcription of any OR allele is such that feedback repression may occur before any subsequent OR activation . It is also possible that a functional asymmetry exists between OR alleles , such that in a given cell , one allele is more likely to be activated than the other . The fact that receptor alleles display replication-timing asymmetry [5] suggests that a differential marking of alleles may exist and be used to stagger activation , providing enough time between possible selection events to allow feedback repression and ensure monoallelic expression . The intriguing observation that cells expressing tet-P2 biallelically were found in a more basal region than those expressing tet-P2 monoallelically suggests that cells expressing tet-P2 biallelically make up a younger neuronal subpopulation . It is possible , therefore , that a refinement mechanism exists that prevents such biallelic expression , whereby the maturing neurons force the extinction of one of the two alleles . It is further possible that a competitive process between OR alleles underlies this mechanism of monoallelic expression . We thus favor a model of OR selection in which kinetic mechanisms ensure the initial stochastic selection of an OR allele . In this model , OR loci are in a semi-permissive state that limits initial OR activation to ensure that only one OR gene may be randomly activated within a given window of time . The inefficiency of this initial selection process ensures that the first functional receptor gene chosen will trigger the feedback mechanism prior to any subsequent OR activation . In this way , the initial expression of OR is probabilistic , resembling variegated activation [44] . The chosen OR allele is then maintained as the sole receptor , after the feedback mechanism triggers a change in the chromatin of the nonselected OR alleles , making them inaccessible . By what mechanism would the selected OR allele remain transcriptionally active in the context of the feedback repression ? It is possible that there is a unique nuclear compartment involved in the maintenance of OR choice that protects the selected allele . In this scenario , the single activated OR allele would gain entrance into this specialized compartment and be shielded from feedback repression , thus stably maintaining singular OR choice . The existence of such a compartment may be revealed by the observation that an olfactory locus control region , the H element , on Chromosome 14 [16] , [24] , [25] associates with active receptor alleles in trans [22] . This association may mark a specialized transcriptional factory [20] for OR expression required for the maintenance of singular OR expression . Olfactory turbinates were dissected out and immediately fixed in freshly prepared 1% paraformaldehyde ( Electron Microscopy Sciences ) in 1× PBS on ice for 60 min , followed by decalcification in 0 . 45 M EDTA , 1× PBS , for 18 h at 4°C . Tissue was frozen in O . C . T . compound ( Sakura-Fintek ) , and 16-µm sections were cut on a cryo-microtome ( Leica ) and collected on Superfrost Plus slides ( Fisher Scientific ) . IHC was performed with rabbit antisera against GFP ( Molecular Probes ) used at 1∶1 , 000 , goat antiserum directed against beta-galactosidase ( Biogenesis ) used at 1∶1 , 000 , and rabbit anti-VP16 ( Abcam ) used at 1∶500 . Secondary antibodies ( donkey ) conjugated to Cy3 ( Jackson Labs Technologies ) or Alexa 488 ( Molecular Probes ) were used to visualize primary antisera in conjunction with Toto-3 nuclear counterstain ( Molecular Probes ) . Stained sections were visualized , and whole-mount visualization of endogenous GFP fluorescence was performed , with Zeiss 510 and 710 laser-scanning confocal microscopes . Relative cell position in the olfactory epithelium was determined by measuring the distance of the receptor positive neuron from the neuroepithelium–lamina propria interface divided by the basal-to-apical height of the epithelium . Graph points represents an individual cell , with n = 100 for each genotype . All measurements were performed using Image J software , and graphs were created , and corresponding statistics performed , using GraphPad Prism 6 . 0 software . Olfactory turbinates were dissected out and immediately fixed in freshly prepared 1% paraformaldehyde ( Electron Microscopy Sciences ) in 1× PBS on ice for 60 min , followed by decalcification in 0 . 45 M EDTA , 1× PBS , for 18 h at 4°C . Tissue was frozen in O . C . T . compound ( Sakura-Fintek ) , and 16-µm sections were cut on a cryo-microtome ( Leica ) and collected on Superfrost Plus slides ( Fisher Scientific ) . Two-color RNA in situ hybridizations were performed using riboprobes labeled with either digoxigenin ( dig ) or fluorescein isothiocyanate ( FITC ) derivatized ribonucleotides ( Roche ) by either T7 or SP6 RNA polymerase ( Promega ) . Probes were hybridized [17] on the sections for 18 h at 68°C in hybridization buffer containing 50% formamide ( Sigma ) . Probes labeled with dig were detected by sheep anti-dig conjugated to horseradish peroxidase ( Roche ) , and visualized using Cy3 tyramide ( PerkinElmer ) following manufacturer's instructions . FITC-labeled probes were detected by sheep anti-FITC horseradish peroxidase following inactivation of the anti-dig horseradish peroxidase with 0 . 05% sodium azide in TNB buffer ( TSA Kit , PerkinElmer ) , and visualized with FITC tyramide ( PerkinElmer ) . Nuclei were counterstained with Toto-3 , 1∶1 , 000 ( Molecular Probes ) . Slides were visualized with Zeiss 510 and 710 laser-scanning confocal microscopes . Conditional expression of the tet-P2 alleles was accomplished by treatment with doxycycline , which ablates the binding of tTa to teto in the operator element . Mice were fed doxycycline-infused food ( Bio-Serv Dox diet , 200 mg/kg ) from E0 , through maternal feeding , to postnatal ages indicated , to accomplish staged activation or deactivation of the tet-P2 allele .
Odorant receptor ( OR ) gene choice is a paradigmatic example of transcriptional regulation in which each olfactory sensory neuron selects a single OR from a repertoire of over 1 , 000 genes . Two mechanistic models of OR choice have been proposed . One postulates the existence of a specialized transcriptional machinery that selects just one OR allele , while a second , kinetic model proposes that OR chromatin is intrinsically nonpermissive , such that inefficient activation during a critical window of time restricts expression to a single OR allele . Here , we used a transgenic approach in mice in which we inserted a conditionally regulated exogenous promoter into an OR locus by homologous recombination in embryonic stem cells . The resulting novel mouse lines allowed the functional interrogation of the OR locus in vivo during development of the olfactory epithelium , enabling us to directly test models of OR choice . Using this experimental strategy we found that OR loci are indeed slow to activate and that the subsequent phenomenon of spatial restriction of OR expression is accomplished by repression . We also observed a developmental shutdown of OR loci concomitant with expression of the OR repertoire . Together , these experiments provide prima facie evidence for a kinetic model of initiation of OR gene choice , coupled with repression of nonselected OR alleles .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "molecular", "cell", "biology", "neuroscience", "developmental", "biology", "biology" ]
2013
Functional Interrogation of an Odorant Receptor Locus Reveals Multiple Axes of Transcriptional Regulation
Crimean-Congo hemorrhagic fever ( CCHF ) is an often lethal , acute inflammatory illness that affects a large geographic area . The disease is caused by infection with CCHF virus ( CCHFV ) , a nairovirus from the Bunyaviridae family . Basic research on CCHFV has been severely hampered by biosafety requirements and lack of available strains and molecular tools . We report the development of a CCHF transcription- and entry-competent virus-like particle ( tecVLP ) system that can be used to study cell entry and viral transcription/replication over a broad dynamic range ( ~4 orders of magnitude ) . The tecVLPs are morphologically similar to authentic CCHFV . Incubation of immortalized and primary human cells with tecVLPs results in a strong reporter signal that is sensitive to treatment with neutralizing monoclonal antibodies and by small molecule inhibitors of CCHFV . We used glycoproteins and minigenomes from divergent CCHFV strains to generate tecVLPs , and in doing so , we identified a monoclonal antibody that can prevent cell entry of tecVLPs containing glycoproteins from 3 pathogenic CCHFV strains . In addition , our data suggest that different glycoprotein moieties confer different cellular entry efficiencies , and that glycoproteins from the commonly used strain IbAr10200 have up to 100-fold lower ability to enter primary human cells compared to glycoproteins from pathogenic CCHFV strains . Crimean-Congo hemorrhagic fever ( CCHF ) is a rapidly progressing inflammatory illness with high case fatality rates and a vast endemic area [1–6] . The etiological agent , CCHF virus ( CCHFV ) , is a tri-segmented virus belonging to the Nairovirus genus of the Bunyaviridae family; it is primarily maintained in and transmitted by Hyalomma species ticks [1 , 5 , 6] . Human infection is usually associated with tick bites or by unprotected contact with bodily fluids of infected animals or humans . Subclinical and mild cases of CCHFV infection usually consist of non-specific “flu-like” symptoms ( fever , vomiting , and diarrhea ) , and are self-resolving . Severe CCHFV infection progresses to CCHF , which is characterized by petechiae , ecchymosis , epistaxis , gingival hemorrhage , and , frequently , gastrointestinal and cerebral hemorrhage [1 , 7 , 8] . Case fatality rates of CCHF vary among outbreaks and potentially among strains of CCHFV , but are approximated to 30% of clinical cases [9 , 10] . The broad endemic region and high fatality rate of CCHF necessitate further research into the biology of CCHFV and development of effective prophylactic and therapeutic options to treat CCHFV infections for mitigating the negative public health impact of this pathogen . Basic research on CCHFV and the development of CCHF therapies and prophylaxes have been severely hampered by a number of factors . Safe handling of CCHFV requires high-containment facilities ( biosafety level 3 ( BSL-3 ) and BSL-4 facilities in endemic and non-endemic areas , respectively [9] ) . In addition , while CCHFV strains are highly variable in nature , laboratory strain availability is limited; the majority of basic research uses strain IbAr10200 , which has unknown pathogenicity in humans . Furthermore , due to technical difficulties in engineering recombinant CCHFV and pseudo-typing CCHFV glycoproteins onto other viruses , few and very limited reporter systems of CCHFV are available [11–14] . The major viral components of CCHFV particles consist of the viral genome and proteins . CCHFV , like all Bunyaviridae members , has a tri-segmented , negative sense RNA genome . The 3 segments , named small ( S ) , medium ( M ) , and large ( L ) , encode the viral nucleocapsid protein ( NP ) , the glycoprotein precursor ( GPC ) , and the viral polymerase ( L ) , respectively . Each of the CCHFV genomic segments consist of a coding region flanked by 5′ and 3′ non-coding regions ( NCRs ) . The NCRs are sufficient to initiate viral transcription , replication , encapsidation of RNA by NP and L , and packaging the RNA into viral particles [12 , 15] . An infectious CCHFV particle consists of at least all 3 viral RNA segments bound to NP and L ( ribonucleoprotein complexes , RNPs ) that are encapsulated by a lipid membrane containing the mature glycoproteins Gn and Gc , which are generated by post-translational processing of the GPC . Unlike many other negative-strand RNA viruses , bunyaviruses do not encode a separate matrix protein responsible for driving virus formation and incorporating RNPs into nascent viral particles . Rather , these processes are thought to be mediated by interaction between the RNPs and Gn and/or Gc [16–19] . Furthermore , as Gn and Gc mediate CCHFV entry into cells , these proteins are thought to be the major targets of host neutralizing antibody responses . Presumably due to this immunologic pressure , rapid mutation and frequent reassortment of the M segment have been reported in phylogenetic studies of CCHFV [20 , 21] . CCHFV reassortment occurs when the same cell is co-infected with at least 2 CCHFV strains . In order for reassortment to occur , the genomic NCRs and viral proteins must be compatible ( i . e . , the strains must possess both RNA-protein and protein-protein compatibility ) . How interaction of NCRs with RNPs and structural glycoproteins influences the reassortment observed in CCHFV is unknown [20] . To accelerate studies of CCHFV , we optimized a virus-like particle ( VLP ) system for use in a BSL-2 setting . The VLPs are transcription- and entry-competent VLPs ( tecVLP ) , do not produce infectious CCHFV , and are morphologically similar to CCHFV . We show that the tecVLP system is suitable for addressing the following points: ( 1 ) screening antivirals; ( 2 ) testing potency of monoclonal antibodies against divergent CCHFV strains; and ( 3 ) identifying potential molecular determinants of CCHFV reassortment , such as compatibility between NCRs and glycoproteins from various CCHFV strains . Unlike previous CCHFV reporter systems [12–15] , transfection or other pre-treatment of target cell lines is not required for tecVLP activity , so diverse cell lines and human primary cells may be used in tecVLP assays without special modification . This molecular tool may therefore be used in elucidating important aspects of CCHFV biology , in high-throughput screening , and in developing effective clinical countermeasures against CCHFV . Trained personnel performed all procedures involving potentially infectious agents ( work with infectious CCHFV and initial safety experiments with tecVLPs ) in a BSL-4 facility according to standard operating procedures approved by the institutional biosafety committee . Other procedures were carried out under BSL-2 conditions . The use of human blood products was approved by Emory University Institutional Review Board ( IRB reference IRB00045947 ) . Under this protocol , no donor personal information was provided , and informed consent was given . All adult blood donors provided informed consent , and a parent or guardian of any child participant provided informed consent on the child’s behalf . HuH7 cells ( obtained from Apath LLC , Brooklyn , NY , USA ) were propagated in Dulbecco’s modified Eagle’s medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) , 1% non-essential amino acids , and 1% penicillin/streptomycin ( all from Life Technologies , Grand Island , NY , USA ) . BSR-T7 cells ( a kind gift from K . K . Conzelmann , Ludwig-Maximilians-Universität , Munich , Germany ) , which constitutively express T7 polymerase , were propagated in DMEM supplemented with 5% FBS , 1% sodium pyruvate , 400 ng/mL G418 , and 1% penicillin/streptomycin . A549 cells ( ATCC , Manassas , VA , USA ) and SW-13 cells ( a kind gift from P . Leyssen , Rega Instituut KU , Leuven , Belgium ) were both propagated in DMEM supplemented with 10% FBS , 1% sodium pyruvate , and 1% penicillin/streptomycin . All cells were grown in a humidified 37°C , 5% CO2 incubator . Peripheral blood mononuclear cell ( PBMC ) pheresis products were obtained from a single healthy human donor at Emory University hospital ( Atlanta , GA , USA ) . PBMC were purified from whole blood pheresis products using Ficoll-Paque ( GE Healthcare , Atlanta , GA , USA ) according to manufacturer's instructions . Monocytes were isolated from the purified PBMC using the human Monocyte Isolation Kit II ( Miltenyi Biotec Inc . , San Diego , CA , USA ) according to manufacturer’s instructions , and frozen in liquid nitrogen until use . Monocytes were plated in 96-well cell culture plates at a density of 2 . 5 × 105 cells/cm2 in RPMI media supplemented with 10% FBS and 1% penicillin/streptomycin , and cultured for 10 days to allow differentiation into monocyte-derived macrophages . RPMI media was replaced every 2–3 days . GM05659 cells ( apparently healthy , non-fetal human fibroblasts from chest skin , obtained from Coriell Institute , Camden , NJ , USA ) were cultured in DMEM supplemented with 10% FBS , 1% sodium pyruvate , and 1% penicillin/streptomycin , and grown in a humidified 37°C , 5% CO2 incubator . Sequences of the M genomic segments of the novel CCHFV isolates were generated as previously described [21] . Reverse transcription PCR ( RT-PCR ) amplification products of the M segments were analyzed by Sanger sequencing and uploaded to GenBank . CCHFV helper plasmid genes were synthesized from GenBank sequences by GenScript USA Inc . ( Piscataway , NJ , USA ) . The CCHFV reference strain IbAr10200 L polymerase gene was codon-optimized and cloned into the mammalian expression plasmid pCAGGS-LCK to produce helper plasmid pC-L , as previously described [11] . GPC genes from CCHFV strains IbAr10200 ( reference CCHFV strain ) , Afg2990 ( human lethal case ) , and from CCHFV isolated from human patient samples collected in Oman and Turkey were codon-optimized , synthesized by GenScript , and cloned into the mammalian expression plasmid pCAGGS ( pC ) . These constructs were named pC-GPC-IbAr , pC-GPC-Afg , pC-GPC-Oman , and pC-GPC-Turk . Both pCAGGS and pCAGGS-LCK ( both abbreviated to pC ) have the same mammalian promoter for expression , but the pCAGGS-LCK is a low copy plasmid in bacteria to facilitate efficient bacterial production of the unstable pC-L construct . The previously described pC-NP plasmid was used to express NP from CCHFV strain IbAr10200 [11 , 12] . The previously described T7 polymerase plasmid pC-T7 was also used [11] . Minigenomes encoding the NanoLuc luciferase gene ( Promega , Madison , WI , USA ) sequence flanked by S , M , or L NCRs from CCHFV strain IbAr10200 , or with L NCRs from the CCHFV samples from Oman or Afg2990 , were gene-synthesized ( IDT , Coralville , IA , USA ) . The minigenomes were cloned into pSMART-LCK plasmid ( Lucigen , Middleton , WI , USA ) . The resulting plasmids ( pS-Luc , pM-Luc , pL-Luc , pOmanL-Luc , and pAfgL-Luc ) expressed viral-sense ( i . e . , negative or non-coding sense ) RNA fragments containing CCHFV recognition signals under the control of a T7 promoter , and containing one extra G at the 5′ end of the transcripts to enhance transcription by the T7 polymerase ( Fig 1A ) . BSR-T7 cells were seeded in multi-well plates overnight and transfected with combinations of minigenome and helper plasmids . Plasmids were transfected using TransIT-LT1 Transfection Reagent according to manufacturer’s recommendations ( Mirus Bio LLC , Madison , WI , USA ) . Helper plasmids were transfected in a weight ratio of pC-NP:pC-GPC:pC-L:pC-T7:minigenome of 4:10:2:4:1 unless otherwise noted , and if a helper plasmid was omitted , it was replaced with an equal weight of empty pC . The ratio of minigenome to helper plasmid was kept constant . The total amount of transfected DNA varied according to the size of the culture plate well: a 6-well plate was transfected with 5 μg of total DNA per well , while a 24-well plate was transfected with 1 μg of total DNA per well . To minimize carry-over of plasmids to the subsequent passage , transfection media was removed ~16–18 h post transfection and replaced with fresh media . Cell lysates , or supernatants for tecVLP passaging , were collected 3 days post transfection . NanoLuc signal was assayed in BSR-T7 cells transfected with CCHFV minigenome plasmids and in A549 , BSR-T7 , GM05659 , HuH7 , monocyte-derived macrophages , and SW-13 incubated with tecVLPs . Briefly , culture media was removed from the cells , and the cells were then washed once with PBS , and either frozen at -20°C or lysed by incubating for 30–45 min in passive lysis buffer ( Promega ) at room temperature . 20 μL of cell lysate was removed and assayed with Nano-Glo Luciferase Assay System ( Promega ) to detect NanoLuc signal . All luminescence readings were carried out in opaque , white 96-well plates using the Synergy 4 instrument ( BioTek Instruments Inc . , Winooski , VT , USA ) . BSR-T7 cells were transfected with plasmids for tecVLP rescue as described in “Plasmid transfections for VLP production” section , or with pC as a mock transfection control . In parallel , supernatants from tecVLP-producing or mock-transfected BSR-T7 cells , and CCHFV strain IbAr10200 viral stock ( SW-13 cell supernatants ) , were clarified by low speed centrifugation ( 1500 × g for 10 min ) . SW-13 cells were seeded at ≥ 90% confluence and allowed to adhere overnight . The media was removed from the SW-13 cells , and the cells were incubated with supernatants from mock- , tecVLP- , or CCHFV-treated cells for 2 h at 37°C . After incubation , the supernatants were removed and replaced with fresh media . Two days post incubation , cells were fixed with 10% formalin-buffered solution and permeabilized with Triton-X100 . Presence of CCHFV antigens was detected by incubation with CCHFV hyperimmune mouse ascetic fluid ( HMAF , made in-house at CDC , Atlanta , GA , USA ) or monoclonal antibody ( mAb ) 13G8 ( BEI Resources , Manassas , VA , USA ) followed by incubation with goat anti-mouse Alexa 488-conjugated antibody ( Life Technologies ) . Images were captured with a TCS SP5 confocal microscope ( Leica Microsystems , Buffalo Grove , IL , USA ) . BSR-T7 , HuH7 , SW-13 , A549 , and GM05659 cells were seeded at ≥ 70% confluence and allowed to adhere overnight . Plates of primary human macrophages were seeded at 2 . 5 × 105 cells/cm2 , and allowed to differentiate for 10 days . For all cells , media were removed and cells incubated with tecVLP-containing supernatants from transfected BSR-T7 cells for at least 2–3 h at 37°C . After incubation , the tecVLP-containing supernatants were removed , and the cells were washed 3 times with sterile PBS or RPMI media prior to adding fresh media . The cells were incubated overnight at 37°C to allow biosynthesis of NanoLuc in the cells . Following the incubation period , the cell medium was removed and the cells were washed once more with PBS; the cells were then incubated with passive lysis buffer for NanoLuc assays , or frozen at -20°C . tecVLP titration was performed on 10-fold serial dilutions ( prepared in DMEM ) of transfected cell supernatants , using a TCID50 assay on SW-13 cells in 96-well plates . Plates were incubated with the supernatants overnight at 37°C , and were then treated with passive lysis buffer for NanoLuc assays , or frozen at -20°C . Wells that displayed NanoLuc signal at least 3 standard deviations above background levels were considered positive for tecVLP signal . tecVLP concentrations were calculated using the Reed and Muench formula [22] , and expressed as TCID50 per mL of stock . CCHFV IbAr10200 PreGn- and Gc-specific mAbs ( 13G8 for PreGn; 11E7 and 12A9 for Gc ) , and CCHFV IbAr10200 NP-specific mAb ( 9D5 ) were obtained from BEI Resources . mAbs were diluted in DMEM supplemented with 5% FBS to equal starting concentrations , and further diluted in a 2-fold dilution series ( concentration range 1 × 101 to 8 × 10−2 μg/mL , or ~1:100 to 1:12800-fold dilution ) . The mAb dilutions were mixed with an equal volume of tecVLP-containing supernatant and incubated for 1–2 h at 37°C . The mixture was then applied to confluent monolayers of SW-13 cells , and incubated as outlined in tecVLP passaging . Ribavirin and chloroquine sulfate were obtained from U . S . Pharmacopeia ( Rockville , MD , USA ) . The inhibitors were dissolved in DMSO ( Sigma-Aldrich , St . Louis , MO , USA ) and diluted in OptiMem ( Life Technologies ) to starting concentrations , and further diluted in a 2-fold dilution series ( final concentration range of 400 μM to 3 μM for ribavirin , and 500 μM to 3 . 9 μM for chloroquine ) . The diluted drugs were added to monolayers of SW-13 cells , and cells were incubated for 15–20 min at 37°C . After incubation , equal volume of tecVLP-containing supernatants were added to the drug mixtures , and cells were incubated for 1–2 h at 37°C . The inocula were removed and the cells washed 3 times with sterile PBS prior to addition of fresh media with the same compound concentration; cells were then incubated overnight as described in tecVLP passaging . Cell viability was determined concurrently with tecVLP signal inhibition experiments , but on only compound-treated cells . Viability was determined using the CellTiter-Glo Luminescent Cell Viability Assay ( Promega ) according to manufacturer’s instructions . BSR-T7 cells in 6-well plates were transfected with plasmids necessary for the production of tecVLP as described in the “Plasmid transfections for tecVLP production” section above . After 3 days , tecVLP-containing cell supernatants were removed , clarified by centrifugation ( 5–10 min at 1500 × g ) , filtered through 0 . 22 μm pore size filters ( EMD-Millipore , Billerica , MA , USA ) , and concentrated in 100 kDa cutoff Centricon Plus-70 centrifugal filter units ( EMD-Millipore ) to 5–100-fold concentration . Concentrated tecVLP-containing supernatants were fixed by incubation with an equal volume of 5% paraformaldehyde and stored at 4°C until use . The concentrated , fixed tecVLP samples were processed as follows . First , 2 μL of each sample was pipetted onto a 300-mesh formvar/carbon-coated nickel grid ( EMS , Hatfield , PA , USA ) , and the sample was incubated overnight at 4°C . The samples were then blotted , rinsed with bacitracin ( 50 μg/mL ) [23] , blotted , negatively stained with 5% ammonium molybdate ( pH 6 . 9 ) and 0 . 1% ( w/v ) trehalose , and blotted a final time [24] . The grid was examined using a Tecnai BioTwin transmission electron microscope ( FEI Company , Hillsboro , OR , USA ) operating at 120 kV , and images were captured with a 2K × 2K camera ( AMT Corp . , Woburn , MA , USA ) . Concentrated tecVLP-containing supernatants or pC-GPC-transfected BSR-T7 cell lysates were incubated with NuPAGE LDS Sample Buffer for 10 min at 70°C prior to loading onto NuPAGE Novex 3–8% tris-acetate protein gels ( all from Life Technologies ) . The gels were run at a constant 200 V for 45 min , and transferred onto nitrocellulose membranes using the iBlot instrument ( Life Technologies ) according to manufacturer’s instructions . The membranes were incubated overnight at 4°C with anti-N mAb 9D5 ( BEI Resources; diluted 1:1000 ) , anti-Gn polyclonal rabbit sera [25] ( a kind gift from A . Mirazimi , Karolinska Institutet , Sweden; diluted 1:500 ) , or anti-Gc mAb 7E11 ( BEI Resources; diluted 1:1000 ) . Signals were detected with Fast Western Blot Kits mouse or rabbit SuperSignal West Dura ( Thermo Fisher Scientific Inc . , Waltham , MA , USA ) according to manufacturer’s recommendations . Full-length CCHFV M gene sequences were translated and aligned using the ClustalW algorithm , and phylogenetic trees were constructed using Mega ( Biodesign Institute , Tempe , AZ , USA ) [26] via the Jukes-Cantor neighbor-joining method with bootstrapping to 10000 iterations . Analyses were done using one-way or two-way analyses of variance ( ANOVA ) with Tukey’s multiple comparisons test . The analyses were performed using GraphPad Prism version 6 . 00 for Mac OS X ( GraphPad Software Inc . , La Jolla , CA , USA ) . For inhibitor dilutions , GraphPad Prism was used to fit a 4-parameter equation to semilog plots of the concentration-response data . The plot was used to interpolate the concentration of compound that inhibited 50% of the NanoLuc signal in target cells ( EC50 ) . The 50% cytotoxic concentration ( CC50 ) was derived using luciferase signal levels from inhibitor-treated cells . The selectivity index ( SI ) was calculated by dividing the CC50 by the EC50 . Helper plasmid genes were based on published and novel CCHFV , and T7 polymerase sequences . Replication machinery plasmids relied on published reference strain IbAr10200 gene sequences ( NP gene accession no . NC_005302; L gene accession no . AY389508 ) . GPC helper plasmid gene sequences were based on published sequences of CCHFV strains IbAr10200 ( accession no . NC_005300 ) and Afg2990 ( accession no . HM452306 . 1 ) , or on sequences of novel CCHFV isolates ( Oman-811466 , accession no . KR864901; Turkey-810473 , accession no . KR864902 ) . T7 polymerase helper plasmid was based on a published gene sequence ( accession no . M38308 ) . Minigenomes sequences were based on a published NanoLuc luciferase gene sequence ( accession no . JQ437370; ) flanked by CCHFV strain IbAr10200 S , M , or L NCRs ( S accession no . NC_005302; M accession no . NC_005300; L accession no . AY389508 ) , or by L NCRs from strains Oman ( accession no . DQ211619 ) or Afg2990 ( accession no . HM452307 ) . While the tecVLP system reported here is based on similar premises as previous systems [12 , 13] , it incorporates 2 modifications: the reporter is NanoLuc , a smaller protein that generates a brighter signal than many other luciferases; and the CCHFV L [11] and GPC helper plasmid sequences are codon-optimized . Because previous reports have indicated differences in the efficiency of transcription , replication and/or packaging of the 3 genomic CCHFV segments [12 , 13] we first tested which segment NCR was transcribed most efficiently in our system . In order to assess the reporter signal produced , we transfected cells with IbAr10200 helper plasmids and minigenomes containing S , M , and L genome segment NCRs ( Fig 1A ) . The resulting NanoLuc signal was similar regardless of segment used , suggesting no differences in transcription or replication of the 3 genomic segment NCRs ( Fig 1B ) . To determine whether using minigenomes of all 3 segments together would boost the overall signal , equal amounts of S-Luc , M-Luc , and L-Luc were transfected into BSR-T7 together . We then compared the resulting signal to that in cells transfected with triple the amount of individual minigenomes ( 3 × S-Luc , 3 × M-Luc , or 3 × L-Luc ) . The highest signal levels were seen when using 3 × L-Luc or S-Luc + M-Luc + L-Luc , ( Fig 1B ) . While there was a difference in signal levels in cells transfected with different minigenomes , the titers of tecVLPs ( ~2–6 ×104 TCID50/mL; Fig 1C ) were not apparently different . Likewise , when the tecVLPs resulting from minigenome transfections were passaged to SW-13 cells , the NanoLuc signal levels generated by tecVLPs were similar regardless of minigenome used ( Fig 1D ) . To be consistent in subsequent experiments , we used the L-Luc minigenomes at the original concentration . Due to safety concerns , we also verified that cells treated with tecVLPs do not release infectious virus . SW-13 cells were treated with infectious CCHFV , tecVLP ( in supernatants from transfected BSR-T7 cells ) , or supernatants of untransfected BSR-T7 cells ( negative control ) . Following 2 days of incubation , the SW-13 cells were stained by standard immunofluorescent assay . The cells inoculated with CCHFV had readily detectable viral antigens ( S1A Fig ) , while cells incubated with tecVLPs or control supernatants did not ( S1B and S1C Fig ) . In addition , SW-13 cells incubated with tecVLPs did not produce new tecVLPs , as supernatants of SW-13 cells treated with tecVLPs did not result in production of NanoLuc signal when passaged onto naïve cells ( S1D Fig ) . Therefore , we concluded that the tecVLPs are incapable of spreading . To compare tecVLP morphology and cell entry to those of authentic CCHFV , we used electron microscopy and a neutralization assay , respectively . Electron microscopy showed that tecVLPs were morphologically consistent with CCHFV and other bunyaviruses , and were relatively uniform in size ( 94 ± 3 nm , n = 13 , from 5 fields; average ± standard error of the mean , Fig 2A ) . Furthermore , tecVLPs were neutralized by previously reported neutralizing monoclonal antibodies [27] targeting IbAr10200 strain glycoprotein Gc ( 11E7 and 12A9 ) , but not by mAbs targeting strain IbAr10200 NP ( 9D5 ) or the glycoprotein PreGn ( 13G8 ) ( Fig 2B ) . These data suggest that CCHFV IbAr10200 tecVLPs are , from a structural perspective , consistent with bona fide CCHFV particles . Due to the sequence variability between the NCRs of different CCHFV strains , we expected differences in the efficiency with which viral sense RNAs are recognized and transcribed or packaged into particles by IbAr10200 proteins . To study the role of NCR sequences in tecVLP production , L NCR minigenomes from strains isolated from severe human cases of CCHFV ( Oman and Afg09 ) were expressed in the tecVLP system . tecVLPs were generated using minigenome plasmids containing Oman or Afg09 L NCRs flanking NanoLuc , and the same IbAr10200 helper plasmids ( NP + GPC + L ) as used previously ( Fig 1A ) . The results show that NCRs from all 3 strains were transcribed by strain IbAr10200 replication machinery ( NP and L ) at approximately the same efficiency in transfected cells , as signal levels ( Fig 3A ) and titers of tecVLPs produced in BSR-T7 cells ( Fig 3B ) were similar regardless of the NCR in the minigenome . The differences in signal produced by SW-13 cells incubated with tecVLPs with different NCRs were minor and not statistically significant ( p > 0 . 05 , Fig 3C ) . As M segments , and therefore GPCs , are commonly exchanged between CCHFV strains [20 , 21 , 28–30] , we assessed the compatibility between IbAr10200 replication machinery and mature glycoproteins from several pathogenic strains of CCHFV . To study the production of tecVLPs by the IbAr10200 replication machinery , GPCs from CCHFV strains Turkey , Oman , and Afg09 were expressed in the tecVLP system in place of IbAr10200 GPC . The full-length sequences of strain Turkey and Oman GPCs were elucidated prior to use in the tecVLP system . The GPC of the commonly used CCHFV strain IbAr10200 phylogenetically clusters with African CCHFV strains , while Turkey , Oman , and Afg09 GPCs cluster in different nodes of the phylogenetic tree ( S2 Fig ) . Based on amino acid sequences of the entire GPC , these strains were 14–20% different from IbAr10200 GPC ( 86% , 83% , and 80% amino acid identity between IbAr10200 and Afg09 , Oman , and Turkey GPCs , respectively ) . Using GPCs from these strains in transfected cells did not considerably affect NanoLuc signal levels in transfected BSR-T7 cells ( Fig 4A ) , but did affect the amounts of tecVLPs produced . Turkey and Oman strain GPCs led to the highest tecVLP titers , followed by IbAr10200 and Afg09 GPCs ( Fig 4B ) . Only the mature forms of Gn and Gc were detected by western blotting in the cell supernatants containing the tecVLP ( ~35 kDa for Gn and ~70kDa for Gc , Fig 4C ) . Levels of Gn were highest when using Turkey and Oman GPCs , lower when using IbAr10200 GPC , and lowest when using Afg09 GPC . Mature Gn is synthesized from a larger precursor that requires post-translational processing . We tested if the ratios of Gn precursor to mature Gn were equivalent in BSR-T7 cell transfected with GPCs of different CCHFV strains . Western blotting of the cell lysates showed a lower proportion of Afg09 mature Gn over Gn precursor in comparison to other GPCs ( Fig 4D ) . Due to a previous report that mature CCHFV glycoproteins interact with the NCR regions of the CCHFV genome [17] , we used the tecVLP system to address whether this interaction affects the efficiency of tecVLP release in a strain-specific manner . The results demonstrated that while altering the GPC resulted in a substantial difference in tecVLP titer and signal strength , changing minigenome NCRs had a minimal effect on tecVLP signal strength ( Fig 5 ) . In addition , using the minigenome NCR and GPC from the same strain together did not affect tecVLP production or NanoLuc signals synergistically; Afg09 GPC did not preferentially increase the signal or titer of Afg09 minigenome tecVLPs ( Fig 5A ) , nor did the Oman GPC preferentially increase the signal of Oman minigenome tecVLPs ( Fig 5B ) compared to the minigenome containing NCRs from other strains . In order to study the effects of GPC from different CCHFV strains on cell entry in the absence of confounding factors like differences in NP or L , we compared NanoLuc signal levels produced in immortalized and primary cells incubated with tecVLPs containing GPC from several CCHFV strains . tecVLPs containing IbAr10200 , Turkey , Oman , or Afg09 GPCs were capable of entering several immortalized cell lines ( Fig 6A ) . Predominantly , the strength of the resulting signal corresponded to tecVLP titers ( Fig 4B ) , with Turkey and Oman GPC tecVLPs yielding the highest titers and signal levels , IbAr1200 GPC producing intermediate levels , and Afg09 GPC tecVLPs yielding the lowest titers and signal levels ( compare Figs 4B with 6A ) . However , NanoLuc signal generated by IbAr10200 GPC-containing tecVLP in A549 cells was on par with Afg09 GPC-containing tecVLPs . Furthermore , when primary human cells were used instead of immortalized cell lines , tecVLPs containing IbAr10200 GPC generated less signal than tecVLPs containing Afg09 GPC; this was especially clear in monocyte-derived macrophages , which seemed refractory to entry by tecVLPs with IbAr10200 GPC ( Fig 6B ) . Efforts to screen CCHFV inhibitors have been hindered in part by the lack of high-throughput quantitative molecular systems that can be used in a BSL-2 setting . In order to overcome this limitation , we evaluated the potential of the tecVLP system to be used to screen compounds and antibodies in a high-throughput , 96-well format . We screened reported inhibitors of CCHFV cell entry ( mAbs and chloroquine ) and of viral transcription ( ribavirin ) using SW-13 cells treated with tecVLPs expressing glycoproteins from several CCHFV strains . The non-neutralizing mAb 13G8 ( targeting IbAr10200 PreGn; Fig 2B ) and the neutralizing mAb 12A9 ( targeting IbAr10200 Gc; Fig 2B ) did not neutralize tecVLPs containing Turkey , Oman , or Afg09 GPCs . However , the neutralizing mAb 11E7 ( targeting the IbAr10200 Gc ) effectively neutralized all tecVLPs ( Fig 7A ) . This demonstrates that the tecVLP system can be used to differentiate between strain-specific and broadly acting neutralizing mAbs and to rapidly assess mAb effectiveness . While mAbs are expected to bind different CCHFV glycoproteins with varying efficacy , small molecule CCHFV inhibitors should have similar inhibitory effects regardless of the GPC used . Indeed , using chloroquine or ribavirin on tecVLP-treated SW-13 cells decreased the signal produced by tecVLPs with equal efficiency regardless of the GPC constructs used to produce tecVLPs ( Fig 7B ) . The average EC50 was 23 . 23 ± 0 . 47 μM for chloroquine and 47 . 48 ± 1 . 43 μM for ribavirin , which is consistent with previously reported values [31–33] . The CC50 of chloroquine and ribavirin were 94 . 58 μM and 307 . 4 μM , respectively , with a corresponding average SI of 4 . 1 and 6 . 5 , respectively ( Fig 7B ) . These data suggest that the tecVLP system may be effective in screening inhibitors in a medium- or high-throughput set-up . CCHF is a geographically widespread , life-threatening illness characterized by severe flu-like and hemorrhagic symptoms and relatively high case fatality rates . Research on CCHFV , the causative agent of CCHF , has been hampered by a number of factors . Requirement for high-containment laboratories , limited strain availability , and lack of robust molecular tools for studying CCHFV all stalled basic CCHFV research . The development of VLP systems , especially those that can be simply scaled as needed , and that allow the study of CCHFV in a safe and effective manner , is a major step towards accelerating basic and applied research on this important public health risk . While our work builds on a previously reported minigenome system [12] and is not the first VLP system for CCHFV to be documented [13] , our system possesses several important advantages . ( 1 ) We demonstrated that the generated tecVLPs are morphologically consistent with CCHFV , and cell entry was neutralized by same monoclonal antibodies as authentic virus ( Fig 2 ) [27] . ( 2 ) A high yield of tecVLPs may be generated in 3 days without passaging in transfected cells ( Fig 1C ) . ( 3 ) Recipient cells may be used without resource-consuming pre-treatment steps , such as transfection of helper plasmids ( Fig 4 ) ; ( 4 ) therefore , the system reflects primary transcription/replication in a more natural setting than plasmid overexpression , and ( 5 ) a wider range of cell lines may be used ( Fig 5 ) . ( 6 ) GPCs and minigenomes from divergent CCHFV strains may be used ( Figs 3 , 4 and 6 ) , expanding the utility of this system . Importantly , the tecVLP system is safe for using outside of high-containment laboratories , since it does not generate infectious virus ( S1 Fig ) . Due to the lack of tecVLP replication , experiments assessing strain virulence cannot be conducted in vivo , but tecVLPs can likely be used to investigate the underlying differences between pathogenic and non-pathogenic or weakly pathogenic strains . Therefore , this system has the potential to greatly aid the study of CCHFV particle assembly , egress , entry , and primary transcription/replication in vitro and in vivo . In addition , due to ease of scaling , the tecVLP system may be suitable for high-throughput screens of antiviral agents . To assess the usefulness of our system , we examined several aspects of CCHFV biology , and tested the tecVLP system as a screening tool for CCHFV inhibitors . Based on previous minigenome data [12 , 13] , we hypothesized that CCHFV replication machinery preferentially transcribes , replicates , and packages the CCHFV L genomic segment over other segments . While L segment NCRs sometimes produced higher NanoLuc signals in transfected cells , as in previous reports [12 , 13] , the amounts of tecVLPs produced did not substantially differ between minigenomes ( Fig 1 ) . In order to be consistent between experiments , however , we used the L NCR-based minigenomes and tecVLPs in most of our experiments . Our first sets of experiments focused on observing the ability of IbAr10200 replication machinery to replicate minigenomes possessing NCRs of 2 pathogenic CCHFV strains . While the termini of the NCRs are highly conserved ( 1–2 differences in the terminal 30 nucleotides ) , significant differences are seen in the internal regions of the NCRs ( S3 Fig ) . Thus , we hypothesized that the NCR sequences that differed may affect transcription , replication , and/or packaging efficiency by the strain IbAr10200 replication machinery . However , we saw no substantial differences in reporter signal or tecVLP production ( Fig 3 ) . While the difference was small , we were surprised to find that the IbAr10200 replication machinery was not best adapted to transcribe its own minigenome compared to minigenomes from divergent strains . Therefore , we concluded that CCHFV IbAr10200 replication machinery efficiently incorporates L NCRs from several CCHFV strains into tecVLPs , probably because NCRs do not differ sufficiently at the sites critical for transcription , replication , and packaging . This finding may have significant implications for assessing reassortment potential between CCHFV strains , as it suggests that CCHFV strains have evolved to easily exchange segments during co-infections . Indeed , epidemiological studies have frequently reported genetic reassortment between CCHFV strains , especially in the GPC-encoding M segment [20 , 21 , 30 , 34] . Due to high reported reassortment frequency and experimental reports from other bunyaviruses [35–37] , we also examined the interaction between the IbAr10200 replication machinery and GPCs from other CCHFV strains by determining efficiency of tecVLP production using these constructs . We were surprised to see that GPC from Afg09 , the strain phylogenetically most closely related to IbAr10200 , resulted in lower tecVLPs titers than IbAr10200 , while the more distantly related Oman and Turkey GPCs resulted in higher tecVLP titers than IbAr10200 GPC ( Fig 4B and S2 Fig ) . While all GPCs were transcribed , translated , and secreted into the cell supernatant , the amounts of mature Gn and Gc generally correlated with tecVLP titers ( Turkey ≈ Oman > IbAr10200 > Afg09; Fig 4C ) . Cell lysates of transfected BSR-T7 cells showed that while relatively high levels of the Gn precursor are produced for all GPCs , the Afg09 strain Gn precursor appeared to be inefficiently processed ( Fig 4D ) . These findings suggest that post-translational cellular glycoprotein processing is likely responsible for the amount of tecVLP produced . In addition , we found that tecVLPs containing different GPCs behaved similarly in several immortalized cell lines , with Turkey and Oman GPC resulting in highest signal levels , followed by IbAr10200 , and Afg09 GPC resulting in the lowest signal levels ( Fig 6A ) . However , in A549 cells , primary human fibroblasts , and especially primary human monocyte-derived macrophages , IbAr10200 GPC-containing tecVLPs generated lower signal levels than tecVLP with other GPC strains ( Fig 6B ) . As these tecVLPs differed only in the surface glycoproteins , the ability to enter cells is likely to be the cause of different signal levels ( Fig 6 ) . This finding shows that in addition to efficiently incorporating into the viral particle , mature glycoproteins must facilitate entry into multiple cell types . Furthermore , these data suggest that the IbAr10200 GPC is “lab-adapted , ” probably due to multiple passages , and has poorer entry capacity than proven pathogenic CCHFV strains , which enter cells more efficiently . Thus , IbAr10200 may not accurately represent the mechanisms of entry used by highly pathogenic CCHFV strains . Additionally , since pathogenic CCHFV strains do not necessarily produce higher tecVLP titers than IbAr10200 but do facilitate efficient entry into immune cells , our data suggest that the ability to efficiently enter immune cells may be a better assessment of strain virulence than absolute tecVLP production . Finally , due to the proposed “matrix protein” function of the CCHFV glycoproteins [17] , we also tested for any synergy between GPCs and NCR minigenomes from the same CCHFV strain during tecVLP production . We found that , in our system , using the GPC and NCR from the same strain had no synergistic effect on tecVLP production ( Fig 5 ) . Overall our data were unexpected , as we found that while the IbAr10200 replication machinery certainly yields a higher NanoLuc signal when used with certain glycoproteins or minigenomes , it does not always prefer its own glycoprotein or minigenome . In order to show that our system can be used to screen inhibitors of cell entry and transcription/replication , we used known inhibitors of CCHFV receptor-mediated entry ( neutralizing mAbs ) , endosome-mediated entry ( chloroquine ) , and transcription ( ribavirin ) on tecVLPs with different glycoproteins . To demonstrate that tecVLPs could be used to identify even relatively minor differences in mAb affinity , we tested several previously reported mAbs , both neutralizing and non-neutralizing , in our assay . The results show that mAbs 11E7 and 12A9 , which target Gc and which were previously reported to neutralize IbAr10200 , readily neutralize tecVLPs expressing IbAr10200 GPC , while non-neutralizing anti-PreGn and anti-NP mAbs ( 13G8 and 9D5 , respectively ) do not neutralize IbAr10200 GPC-containing tecVLPs [27] ( Fig 2B ) . In contrast , tecVLPs containing GPC from other strains are not neutralized by 12A9 , but are neutralized by 11E7 , identifying 11E7 as a broadly neutralizing anti-CCHFV mAb ( Fig 7A ) . These results both illustrate the power of the tecVLP system to quickly screen mAbs , and show that this system can detect mAbs targeting mature glycoproteins of different stains . Unlike antibodies , inhibitors targeting common components of tecVLPs or cell entry pathways should behave similarly in all tecVLPs regardless of GPC origin . Indeed , chloroquine ( which inhibits viral cell entry ) and ribavirin ( which inhibits RNA transcription ) inhibited all tecVLPs , and both inhibitors had a nearly identical EC50 regardless of the GPC used to generate each tecVLP ( Fig 7B ) . Furthermore , the EC50 values calculated for the tecVLPs were similar to those reported in previous studies using live CCHFV [31 , 32] . These data suggest that tecVLPs might be useful as a replacement of live CCHFV in inhibitor screens , allowing high-throughput studies at BSL-2 conditions . In conclusion , our tecVLP system is a safe , robust , and effective way to study the molecular life cycle of CCHFV . The key features of this system are that it can be used in a regular laboratory with multiple cell types , and can be easily modified to fit the needs of the researcher . We used the system to explore glycoprotein and genome incorporation into tecVLPs , and our findings suggest that compatibility between the glycoprotein and the replication machinery impacts the reassortment potential between CCHFV strains . Furthermore , our study also suggests that tecVLPs may be able to replace live CCHFV in screening both immunological and small molecule inhibitors and evaluating these inhibitors in vitro , both in high- and low-throughput settings .
The tick-borne Crimean-Congo hemorrhagic fever virus ( CCHFV ) is the causative agent of a frequently life-threatening disease . CCHFV is present in a wide geographic area with potential for expansion . Moreover , CCHFV segmented genome reassortment leads to new strains with potentially different virulence . Studying CCHFV is highly necessary , but requires dedicated , resource-intensive , high biosafety and security laboratories . In part due to the need for high containment , CCHFV studies have been limited , and developing tools to study CCHFV has been difficult . We report the development of a system that mimics the CCHFV life cycle and produces virus-like particles ( VLPs ) that are similar to CCHFV in cell culture , but do not form infectious CCHFV and therefore do not require the use of special laboratories . We generated VLPs representing several pathogenic CCHFV strains with robust reporter signal activity . This allows VLPs to be used in testing cell entry inhibitors against a wide array of CCHFV strains . In addition , VLPs can be used in a variety of cell lines and in cells directly isolated from humans . Our results also suggest that the CCHFV strain IbAr10200 , which is commonly used in the laboratory , may not accurately reflect the activity of circulating pathogenic CCHFV strains , as the surface glycoproteins of IbAr10200 confer reduced entry efficiency of VLP into cells derived directly from humans . In addition , we show that drugs with proven anti-CCHFV properties inhibit VLP activity , and identify a monoclonal antibody that prevents cell entry of VLP made using glycoprotein genes from different , pathogenic CCHFV strains .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[]
2015
Assessment of Inhibitors of Pathogenic Crimean-Congo Hemorrhagic Fever Virus Strains Using Virus-Like Particles
Plant–animal mutualisms are characterized by weak or asymmetric mutual dependences between interacting species , a feature that could increase community stability . If invasive species integrate into mutualistic webs , they may alter web structure , with consequences for species persistence . However , the effect of alien mutualists on the architecture of plant–pollinator webs remains largely unexplored . We analyzed the extent of mutual dependency between interacting species , as a measure of mutualism strength , and the connectivity of 10 paired plant–pollinator webs , eight from forests of the southern Andes and two from oceanic islands , with different incidences of alien species . Highly invaded webs exhibited weaker mutualism than less-invaded webs . This potential increase in network stability was the result of a disproportionate increase in the importance and participation of alien species in the most asymmetric interactions . The integration of alien mutualists did not alter overall network connectivity , but links were transferred from generalist native species to super-generalist alien species during invasion . Therefore , connectivity among native species declined in highly invaded webs . These modifications in the structure of pollination webs , due to dominance of alien mutualists , can leave many native species subject to novel ecological and evolutionary dynamics . Plant–animal mutualisms are highly asymmetric , such that if a plant species depends strongly on an animal species , the animal typically depends weakly on the plant , and vice versa [1 , 2] . Thus , the resulting mutualistic webs have a nested structure—a robust property of this type of networks [3] —whereby specialists interact preferentially with generalists , rather than with other specialists , and interactions between generalist partners form the network core [2 , 4] . This limited reciprocal dependence or mutualism strength might increase web stability , buffering plant and animal species against the extinction of any of their partners [1 , 5–8] . Additionally , a decrease in mutualism strength may indicate changes in network architecture whereby some components of an interaction network become more weakly connected , or disconnected , whereas others become more central . Here we show that integration of invasive mutualists into native plant–pollinator networks , while it does not alter overall web connectivity , decreases mutualism strength by increasing the concentration of interaction links in a few alien species . Given the arrival of propagules of alien organisms in a new locality , invasion is usually triggered by different types of mostly human-related disturbances and/or promoted by an enemy-free space that creates appropriate conditions for establishment [9 , 10] . Once established , aliens can increase in abundance and even dominate an entire community through a series of direct and indirect facilitative and self-perpetuating mechanisms [9–11] , which can cause displacement of native competitors and disruption of their interactions [12–15] . In particular , the fate of alien flowering plants and flower-visiting animals in a novel environment may depend largely on how well they integrate into existing pollination webs [16] . If they integrate poorly—due , for instance , to a lack of coevolutionary history with their native counterparts—then their success , in terms of seed production for plants and nectar and pollen acquisition for pollinators , may be conditioned by the presence of other alien partners . However , absolute failure of aliens to integrate into native pollination webs seems unlikely , because many plant–pollinator interactions are rather unspecific and diversified , and alien mutualists have a high chance of interacting with native generalists [17 , 18] . In any event , preferential interaction between alien partners might create a separate network compartment with little effect on the structure of the original native web . On the other hand , because many invasive plants and pollinators are themselves highly generalist , their interactions with other alien and native species could become central in the structure of modified plant–pollinator webs . Alien integration need not to alter the architecture of former pollination networks in terms of its connectivity , or who interacts with whom . For instance , alien plants may compete with native plants for space and resources ( light and water ) but not necessarily for pollinators , whereas alien and native flower-visiting animals may present different activity periods or exploit different floral resources [19–21] . However , as invasion progresses , some alien mutualists may become increasingly abundant and/or change their per capita interaction strength , elevating their chance of interacting with a large number of partners [10 , 22 , 23] and , as long as network connectivity remains constant , of “sequestering” interaction frequency and links from the original web . The transfer of interactions from native to alien generalists might create a positive feedback that fosters invasiveness and subjects native species to novel ecological and evolutionary dynamics [11] . We explored the effects of invasive species on the structure of pollination networks by compiling information provided by 10 paired , quantitative , plant–pollinator webs , eight from the temperate forests of the southern Andes and two from oceanic islands , which differ in the functional incidence of alien species . First , we evaluated the degree of mutual dependence between interacting partners ( i . e . , mutualism strength ) , characterizing networks with different levels of invasion . Second , we assessed whether a decrease in mutualism strength found in the most invaded networks was accompanied by a shift in the identity , from native to alien , of the generalist partners participating in the most asymmetric interactions and also by differences in the ecological role played by native and alien mutualists . Finally , we investigated whether an increase in alien dominance could result in a loss of interactions and decrease in connectivity between native partners . We report that although alien species could behave as mostly unnoticed commensals during initial stages of invasion , during later stages they monopolize interactions , including those that previously formed the core of native pollination webs . The 10 pollination webs included in this study varied in the total number of interacting species ( i . e . , their sizes ) and number of alien species recorded ( Table 1 ) . The sizes of the study webs ( 21–69 species ) and number of interactions ( 23–145 links ) were smaller than those of many tropical pollination webs [24] or webs assembled from observations collected over large areas or over long time periods [18] , but typical of local webs from other temperate regions and isolated islands [24–26] . In addition , these are the few webs studied , so far , that include both alien mutualists and some estimate of interaction frequency , a measure that relates strongly to plant reproductive success and is presumably associated with the amount of floral resources gathered by a given pollinator species [27] . The functional importance of invading plants and animals in each pollination web was estimated from the proportions of the sum of all visitation frequencies recorded at the flowers of alien plants and for alien flower visitors , respectively ( Table 1 ) . These estimates are determined by both the number of alien species present in each web and the total interaction frequency of each individual alien species . We should acknowledge , however , that the per visit efficiency in pollen delivery or in resource uptake could differ between native and alien species and might accentuate any expected effect of invasive species on either plant or animal fitness based on changes in interaction frequency alone [15] . For all five pairs of webs , the four pairs from the southern Andes and the pair from oceanic islands , the web with the highest incidence of visits to alien plants also had the highest incidence of visits from alien pollinators ( Table 1 ) . We considered the average between these two proportions as an index of the degree of invasion of a pollination web , which ranges from 0 for a web with no interacting alien species to 1 for a web characterized exclusively by interactions between alien species . Despite extensive variation , the four southern Andean webs from mostly undisturbed habitats and the web from Flores island represent the five lowest values of this index ( <0 . 32 ) . These five webs were grouped into the “lightly-invaded” category , whereas their paired counterparts , including the web from Aigrettes , were grouped into the “highly-invaded” category ( invasion index > 0 . 32 ) . We calculated the mutual dependency for all pairs of interacting species in each web based on estimates of interaction frequency , and we consider the mean of all pairwise nonzero products of mutual dependencies as a measure of mutualism strength [1 , 28] . Each estimate of mutualism strength was compared with a distribution of expected values generated by a randomization procedure , and observed values were standardized by their respective expected means to lessen the influence of web size and total number of links ( Table 2 ) . The studied pollination webs exhibited generally smaller mean products of mutual dependences between interacting species than expected by chance alone . All but two webs , both from the lightly-invaded group , had standardized mutualism strengths below the limit set by the 2 . 5 percentile of their respective randomly generated distributions ( Figure 1A ) . The highly-invaded web of each of the five network pairs had consistently lower standardized mutualism strength than its lightly invaded counterpart ( binomial test , p = 0 . 03125 ) . More generally , mutualism strength—either standardized or not—varied inversely with the extent of invasion ( Table 2 and Figure 1A ) . This declining trend can be attributed directly to the effects of interacting alien species , as the mutualism strength of the sub-web formed by the native species showed a weak positive association with invasion index ( Figure 1B ) . As a consequence , the ( standardized ) mutualism strength of the native sub-web was relatively similar to the mutualism strength exhibited by the whole network for the lightly invaded webs ( mean ± standard error [SE] = −0 . 31 ± 0 . 043 versus −0 . 25 ± 0 . 047; paired t-test , t = −1 . 40 , degrees of freedom [df] = 4 , p = 0 . 23 ) , whereas it was much larger for the highly invaded group ( mean ± SE = −0 . 17 ± 0 . 042 versus −0 . 43 ± 0 . 047; t = −5 . 05 , df = 4 , p <0 . 01 ) . Hence , the presence of invasive alien mutualists in highly invaded pollination webs apparently decreased absolute and relative mutualism strength . To identify the causes of changes in mutualism strength with increasing invasion , we compared the mean and distribution of the asymmetry between interacting pairs of plant–pollinator native species versus interacting pairs that included at least one alien partner for lightly and highly invaded webs . We used Bascompte et al . 's index of asymmetry , which ranges between 0 and 1 [1] . Differential asymmetries characterized the interactions involving aliens according to the extent of invasion . Whereas we did not find a significant difference between the mean asymmetry of native–native interactions and interactions involving at least one alien species for the lightly invaded webs ( paired t-test , t = 1 . 48 , df = 4 , p = 0 . 21 ) , we did find a consistent trend for the highly-invaded webs ( t = −6 . 31 , df = 4 , p <0 . 005 ) . For these latter webs , interactions involving alien species were more asymmetric than interactions between native mutualists ( Figure 2 ) . The comparative distribution of pairwise interaction asymmetries also illustrates the differential influence of alien species in the structure of pollination webs . Figure 2 shows an overrepresentation of large asymmetries , implying that a strongly dependent mutualist ( i . e . , a specialist ) commonly interacts with a weakly dependent partner ( i . e . , a generalist ) . However , the distribution of asymmetries of interactions between native mutualists and interactions involving at least one alien partner showed a differential pattern according to invasion level . Whereas the distribution of asymmetries between these two types of interactions was similar for the lightly invaded webs ( Kolmogorov-Smirnov test , D = 0 . 113 , p = 0 . 42 ) , it greatly differed for the highly-invaded group ( D = 0 . 184 , p < 0 . 005 ) . Specifically , in this latter group , the incidence of high asymmetry ( >0 . 8 ) associated with interacting aliens was larger than those characterizing interactions between native species ( 60 . 6% versus 42 . 7%; χ2 = 13 . 53 , df = 1 , p < 0 . 0005 ) , a trend that was not observed among the lightly-invaded webs ( 44 . 3% versus 47 . 0%; χ2 = 0 . 17 , df = 1 , p = 0 . 67 ) . Therefore , aliens engage disproportionately in the most asymmetric interactions during advanced stages of invasion . The differential participation of aliens in highly asymmetric interactions relates to the high individual strength that generalist alien species achieved in the most-invaded webs . We characterized each species present in each web by the number of species with which it interacts ( degree ) and the sum of the dependences of the species with which it interacts ( strength ) . Thus , a species' strength is a quantitative extension of its degree , and it represents the ecological importance of a given mutualistic plant or animal species from the perspective of the interacting animal or plant assemblage , respectively [1] . We examined whether the slope of the linear relation between species degree and strength differed between native versus alien species in lightly and highly invaded webs . Alien species will exhibit a higher slope than native species if they become disproportionately important , in terms of their strength , particularly in highly invaded webs . The analysis of the relation between species strength and degree for native versus alien plant and flower visitors reveals the differential ecological importance achieved by alien mutualists along invasion ( Figure 3 ) . In the lightly invaded webs , native and alien plant and animal mutualists had almost identical slopes ( test of homogeneity of slopes , F = 0 . 001 , df = 1 , 47 , p = 0 . 94 , and F = 0 . 13 , df = 1 , 124 , p = 0 . 72 for plant and animal species , respectively ) . However , in the highly invaded webs , where alien species engaged in the most generalized interactions ( species degree > 8 ) , aliens exhibited a higher slope than natives ( F = 3 . 45 , df = 1 , 67 , p = 0 . 06 , and F = 42 . 44 , df = 1 , 177 , p < 0 . 0001 for plant and animal species , respectively ) . Thus , in highly invaded webs , many species interact with generalist aliens , and more species become highly dependent on them . Changes in quantitative parameters characterizing the structure of invaded pollination webs were not associated with changes in network connectivity , but they were associated with an altered distribution of interaction links . Overall , the connectance ( i . e . , the percent of all possible interactions actually observed ) of the analyzed webs decreased with the number of species in each web ( Figure 4 ) , a relation that could be depicted by a similar negative-exponential fit as the one estimated by Jordano from a sample of several qualitative plant–pollinator webs [24] . However , the remaining variation did not depend on the extent of web invasion ( i . e . , the invasion index; r2 = 0 . 076 , F = 0 . 66 , df = 1 , 8 , p = 0 . 44 ) and paired comparisons of residuals between lightly and highly invaded webs were not significantly different ( −1 . 13 ± 1 . 69 versus 1 . 23 ± 0 . 87 %; t = −1 . 05 , df = 4 , p = 0 . 35 ) . In general , both groups of webs exhibited similar connectivity ( 22 . 1 ± 2 . 62 versus 20 . 1 ± 3 . 23 % , respectively; t = 0 . 99 , df = 4 , p = 0 . 38 ) . However , native mutualists were more connected among themselves in the lightly invaded than in the highly invaded webs ( 25 . 2 ± 3 . 49 versus 16 . 8 ± 3 . 54%; t = 6 . 91 , df = 4 , p = 0 . 002 ) , a difference that persisted ( p = 0 . 04 ) after including the total number of native species as a covariate . The connectance of the native sub-webs exceeded or equaled the overall connectance exhibited by their respective webs in the lightly invaded networks , whereas it was significantly lower in three of the five highly invaded webs ( Figure 5 ) . For the other two highly invaded networks , where connectance among native species was similar to that exhibited by their respective webs , their lightly invaded counterparts were characterized by particularly richly connected native sub-webs . Thus , these results reveal general invariance in overall network connectivity , irrespective of invasion degree and beyond any influence of network size , so that if native species become less connected among themselves they become more connected with alien species . Previous studies showed that alien mutualists can integrate into pollination webs , but with a slight effect , if any , on the connectivity of the original network [18 , 29] . Our results reveal , however , that the effect of aliens on the distribution of interaction links could greatly depend on the extent of invasion which , in turn , may be mediated by external factors , such as disturbance , and influenced by particular historical settings [9] . Our work also demonstrates that aliens can modify basic quantitative parameters of pollination webs , such as the strength of interactions and distribution of asymmetries , that constitute the basic foundations of the architecture of mutualistic networks [1 , 2 , 4–6] . Several recent studies propose that species persistence should increase in a mutualistic network governed by limited interdependency , as the disruption of any link will have little effect on community stability [1 , 5–7 , 30] . However , this low mutualism strength may characterize either a diffuse network dominated by weak mutual dependence between interacting pairs of species or a highly structured network dominated by asymmetric links with interacting partners depending unevenly on each other . Asymmetry seems common in plant–animal mutualistic networks [1] and was evident from the networks that we studied ( Figure 2 ) . This pattern reflects a type of mutualistic web in which specialists interact differentially with generalists , whereas weak mutual interactions between generalist partners characterize the left tail of the distribution . Our results also demonstrate that diminished mutualism strength results from the involvement of generalist alien species in an unusual proportion of the most asymmetric interactions in highly invaded webs . The strength achieved by some of these generalist aliens surpasses that of any native species , indicating that many species that are ecologically specialized because of being rare [23] interact exclusively with at least some of the invaders ( see also [1 , 2] ) . Therefore , these super-generalist aliens become central nodes of highly invaded webs that might increase nestedness and the persistence of many species [4] , but greatly modify network architecture during invasion . Our results also suggest the likely dynamics of change in a pollination network during invasion . Upon arrival , alien newcomers are rare and probably persist in existing pollination networks through interactions with native generalists [17 , 18] , so they engage in few interactions and exhibit limited integration due to their scarcity . If disturbance and/or the lack of regulatory processes , such as predation and parasitism , subsequently allow an increase in abundance of an alien species , its ecological generalization may also increase , because abundance is an important determinant of a species' degree [22 , 23 , 31] . Additionally , habitat modification can change the mode of action ( i . e . , per capita effect ) of at least some alien species and thus their total impact may increase beyond expectations based on invader abundance alone [10] . Therefore , the growth of a population of an invasive species likely precipitates a disproportionate increase in its importance in the structure of the network through both numerical and functional effects . In the case of invasive plants , for instance , this augmented strength may result not only from high density , but also from the tendency of these species to produce exuberant flower displays and offer superabundant flower resources [12] . In the case of invasive flower visitors , this high species' strength may also relate to highly plastic behavior , efficient resource search and exploitation , and indiscriminate foraging as exhibited by the honey bee , Apis mellifera [32] , and some highly invasive bumble bees such as Bombus terrestris [33] or B . ruderatus [34] . The conceptual model we portray may also accommodate contrasting evidence for the existence of the so-called “invader complexes” , groups of introduced species interacting more with each other than expected by chance [16 , 18 , 29 , 35] . Because interactions among super-generalist aliens form the main core of highly-invaded webs , facilitation between alien partners may become apparent only during late stages of invasion . Whereas alien mutualists can integrate into native pollination networks , they seem not to increase the connectivity of the invaded web . Our results demonstrate that connectance decreased with total number of species in the same fashion as found in a previous and broader study [24] , regardless of whether the networks are highly invaded ( Figure 4 ) . Indeed , the negative-exponential coefficient of the relation in Figure 4 , 0 . 16 , is practically the same as the 0 . 17 reported by Jordano [24] . This similarity can relate to different constraints that may determine limits in the connectivity of this type of network [30 , 36–38] . Therefore , the increasing role of aliens as prime nodes in network structure entails the erosion in connectivity among members of the pre-invaded web , as the decrease in connectivity among native species in some of the most invaded webs illustrates clearly ( Figure 5 ) . From the alien species' perspective , usurpation of links and of interaction frequency in mutualistic networks can establish a self-perpetuating positive feedback , whereby invasive species increasingly enhance their reproductive success and dominance . From the native species' perspective , whereas many of the “lost” interactions may be rather redundant , others might be key in their ecological and evolutionary dynamics . For instance , the clonal herb Alstroemeria aurea ( Alstroemeriaceae ) is a keystone mutualist in south Andean forests . Despite being highly generalist , its reproduction relies principally on the giant bumble bee B . dahlbomii , another key mutualist [39] . Recently , the introduced European bumble bee B . ruderatus invaded austral South America and displaced native B . dahlbomii even from some undisturbed areas [34 , 40] . Although the reproductive consequence of this pollinator replacement for Al . aurea is unknown , B . ruderatus is a less-efficient pollinator of this plant species because of its smaller size , and therefore pollination quantity and/or quality may decline [41] . In the long term , this novel interaction may select for smaller flowers of Al . aurea . For other native plant species , like the south Andean endemic Chilean fire-bush , Embothrium coccineum ( Proteaceae ) , usurpation of links could significantly decrease reproductive output because of replacement of a diverse pollinator assemblage by Ap . mellifera in highly-modified settings [40] . In such cases , invasive species can contribute to their eventual demise through the disruption of the pollination mutualism ( see also [15] ) . Invaded mutualistic webs may actually sustain high diversity and even some rare pollinators may increase in abundance due to plentiful resources offered by some mass-flowering alien plants [42–44] . Yet , the focus on diversity of species and links or other metrics describing the structure of quantitative webs can overlook subtle , but transcendent changes in network architecture [45] . Although many native mutualists can survive alien dominance , our results indicate that particular configurations of biological communities , and thus unique ecological interactions and evolutionary pathways , can be lost forever . We assembled a dataset ( Dataset S1 ) composed of ten quantitative plant–pollinator webs , including alien species , from our unpublished records and Olesen et al . [29] . The field sampling procedures that we used to characterize the eight south Andean plant–pollinator webs are presented in detail elsewhere [16 , 35] . Briefly , per-flower visit frequencies ( number of visits × flower−1 × 15 min−1 ) by different visitor species were estimated at the flowers of the most common animal-pollinated native and alien plant species at each of four forested sites in Nahuel Huapi National Park , Argentina , during the 2000–2001 flowering season . Sites were located along a 50-km transect , oriented East-West along a gradient of increasing precipitation . At each site , corresponding to a different native forest type , we surveyed flower-visiting animals in two habitats units <1 km apart characterized by contrasting disturbance intensity , a mostly undisturbed or less disturbed area ( U ) and a highly-disturbed area ( D ) , which had been either burned or logged and was characterized by a higher number and abundance of alien species . In total , we accumulated 1 , 639 diurnal observation periods of 15 min each during 73 d . Sampling was distributed evenly among the four study sites , between disturbed and undisturbed habitats within sites and throughout the flowering season . Individuals observed visiting flowers were morphotyped and identified to the minimum possible taxonomic level with the aid of a reference collection and the expertise of different specialists . Individuals that could be identified to the species level accounted for about 85% of all flower visits recorded . Previous analyses conducted on this data set showed that plant species origin , alien versus native , influences visitation frequency and the composition of the flower-visiting species assemblage independent of habitat disturbance [16 , 35] . The data obtained from Olesen et al . 's study [29] of two other pollination webs from oceanic islands , Flores , in the Azores , and Ile aux Aigrettes , a small islet 600 m off the coast of Mauritius ( hereafter Aigrettes ) , also included alien plants and pollinators . This study also involved a large sampling effort , including observations of the numbers of flower visitors seen during 226 and 341 observation periods of 30 min each on Flores and Aigrettes , respectively . However , Olesen et al . [29] did not contrast disturbed and undisturbed habitats on these islands . All flower visitors included in the ten sampled networks were presumed to act as pollinators , as they contacted sexual parts of the flowers they visited . The plant species included in the networks encompass a mix of herbaceous and woody forms , whereas flower visitors were all insects , except for a hummingbird , Sephanoides sephaniodes , native to austral South America and present in some of the south Andean webs , and a gecko , Phelsuma ornata ornata , endemic to Mauritius . Eight out of the ten webs included the introduced honey bee , Ap . mellifera , whereas the bumble bee , B . ruderatus , was an alien flower visitor in six of eight south Andean webs [16] but native on Flores [29] . Although the south Andean webs share some native and alien species , each web includes unique species and species combinations ( Dataset S1 ) . Each of the ten plant–pollinator webs was depicted in a matrix , in which the rows represent different plant species ( P ) and columns depict animal pollinators ( A ) , and cells record the occurrence and intensity of interactions between plant and pollinator species . As measures of interaction frequency , we used the mean visit frequency per observation period for the south Andean matrices , and the total numbers of visits from different pollinator species during the total sampling period on each plant species for the island webs ( see [2 , 23] ) . We calculated the connectance of each matrix ( i . e . , a measure of connectivity; [24] ) as the percentage of the P × A cells with an interaction frequency >0 . Based on estimates of interaction frequency , we calculated the mutual dependency for all pairs of interacting species in each web . The frequency of an interaction relative to its row total ( i . e . , the fraction of all animal visits to a plant species by a particular animal species ) represents the dependence of plant species i on pollinator species j , whereas the frequency of a given interaction relative to its column total ( i . e . , the fraction of all visits by an animal species to a particular plant species ) represents the dependence of pollinator species j on plant species i . We defined the strength of the mutualistic interaction between plant species i and pollinator species j as the product of their respective dependences [1] and the mutualism strength for an entire web as the mean of all pairwise nonzero mutualistic strengths . A web dominated by either mutually weak or highly asymmetric interactions will exhibit low mutualism strength [1 , 28] . The observed mutualism strength was compared with a distribution of expected values generated from 10 , 000 randomized datasets , where we shuffled the observed interaction frequencies within each matrix with the restriction that each species had at least one interaction [2 , 23] ( Protocol S1 ) . Because of the sensitivity of mutualism strength to the number of species and links , we standardized the observed mutualism strength ( O ) for each web as ( O – E ) / E , where E is the expected mean mutualism strength of its corresponding simulated distribution . This relative measure of mutualism strength was not influenced significantly by network size ( Table 2 ) . For each web , we estimated both the mutualism strength of the whole network and that of the native sub-web ( i . e . , after excluding interactions with and between alien species ) . To identify the causes of changes in mutualism strength with increasing invasion , we compared the mean and distribution of the asymmetry between interacting pairs of native plant–pollinator species versus interacting pairs that included at least one alien species . Asymmetry between species i and j was characterized by AS ( i , j ) = max , which ranges between 0 and 1 [1] .
Plant–animal mutualisms are characterized by weak or asymmetric mutual dependences between interacting species , such that if a plant species depends strongly on an animal species , the animal typically depends weakly on the plant , and vice versa . This limited reciprocal dependency , or “mutualism strength , ” might increase species persistence by buffering plant and animal species against the extinction of any of their partners . Many plant–pollinator networks include a fraction of alien species , and it is not clear how these invaders might affect the structure of pollination webs . We analyzed 10 paired plant–pollinator webs , eight from forests of the southern Andes and two from oceanic islands , with different incidences of alien species . Highly invaded webs exhibited , on average , weaker mutualistic interactions , and hence a potential increase in network stability , than less-invaded webs . This was due to a disproportionate increase in the participation of some alien species in the most asymmetric interactions and their role as central nodes in the structure of the most invaded pollination webs . The increase in alien dominance involves the usurpation of interaction links , decreasing connectivity among native mutualists . Thus , many native species that rely on native generalists for either reproduction or survivorship become highly dependent on these super-generalist alien mutualists .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "ecology", "plant", "biology" ]
2008
Invasive Mutualists Erode Native Pollination Webs
The X chromosome is present as a single copy in the heterogametic sex , and this hemizygosity is expected to drive unusual patterns of evolution on the X relative to the autosomes . For example , the hemizgosity of the X may lead to a lower chromosomal effective population size compared to the autosomes , suggesting that the X might be more strongly affected by genetic drift . However , the X may also experience stronger positive selection than the autosomes , because recessive beneficial mutations will be more visible to selection on the X where they will spend less time being masked by the dominant , less beneficial allele—a proposal known as the faster-X hypothesis . Thus , empirical studies demonstrating increased genetic divergence on the X chromosome could be indicative of either adaptive or non-adaptive evolution . We measured gene expression in Drosophila species and in D . melanogaster inbred strains for both embryos and adults . In the embryos we found that expression divergence is on average more than 20% higher for genes on the X chromosome relative to the autosomes; but in contrast , in the inbred strains , gene expression variation is significantly lower on the X chromosome . Furthermore , expression divergence of genes on Muller's D element is significantly greater along the branch leading to the obscura sub-group , in which this element segregates as a neo-X chromosome . In the adults , divergence is greatest on the X chromosome for males , but not for females , yet in both sexes inbred strains harbour the lowest level of gene expression variation on the X chromosome . We consider different explanations for our results and conclude that they are most consistent within the framework of the faster-X hypothesis . It has long been suspected that the distinct properties of the X chromosome might in turn produce distinct patterns of evolution on the X relative to the autosomes [1] , [2] . In particular , the hemizygoisty of the X could be responsible for increased adaptive or non-adaptive evolution on this chromosome . Assuming an equal sex ratio and an equal variance in reproductive success in the two sexes , there will be three copies of the X in each mating pair versus four copies of each autosome thereby exposing the X to elevated levels of genetic drift [3] . If , however , we consider adaptive evolution , then the hemizygosity of the X is expected to facilitate the spread of recessive beneficial mutations , the selective benefit of which would otherwise be masked when in a heterozygous state on the autosomes [1] , [3]–[5] . Beneficial mutations with additive effects in heterozygotes are selectively equivalent on the X chromosome and on the autosomes , and would therefore be expected to evolve at similar rates across the chromosomes , whereas beneficial mutations that are dominant are expected to evolve faster on the autosomes [5] . A faster X may also be expected if mutations have sexually antagonistic effects , in which the sign of the selection coefficient is opposite in males and females [6] . In both adaptive and non-adaptive scenarios , it is the hemizygous context of the X chromosome in the heterogametic sex that is expected to drive more rapid evolution relative to the autosomes [7] . Determining the relative importance of different evolutionary forces in shaping the X chromosome is crucial for understanding several phenomena related to the X . For example , Haldane's rule , which is a classic generalization stating that in the hybrids of inter-species crosses the heterogametic sex is most often the inviable or sterile sex [8] , could be explained by the fixation of recessive species-specific substitutions on the X chromosome which interact epistatically with autosomal loci [5] . Understanding how the X evolves could also help explain unusual distributions of genes across chromosomes [9] , such as a disproportionate number of genes involved in cognitive function residing on the X in mammals [10] or an excess of sexually antagonistic genes on the X in Drosophila [11] . A fuller understanding of how selection acts differentially across autosomes and sex chromosomes could also shed light on the role of the X chromosome in the evolution of sexually-selected traits [12] . Empirical studies have sought to quantify the importance of adaptative processes in driving the evolution of the X . While many studies have found that the differences between species can often be attributed to X-linked loci of large effect [13]–[15] , much of the recent work has found inconsistent evidence for an excess of positive selection of X-linked proteins . For example , studies of chimpanzee and human orthologs shows that X-linked loci have higher rates of adaptive protein evolution than autosomal loci [16]–[18] , whereas in Drosophila species , whole-genome comparisons do not reveal any bias towards higher rates of protein evolution on the X chromosome [19]–[21] . Other Drosophila studies , which may use biased samples of genes [7] , recover the faster-X effect found in mammals [22]–[25] including a study that demonstrated accelerated evolution of X-linked genes on the newly-formed X chromosome of D . miranda [26] . A recent study in aphids , an X0 sex determination system , found evidence for adaptive evolution of X-linked genes [27] , and , interestingly , the same finding was reported for the Z chromosome ( the equivalent of the X chromosome in the ZW sex determination system ) in a comparison of chicken and zebra finch orthologs [28] . While the evidence for adaptive evolution of the X remains somewhat patchy , such discrepancies suggest that differences in the biology of different groups of species could strongly influence their chromosomal evolution . An important parameter in the faster-X theory is the presence or absence of dosage compensation in the heterogametic sex; that is , whether the presence of a single copy of a gene in the heterogametic sex is compensated , in terms of gene expression , to an extent that it is selectively equivalent to the two copies in the homogametic sex . Theory shows that beneficial mutations will evolve faster on the X compared to the autosomes , only if mutations are at least partially recessive [5] . Thus , to observe a global fast-X effect , most beneficial mutations must be at least partially recessive . In the absence of dosage compensation , however , theory suggests that beneficial mutations must be more recessive for the X to evolve faster provided that the weaker expression in males results in a correspondingly weaker beneficial selection coefficient [5] – this is because dosage compensation equalises the expression of genes expressed on the X in males and females , and is therefore assumed to also equalise their selection coefficients . Thus , fundamental differences in both the extent and mechanism of dosage compensation between different groups of species could have a dramatic effect on the rate of evolution of the X chromosome [5] . However , it is also possible that adaptive evolution of protein sequences accounts for a larger fraction of the evolutionary divergence between some groups of species relative to others . Therefore , while we may not see significantly higher adaptive protein evolution on the X in Drosophila , it is conceivable that adaptive differences in this group of species are most often seen in cis-regulatory , and therefore non-coding , regions of the genome [20] , [29] . We aimed to address evolution on the Drosophila X chromosome relative to the autosomes at the level of gene expression divergence . By focusing on gene expression , we relax the implicit assumption of previous studies that a majority of adaptive evolution occurs via changes in amino acid sequences . Additionally , by measuring divergence in terms of gene expression rather than coding sequences , we could compare expression divergence in embryos relative to adults and therefore ask whether gene expression is free to evolve independently in different stages of the animal's life-cycle . Our results show that mean gene expression divergence is higher for the X chromosome relative to autosomes and , more surprisingly , this effect is much stronger in the Drosophila embryos relative to the adults . Evidence for accelerated evolution of the X in Drosophila has been sought in the adaptive evolution of protein sequences , but has so far produced mixed results [20]–[24] . We chose to focus on the evolution of gene expression with the advantage that we could detect the effects of divergence of non-coding regulatory sequences , and in addition we could directly compare evolution in different stages of the animal's life-cycle . To explore gene expression divergence across Drosophila chromosomes we used gene expression data from two distinct stages of the life-cycle – the embryo [30] and the adult [31] . In addition , we extracted RNA from the embryos of 17 inbred strains of D . melanogaster and hybridised the samples to whole-genome microarrays to provide insight into the maintenance of gene expression variation across chromosomes but within a single species . Similarly , for adult stages we used whole-genome microarray data from 40 adult inbred strains of D . melanogaster separated into males and females [32] , [33] . Table S1 summarises the chromosomal distributions of genes in each dataset . In the between-species data for embryos , the X chromosome has the highest mean expression divergence ( ; Figure 1A ) an effect that ranges from 18% up to 27% higher and in all cases is significant ( see Table S2 for all chromosomal contrasts ) . In contrast , the X chromosome shows the lowest level of gene expression variation between the embryos of inbred D . melanogaster strains ( ; Figure 1B ) , ranging from 7% up to 10% lower ( Table S3 ) . Bootstrap resampling of the mean divergence across chromosomes confirms that it is significantly higher on the X between species ( Figure 1C ) and significantly lower on the X between strains ( Figure 1D ) . In the between-species data , several specific branches in the phylogeny have significantly longer mean lengths judged by bootstrapping individual branches ( Figure S1 ) . In the adults , mean divergence on the X is not higher than the autosomes in females ( ; Figure 2A; Table S4 ) yet gene expression variation is significantly lower on the X relative to the autosomes in female inbred strains ( ; Figure 2B; Table S5 ) . In adult males , mean divergence is highest on the X , although it is not significant ( ; Figure 2E; Table S6 ) , but once again mean variation is significantly lower on the X in inbred strains ( ; Figure 2F; Table S7 ) . Bootstrap resamples confirm that differences between the chromosomes are significant only in the strains ( Figure 2C , 2D , 2G , 2H ) . When we reduce genes and species to a common set belonging to both the embryonic and adult between-species data , we find that the X remains more significantly divergent in the embryonic data ( Tables S8 , S9 ) . In addition , we find that genes with sex-biased expression patterns also do not display an X effect in either sex confirming that the absence of any effect in adults is not caused by combining genes with different properties in the two sexes ( see Methods; Figure S2 ) . We find that divergence on the X in embryos is not driven by a small subset of time points ( Figure 3 ) , nor can it be explained by artifacts caused by extreme expression levels ( Figure S3 ) or by skews in the sex ratio ( Figure S4; see Methods ) . Overall , these results indicate that there is a strong and significant excess of gene expression divergence on the X chromosome in Drosophila embryos together with a significant reduction of gene expression variation on the X within inbred strains of D . melanogaster . Divergence between species coupled with conservation within species is often viewed as a signature of adaptive evolution , and , at the least , is firm evidence against the observed divergence being driven by a relaxation of selective constraints . In the obscura sub-group , Muller's element D ( 3L in D . melanogaster ) has become X-linked and is referred to as a neo-X chromosome . If X-linkage were the cause of increased expression divergence , then we would expect to see accelerated evolution of gene expression on this chromosome relative to the remaining autosomes in this lineage [20] . As with the global X-effect , we see a small but significant increase in divergence on the ancestral branch of the obscura sub-group in the between-species embryonic dataset ( , Wilcoxon one-tailed test; Figure 4A ) . While the ancestral branch shows an excess of divergence ( Figure 4A ) , the terminal branches do not ( Figure S5 ) . In the adult dataset , there is only one species in the obscura sub-group , and the branch leading to this species does not show an excess of divergence ( Figure 4B ) . An excess of gene expression divergence on the ancestral branch leading to the obscura sub-group for the neo-X suggests that evolution of this chromosome was accelerated more after its formation . More generally , this finding lends independent support to the notion that the X evolves more rapidly than the autosomes . The discovery that Drosophila embryos have both an excess of divergence on the X chromosome between species ( Figure 1A ) and significantly lower levels of gene expression differentiation between strains of a single species ( Figure 1B ) is a pattern consistent with what we would expect to be driven by adaptive evolutionary processes . However , such a pattern could also be explained by random genetic drift since lower effective population sizes limit the amount of genetic variance a species can harbour [34] while simultaneously leading to the divergence of separate species through the accumulation of chance variations along separate lineages . To determine whether it is likely that the X chromosome in Drosophila could accumulate mutations at a faster rate than the autosomes simply by virtue of being in a hemizygous state in males , we analysed data from mutation accumulation lines of D . melanogaster [35] . Twelve lines of D . melanogaster were allowed to accumulate mutations over a period of 200 generations . Since selection is relaxed in these lines , mutations are free to accumulate in the population and if the X has a biased accumulation of mutations due to its hemizygosity , we would expect an excess of gene expression variation between mutation accumulation lines for genes expressed on the X than for those on the autosomes . Gene expression was measured genome-wide at the late larval and puparium formation stages of the life-cycle . After fitting linear models to the data , the authors extracted the variance attributable to mutations and scaled it by the residual variance to give a measure of mutational heritability [35] . Mutational heritability is a dimensionless quantity , defined as the variance in a trait which is attributable to new mutations in each generation divided by the variance attributable to environmental variance ( in an initially homozygous population ) [36] . Thus , this measure captures the rate of increase in the heritability of a trait due to mutations . The trait of interest for us is gene expression , and this metric allows us to infer how quickly different mutation accumulation lines diverge from one another in terms of the accumulation of mutations affecting gene expression at individual genes . The results show that , when we restrict the genes to those that have a measurable mutational heritability , the X has the lowest mutational heritability at both life-cycle stages ( , Figure 5A; , Figure 5B , Wilcoxon one-tailed tests ) . In addition , when we include those genes that do not have a measurable mutational heritability , we find that the X has both more genes with zero mutational heritability and less genes with a measurable mutational heritability than would be expected by chance ( Figure 5C , 5D ) . These results suggest that , for these developmental stages at least , the fixation by random drift of mutations influencing gene expression is not biased on the X chromosome and hence is unlikely to be driving higher gene expression divergence on this chromosome . We note , however , that the mutation accumulation lines do not necessarily perfectly capture the conditions experienced by wild populations of Drosophila and so we believe it is important to conduct further studies designed to answer the question of whether the X fixes more mutations due to its hemizygosity . It was recently discovered that there is a paucity of adult tissue-specific gene expression on the Drosophila X chromosome [37] . This result suggests that the distribution of genes across chromosomes may influence observed differences in chromosomal rates of evolution . To test whether X chromosome genes have unusual embryonic tissue expression patterns , we used a controlled vocabulary of embryonic expression terms based on in situ expression data [38] to ask if there is under- or over-representation of expression terms for genes on the X relative to the whole genome . After correcting for multiple testing , just one term showed a significant departure from its null expectation; genes expressed in the cellular blastoderm are significantly under-represented on the Drosophila X ( ; Table S10 ) . This result makes sense when we consider that dosage compensation of X-expressed zygotic genes in male embryos via the MSL ( Male-specific lethal ) complex is not fully active until after the blastoderm stage [39] , [40] . The lag in activation of MSL-mediated dosage compensation may disfavour cellular blastoderm expressed genes from residing on the X , especially as they would need to evolve an alternative dosage compensation mechanism [40] . More generally , the absence of strong tissue-expression biases on the X chromosome suggests that an unusual chromosomal distribution of tissue-specific embryonic genes is unlikely to be driving the higher gene expression divergence that we find on the X chromosome . Recent evidence suggests that epistatic interactions between genes constitutes a substantial fraction of the variation of quantitative traits in Drosophila [41] . Therefore , to determine the relative benefits of chromosomal location and multi-locus co-evolution for beneficial alleles sweeping to fixation in a population , we analysed several diploid population genetic models of the faster-X effect . To compare evolution in equivalent genetic scenarios , we used the ratio of the selection gradient for X-linked versus autosomal cases ( see Methods ) . The results show that , although a faster-X effect exists in all the cases studied , by far the greatest advantage of X-linkage occurs when both epistatically interacting loci are linked on the same chromosome ( Figure 6 , blue circles; Table S11 ) . When both loci are X-linked there will be no recombination in the heterogametic sex , and this will contribute to an increase in the rate of build-up of linkage disequilibrium between the loci . However , in species such as D . melanogaster there is also no recombination occurring between pairs of homologous autosomes in males , and therefore such an effect would contribute to increased evolution on the autosomes . To quantify the magnitude of this effect , we compared the X-linked case to a scenario in which there is no recombination between autosomally linked loci in males . The results show that the effect of a lack of recombination in males cannot account for the advantage enjoyed by X-linked loci , which when compared against the autosomal case in which there is male recombination shows that the advantage in this case is weak and dependent upon high-levels of genetic variance ( Figure S6 ) . Thus , the benefit of X-linkage in the multi-locus case accrues almost entirely from the increased efficacy of selection when acting on hemizygous males . When positively-interacting alleles are located on separate chromosomes , it is extremely unlikely that they will sweep to fixation within a plausible time period because recombination will very effectively decay the linkage disequilibrium that is built up by selection in each generation [42] . When located on the same chromosome , interactions between loci could be considered to be either cis-trans or cis-cis interactions [42] , thereby broadening the scope of possible genetic scenarios that are consistent with faster-X evolution . It remains possible , however , that beneficial trans-acting variants located on the autosomes , and interacting with fixed cis alleles on the X , are responsible for the excess of divergence that we find on the X . However , there are no reasons to suppose that such interactions ought to be biased in the direction of trans-autosomal to cis-X , since , due to symmetry , the opposite scenario of trans-X to cis-autosomal appears to be just as likely . Indeed , in a recent study of gene expression in hybrids of D . yakuba and D . santomea , hybrid male mis-expression was found to be greater for autosomal genes , most likely as a result of faster evolution of X-linked trans-acting factors [43] . Thus , the available evidence suggests that if there is a bias in positive species-specific interactions between the X and the autosomes , it is in the direction of trans-X to cis-autosomal . Overall , both theory and data support the notion that during adaptive evolution , X-linked alleles have a capacity to sweep to fixation faster than their autosomal equivalents , and this effect is greatly enhanced when there are beneficial interactions between two or more loci . In a recent study of gene expression evolution in mammals , evidence was reported for a faster-X effect [44] ( although a separate study found no evidence for a faster-X effect for gene expression in two species of mice [45] ) . The authors correlated gene expression across homologous chromosomes in species pairs and used one minus Spearman's correlation coefficient as a measure of divergence . The same approach has also been used recently to find an excess of divergence on the X in adult males and females of Drosophila species [46] . Thus , we can ask why this correlation-based measure of divergence uncovers an X-effect in adults when our per-gene expression-level measure of divergence does not ( at least not globally – see Figure S7 ) . To aid our search for an answer to this question , we first applied the correlation method to both embryos and adult males and females in the datasets that we have used . The results show that the X chromosome has a reduced cross-species correlation relative to the autosomes in the embryos ( Figure 7A ) , just as it has in both adult males and females ( Figure 8A , B; all pair-wise comparisons are shown in Figure S8 ) [46] . However , when we use an absolute distance metric to determine the per-chromosome differences between species , we find that , while the X consistently displays a greater distance between species in embryos ( Figure 7B ) , in adults the X chromosome is largely equivalent to the autosomes ( Figure 8C , 8D; Figure S9 ) . Thus , the question arises as to why the X chromosome appears more divergent in terms of correlations but not in terms of distances ? The answer must be sought in the component of gene expression divergence that each measure is capturing . Spearman's rank correlation coefficient is a dimensionless number that in the context of gene expression in two species , determines the extent to which expression relationships between genes are retained across the two species , and the strength of the correlation is insensitive to absolute expression differences ( Figure S10 ) . Thus , this measure of divergence captures how co-ordinated expression is across a specific set of genes in two different species . In contrast , absolute distances , and per-gene expression changes , measure to what extent individual genes differ in expression level in two species , and these metrics are insensitive to how co-ordinated expression is between different genes . This suggests , therefore , that gene expression on the X chromosome in adults is weakly co-ordinated relative to expression on the autosomes even though absolute expression differences are not significantly greater on the X ( Figure S10 ) . Furthermore , when we compare the chromosomal correlations in embryos and adults , we find that embryos have much higher correlations overall than the adults even when we reduce them both to a common set of genes and species ( Figure S11 ) . This suggests that gene expression is generally more highly co-ordinated in Drosophila embryos relative to adults . The excess of gene expression divergence that we find in the embryonic data could be driven by a relaxation of selective constraints acting on X-linked gene expression . We would predict that relaxed selective constraints would lead to an elevation of within-species gene expression variation on the X , and , contrary to this prediction , we find that gene expression variation within inbred strains of D . melanogaster is significantly lower on the X relative to the autosomes ( Figure 1B , 1D ) suggesting that X-linked gene expression is not evolving under a relaxation of selective constraint . In support of this finding , we find a corresponding reduction in gene expression variation on the X in both adult males and females ( Figure 2B , 2D , 2F , 2H ) [46] . Nonetheless , it remains possible that elevated between-species variance coupled with diminished within-species variance is a consequence of random genetic drift , or demographic effects such as bottlenecks [3] , [47] . If the hemizygosity of the X chromosome in males , and the resulting potentially diminished effective population size of the X , were resposible for the lower within-species variance in X-linked gene expression , then we would expect to find an excess of fixation of X-linked gene expression mutations in separate mutation accumulation lines . However , we find the opposite pattern , that mutation accumulation lines display less gene expression variation for X-linked genes ( Figure 5 ) . Part of the reason for this could be due to the X chromosome presenting a smaller mutational target than the autosomes as a result of being in a hemizygous state in males , but this effect of hemizygosity will be present in wild populations of Drosophila as much as in lab-reared lines . It is also possible that , while the experimenters made every effort to neutralise the effects of mutations , selective effects remained in the accumulated mutations and that purifying selection is stronger on the X relative to the autosomes . Prior studies have found that the X chromosome in Drosophila experiences more effective purifying selection against weakly deleterious and recessive mutations [48]–[51] , and in non-recombining chromosomal regions , the X has been shown to experience the smallest reduction in the efficacy of selection [52] . In addition , studies of nucleotide diversity on the X in both coding and non-coding regions in Drosophila species suggest that adaptive processes best explain the observed variance on the X [29] , [47] , [53] , including recent data showing that there is an absence of X-autosomal differences for putatively neutral sites [25] . Overall , our findings are consistent with there being an excess of adaptive evolution of X-linked gene expression , although this does not mean that drift or demographic effects are not involved in shaping gene expression evolution . Gene expression is influenced by both cis-acting regulatory sequences , and by trans-acting factors , such as transcription factors . Thus , while we observe an excess of X-linked divergence of gene expression , this could be the result of either trans-acting factors potentially located on other chromosomes , X-linked cis-acting variants , or a combination of both . Several studies have found evidence for both cis and trans effects influencing gene expression differences both within and between Drosophila species [54]–[59] . Thus far , however , the evidence suggests that there is an excess of cis-acting variants influencing divergence between species [54]–[56] , [60] , and that cis-regulatory divergence increases with the divergence time between species [55] , [59] . One study reported an excess of trans-acting variation influencing gene expression in a comparison of D . melanogaster and D . sechellia , although as noted by the authors this could be related to the unusual demographic history and life-history evolution of D . sechellia [59] . It's possible that the excess of X chromosome divergence that we see is the result of a bias in the direction of autosomal trans-acting factors impacting the X chromosome more than the reverse situation of X-linked trans-acting factors affecting the autosomes . Current evidence suggests , however , that the opposite is the case – that there is a bias towards trans-acting factors on the X impacting autosomal cis-elements resulting in an excess of autosomal mis-expression in Drosophila hybrids [43] , including a study of mis-expression in hyrbid D . simulans males carrying an X-linked allele introgressed from D . mauritiana [61] . Therefore , if there are species-specific interactions between the X and the autosomes , it seems unlikely that they would be biased in such a way as to account for our results . Theoretical considerations also do not favour the notion that trans-acting factors could be driving the majority of the divergence that we find , assuming that a substantial fraction of this divergence is adaptive . Mutations in trans-acting factors are more likely to be pleiotropic , and so should have less scope to influence adaptive evolution than the more modular effects of mutations in cis-regulatory regions [42] , [62]–[65] . Furthermore , population genetic models of the faster-X effect show that if there are two or more interacting loci with beneficial interactions between them , then X-linked loci enjoy a far greater benefit than autosomal loci ( Figure 6 ) . Whether adaptive changes occur in cis or in trans also has important consequences for the scope of mutations to have recessive or partially recessive effects on fitness , which in turn is of central importance for the faster-X phenomenon [5] . We address these issues towards the end of the Discussion . In the embryonic between-species data , we found evidence for faster evolution of gene expression on the X chromosome using two different measures of divergence ( Figure 1A , Figure 7A ) . The first measure captures the change in expression levels on a per-gene basis ( Figure 1A ) , and the second captures the extent to which gene expression relationships between genes have changed in pairs of species , and hence how co-ordinated expression is across a subset of genes ( Figure 7A , Figure S10 ) . In contrast , in the adults , we see evidence for higher divergence on the X chromosome using only the second measure of divergence ( Figure 8A ) and not the first ( Figure 2A ) . This suggests that , while the X displays lower levels of co-ordinated expression in pairs of species in the adult , it does not exhibit significant differences in expression level on a per-gene basis . Then we must ask , why does the embryo diverge more on the X in terms of per-gene expression levels than the adults ? Embryogenesis is a highly dynamic process , driven by a cascade of gene expression unraveling through a highly co-ordinated developmental network leading to large batteries of genes being switched on and off at precise moments during development [66] . In contrast , in a fully developed adult , cells are largely fully differentiated , and gene expression is to a much lesser degree responding to a pre-determined developmental program , and is freer to respond to changes in the environment . Thus , it makes sense that we find gene expression to be overall much more highly co-ordinated in the embryo relative to the adults ( Figure S11 ) . But it is precisely because of the broad dynamic range of embryonic gene expression , with a large fraction of the zygotic genome being activated in a series of waves as embryogenesis proceeds ( Figure S12 ) , that even subtle shifts in timing could potentially produce large differences in expression levels . In a whole adult fly , however , genes are likely expressed in subsets of tissues and organs such that we will not find extremely low or high expression levels for most genes when we extract RNA from all of the tissues simultaneously , thereby diminishing the dynamic range of the data . Therefore , our results highlight the need to perform more precise organ-by-organ comparisons of gene expression in future between-species studies of adult flies . In addition , our analysis draws attention to the different components of divergence that are captured by different measures of gene expression divergence . Taking the above considerations and all of our results into account , we believe that the X effect we find in the embryos is best explained within the framework of the faster-X hypothesis . This does not mean that all of the divergence we see is driven by adaptive substitutions in cis-regulatory regions on the X chromosome , but rather that the excess of X chromosomal divergence that we find together with the reduction of expression variation in inbred strains of D . melanogaster is most consistent within an adaptive evolutionary scenario . In support of this interpretation , researchers found an excess of adaptive substitutions on the X chromosome in a long-term evolution experiment involving lines of D . melanogaster selected for increased rates of egg-to-adult development [67] . An interesting theoretical corollary of the fast-X interpretation is that it suggests that adaptive substitutions are more likely to occur via new mutations than from standing genetic variation [68] . If we adopt a faster-X interpretation of the data , then we must provide some explanation as to why beneficial cis-regulatory mutations have recessive or partially recessive effects on fitness , in keeping with the original model [1] . Current evidence in adult Drosophila species suggest the opposite , that cis-acting variants have largely additive effects relative to trans-acting factors , which show more deviations from additivity towards dominance and recessiveness [55] , [59] . However , these experiments determine the additivity of the phenotype of a cis variant ( where the phenotype is its gene expression level ) , and not necessarily its effect on fitness . Theory suggests that mutations could have fitness consequences that are non-linear even if they have additive phenotypic effects [69] . Therefore , it is possible that phenotypic measures of cis-acting elements fail to capture their effects on fitness . To understand the fitness effect of a mutation in an organismal context , we must focus on the biology of the organism , and not just on its genetics . One potential route towards non-additive intra-locus effects on fitness is canalisation . The canalisation of embryonic development , such that it is resistant to environmental or genetic perturbations , has long been recognized as a crucial element contributing to the evolution of robustness in developmental systems [70] . The evolution of dominance is a means by which the components of a network could become canalised [71]–[74] . While selection acting on modifiers of dominance will typically be weak ( of the order of the mutation rate ) , it can be substantially stronger in non-equilibrium populations where genetic variation is maintained at high levels by processes such as migration and hybridisation [72] , [74] . The notion that the evolution of robustness ( i . e . , an attempt to prevent change of the phenotype ) could lead to faster evolution of the X may seem counter-intuitive . However , the relationship between robustness and evolvability is well established , and suggests that the evolution of phenotypic robustness can often facilitate adaptive evolution [75]–[77] . We present this scenario partly to illustrate that the biological details of an individual species , such as species range and migratory pressures , might play a significant role in determining how its chromosomes evolve . We report evidence that gene expression evolves faster on the X chromosome in Drosophila embryos . While our results are consistent with adaptive evolutionary processes , more work is required to unravel the details underpinning this excess of divergence at the genetic , phenotypic , and fitness levels . We contend that variations in biological and life-history details , such as differences in dosage compensation menchanisms , can strongly impact how the chromosomes of different species evolve . We therefore stress the importance of appreciating biological context when attempting to understand chromosomal evolution . Deciphering the relationship between species-specific biology and chromosomal patterns of evolution promises to provide fertile ground for future research . We used inbred strains of D . melanogaster , originally collected from farmer's markets in North Carolina and provided as a resource by the Drosophila Genetic Reference Panel ( DGRP; http://dgrp . gnets . ncsu . edu/ ) [33] . Seventeen strains were selected for the collection of 0–2 hour old embryos . Populations of healthy adults from 3–7 days of age , were reared at 25°C and used for embryo collections . To synchronize the age of the embryos in each sample , we pre-laid the flies three times for 1 hour with a fresh apple juice plate with yeast paste before every collection . Another fresh plate with yeast was used to collect the embryos . After collection , embryos were rinsed with distilled water and then dechorionated in 100% bleach for 2 minutes before being washed in desalinated water . The embryos were then transferred into a 1 . 5-ml tube and snap-frozen in liquid nitrogen and stored at C . Three biological replicates were collected for each strain . To isolate RNA , embryos were thawed on ice and homogenized with a pellet pestle and a pellet pestle cordless motor ( Kontes ) . RNA was isolated with the RNeasy Mini kit ( Qiagen ) and eluted with 30 ml of distilled water . The RNA concentration was measured with the NanoDrop spectrophotometer and RNA quality was assessed with Bioanalyser using the Agilent RNA 6000 Nano kit . To prepare samples for hybridization to the chip , we followed the Agilent One-Colour Microarray-Based Gene Expression Analysis protocol version 6 . 5 ( Low Input Quick Amp Labeling ) . The starting amount of RNA was normalized to 100 ng for all samples . Embryonic expression in Drosophila was taken from a species-specific microarray data set , in which eight time-points were sampled for the duration of embryogenesis of D . melanogaster , D . simulans , D . ananassae , D . pseudoobscura , D . persimilis , and D . virilis [30] . Adult Drosophila expression was collected from a microarray experiment that measured the gene expression of whole flies sorted into males and females and taken from D . melanogaster , D . ananassae , D . mojavensis , D . pseudoobscura , D . simulans , D . virilis , and D . yakuba [31] . Gene expression mutation accumulation data was taken from a microarray study of mutation accumulation lines of D . melanogaster [35] . Adult D . melanogaster strain data was taken from a whole-genome microarray study of gene expression in whole adult flies from 40 inbred strains separated into males and females [32] . To quantify gene expression divergence in a chromosomal context , we fitted the following linear model [78] to gene expression measures , , where is the effect of the species , is the effect of the chromosome , and is the effect of the gene nested in the chromosome . The interaction between the species and the gene nested in the chromosome , , provides information about species-specific chromosomal expression of a gene and is given bywhere values are averaged over missing subscripts indicated by dots . Thus , the effect of the gene in the species is the excess that cannot be explained by the expression of the gene across species , the expression of the chromosome in the species , and the overall expression on the chromosome . When there are multiple expression measures over a time-course , our measure of divergence is designed to detect translations up or down in expression level across the time course as a whole ( see Figure S13 ) . Differentiation of gene expression between inbred strains was determined using the R package ‘limma’ [79] . Limma fits linear regression models to each gene separately . The differentiation of each gene was then scored as the mean log fold change of the gene across all pairwise strain comparisons . Absolute pairwise species contrasts of the values were transformed into branch lengths using the Fitch-Margoliash least squares method ( implemented in the PHYLIP program fitch ) [80] . Negative branch lengths were set to zero , and for all genes the topology of the known phylogeny was used [81] . Per-gene expression divergence was then expressed as the sum of all of the branch lengths in each gene tree separately . To test for acceleration on one lineage , for each gene we expressed the branch length of the focal lineage as a proportion of the total of all branch lengths . In the embryonic dataset we chose the ancestral branch leading to the common ancestor of D . pseudoobscura and D . persimilis but not including the terminal branches ( Figure 4A ) . For the adult dataset , which does not have data for D . persimilis , we used the terminal branch leading to D . pseudoobscura ( Figure 4B ) . Mean summed branch lengths were bootstrapped by resampling the genes on each chromosome 10 , 000 times with replacement and in each bootstrap replicate calculating the mean summed branch lengths for the genes on each chromosome ( Figure 1C , 1D ) . Individual branches in the embryonic and adult datasets were tested for an excess of divergence on the X chromosome using the number of bootstrap replicates in which mean autosomal branch lengths were greater than the mean on the X chromosome ( Figure S1 ) . All resampling was carried out using the R statistical programming environment [82] . In both of the Drosophila between-species data sets , the smallest sample of genes was on the X chromosome ( Table S1 ) . To determine whether the differences between the X and the autosomes could have been caused by a sampling bias on the X , we resampled the number of genes present on the X from the autosomes 10 , 000 times without replacement and each time recalculated the mean divergence . The distributions of these resampled means are shown in Figure S14 . Expression of genes in the adults can be biased towards one of the sexes [31] , and it's possible that sex-biased genes might exhibit stronger differences in divergence across the chromosomes . We focused on male and female-biased genes identified in [31] in each of the species . Genes that show a male-bias in at least one species show a significant excess of divergence in both males and females ( ; ; Figures S15 , S16 ) [83] , [84] , and conversely female-biased genes are significantly more conserved in both males and females ( ; ; Figures S15 , S16 ) . When we look at divergence across chromosomes , however , we find that sex-biased genes are not significantly more divergent on the X in either sex ( Figure S2 ) . Interestingly , when we restrict male-biased genes to those in D . melanogaster and D . simulans we do find a weak but significant excess of divergence on the X ( ; Figure S7 ) , which is absent for the same genes expressed in females ( ; Figure S7 ) . The biological function of these genes is enriched for carbohydrate metabolism ( ) and alcohol metabolism ( ) , which might suggest that these are genes that have evolved rapidly and relatively recently , thus preserving the signal of an excess of divergence on the X . Indeed , we find that these genes are significantly more divergent than average ( ; Figure S17 ) . In the between-species embryonic data , our measure of divergence is designed to detect translations in expression up or down in different species across the embryonic time course as a whole ( Figure S13 ) . However , it remains possible that much of the difference that we detect between the X and the autosomes is driven by a subset of the time points . To test this , we extracted divergence measures from each time point separately . We then bootstrap resampled divergence measures for the X chromosome and the autosomes and in each bootstrap replicate calculated the ratio of mean X to mean autosomal divergence . The results show that at every time point the X chromosome displays an excess of divergence relative to the autosomes ( X/A ratio ; Figure 3 ) . Furthermore , all of the resampled time point distributions heavily overlap with one another indicating that higher expression divergence on the X is not driven solely by one or a subset of time points . Differences in gene expression divergence across chromosomes could be influenced by consistent differences in expression levels across chromosomes . In the between-species embryo data , the X chromosome has the weakest mean expression level ( Figure S18 ) , whereas in the adults , the X chromosome has the highest mean expression level ( Figure S18 ) . Higher expression in the adults could be a reflection of a paucity of adult tissue-specific expression on the X chromosome [37] . To elucidate the relationship between expression level and divergence in these data sets , we ranked genes by their expression level ( lowest to highest ) , binned them into groups of 50 genes , and measured the deviation of each group's mean divergence from the global mean divergence . The results show that for the embryos , the relationship is non-linear , with groups of the weakest expressed genes diverging less than the global average ( Figure S19 ) . Thus , although an increasing expression level does predict less divergence , divergence cannot be attributed simply to stochastic fluctuations of the weakest expressed genes . In the adults , the relationship is more linear , with the weakest expressed genes showing the highest divergence ( Figure S19 ) . Thus , higher expression on the X in adults may at least partly explain the lower levels of divergence relative to the embryos . To clarify the relationship between expression level and chromosomal divergence , we bootstrap sampled genes from each chromosome while weighting their probability of being sampled according to their expression level . To sample genes according to expression level we weighted the probability of being sampled according to the cumulative distribution function of a normal distribution with a specified mean expression level and standard deviation . We defined the standard deviation as the standard deviation of the whole expression level distribution divided by the number of mean expression levels that were being sampled . Genes were then sampled with replacement 10 , 000 times for each mean expression level for each chromosome in both the embryonic and adult datasets . Fewer mean expression levels were taken for the adult data due to its lower expression level variance . The results show that , in the embryo , divergence on the X is greater than the autosomes for intermediate gene expression levels , but not when expression is high or low ( Figure S3A ) . In contrast to this result , in the adult data the X shows higher expression divergence when gene expression is low or high ( Figure S3B ) . Thus , the higher expression divergence of the X in the embryos is not driven by expression levels at the extremes of the distribution . While divergence on the X is not driven by particular periods during development , it is possible that there is a bias in the direction of expression differences between species . For example , if there was a persistent skew towards a male-biased sex ratio in one species relative to another and if dosage compensation in males was incomplete , then we would expect X-linked genes to show a skew towards lower expression in this species as the male-biased population would amplify the incomplete dosage compensation . To test this , we contrasted normalized expression in pairs of species and scored genes as up or down in one species relative to the other . We then asked if the X-chromosome showed significant skews in the number of genes scored as up or down in these species pairs relative to the autosomes . The results show this is not the case for any species pair ( Figure S4 ) , and this is shown in more detail for the D . persimilis versus D . pseudoobscura contrast ( Figure S20 ) , which is pertinent given that there is an excess of X chromosome divergence in this species comparison ( ; Figures S1 , S21 ) . Therefore , there do not appear to be systematic biases in the direction of expression differences between species and hence this is unlikely to be a factor driving the higher divergence of the X chromosome . The discovery that different groups of genes exhibit differences in their chromosomal divergence in adults suggested that there may be a relationship between excess chromosomal divergence and the rate of gene expression evolution . To test this , we scored the ratio of mean divergence of genes belonging to each percentile of each chromosome's divergence distribution relative to the same percentile of the other chromosomes . The results show that in both the embryos and the adult males , excess divergence on the X chromosome increases as the genes become more divergent while such a pattern is not seen consistently on any of the other chromosomes ( Figure S22 ) . In addition we find that while in the embryos most of the genes on the X exhibit an excess of divergence relative to the autosomes , in adult males these genes are restricted to a subset of those on the X . The top enriched biological functions for these genes are primary sex determination , secondary metabolic process , and adult behavior ( Table S12 ) , all likely to be fast-evolving traits and processes . It is interesting to note that in both cases , the fastest evolving genes do not display an excess of divergence on the X . Overall , however , we find that fast-evolving genes tend to diverge more on the X in both embryos and adult males . In the embryonic time course , an initially bimodal gene expression distribution gradually becomes unimodal as the zygotic genome is switched on during embryogenesis ( Figure S12 ) . If the X chromosome happened to be over-represented for genes in the lower mode of this bimodal distribution , then it is possible that much of the excess divergence we find on the X could be driven by spurious divergence between non-expressed genes . Therefore , to test for this we used the expectation-maximisation algorithm to determine a cutoff expression level ( based on time point 1 ) below which a gene could be considered as non-expressed at any time point ( expression of 8 . 513 ) . We then defined three gene sets based on increasingly more stringent criteria for being thrown out from the analysis . The first set ( termed “Two” ) consists of genes that are not expressed in at least two species in at least one time point ( 1502 genes ) . The second set ( “Six” ) consists of genes that are not expressed in at least six species in at least one time point ( 849 genes ) , and the final set ( “Six-Eight” ) consists of genes that are not expressed in at least six species at every time point ( 536 genes ) . Expression distributions for these gene sets shows that they increasingly capture more weakly expressed genes as the criteria for exclusion becomes more stringent ( Figure S23 ) . When we compare gene expression divergence for the data set after removing these gene sets , we find that the excess of divergence on the X is not affected ( Figure S24 ) showing that this effect is not driven by spurious divergence between non-expressed or weakly expressed genes . To determine whether the lower effective population size of the X chromosome might increase the chance that it fixes weakly deleterious mutations , we used gene expression mutation accumulation data to assess potential chromosomal biases in the accumulation of gene expression differences . We used jack-knifed mutational variance estimates scaled by residual variances to provide estimates of the mutational heritability of gene expression changes between lines [35] . As a large fraction of the genes at both the late larval and puparium formation stages did not exhibit measurable mutational heritabilities , we separated the genes with measurable estimates ( Figure 5A , 5B ) . In addition , we categorized genes as having measurable mutational heritabilities from those without and compared the ratios of these two categories across chromosomes using contingency tables . The results were visualized using residual-based shading with the R package ‘vcd’ [85] ( Figure 5C , 5D ) . A hierarchically-arranged controlled vocabulary ( CV ) of embryonic tissue expression terms based on an in situ expression data set [38] was used for assessing under- or over-representation of expression patterns for genes on the Drosophila X chromosome . Enrichment of terms was carried out in the R package ‘topGO’ [86] using custom-written code . The parent-child algorithm was employed to control for the inheritance bias between parent and child terms in the CV hierarchy [87] ( Table S10 ) . The resulting P-values were adjusted using the Benjamini-Hochberg correction in the R package ‘multtest’ [88] . In all of our models , we assume that selection coefficients are equal in the two sexes , which corresponds to the assumption of complete dosage compensation in [5] , and , in the case of the two-locus models , that there is a beneficial epistatic interaction between one of the alleles at each locus . In addition , we assume that viability selection operates on the diploid zygotes , that mating is random , and that double heterozygotes experience half of the fitness benefit of single heterozygotes ( Tables S11 , S13 ) . We derived genotype frequency recurrence equations to describe the evolutionary dynamics in our models and then solved the equations numerically . To compare evolution in the equivalent X versus autosomal scenarios , we extracted the change in allele frequency of the cis-acting beneficial allele between generations , . We used the ratio of selection gradients in the equivalent models as a comparative statistic . The selection gradient describes the change in relative fitness as the allele frequency of the beneficial variant changes . Using the Robertson-Price identity [89] , [90] to describe the change in allele frequency , , in terms of relative fitness , , and replacing with the regression coefficient , , then the selection gradient , , is equal to the change in allele frequency divided by its variance , . We plot the ratio of selection gradients in the X versus autosomal cases ( Figure 6 , Figure S6 ) . Spearman's was measured for pairs of chromosomes in pairs of species for both the embryonic and adult data . Correlation coefficients were bootstrapped by resampling the genes 10 , 000 times on each chromosome separately ( Figure 7A , Figure 8A ) . For the embryos , we used expression averaged across time , and found that correlations derived from this measure agreed very well with correlations derived from expression within single time points in terms of a reduction of correlation on the X chromosome . In addition , we took the mean Canberra distance across chromosomes for pairs of species , averaging it by dividing by the number of genes on each chromosome separately ( Figure 7B , Figure 8B ) . The correlation approach captures the extent to which chromosomal subsets of genes tend to conserve their expression relationships in pairs of species . However , this approach fails to capture the level of conservation of gene expression in a chromosomal subset relative to a separate chromosomal subset across pairs of species . For example , we might wish to ask whether the expression relationship of genes on the X chromosome relative to the autosomal arm 2L shares a conserved pattern in a pair of species . To answer questions of this nature , we introduce a variant of Spearman's correlation coefficient which allows us to rank genes in a chromosomal subset relative to genes in a separate chromosomal subset for pairs of species . For the correlation of subset relative to subset in two species we havewhere and are the ranks of the 'th gene's expression level ( from the genes that belong to subset ) relative to gene expression in subset for species and species respectively . Thus , this relative measure captures whether expression in subset is co-ordinated relative to subset in pairs of species . As it is established that correlation coefficients within subsets can vary , sometimes dramatically , from correlation at the level of aggregates ( known as the Yule-Simpson effect [91]–[95] ) , we believe that it is necessary to account for possible discrepancies when measuring correlation within subsets drawn from a larger population ( Figure S25 ) . When we measure relativised correlations for chromosomal subsets in the embryonic and adult data , we find that the X chromosome displays a significantly higher correlation when correlating against an autosomal background in adult females ( Figure S26 ) . This suggests that in adult females the X is generally more co-ordinated in relation to the autosomes than in relation to itself ( ; Wilcoxon two-tailed test ) , a pattern that could be driven , in part , by gene interactions between the X and the autosomes . More generally , this result highlights the importance of considering cross-chromosome relationships when using correlation-based measures of divergence .
There is a single copy of the X chromosome in males , yet two copies in females . This unique inheritance pattern has long been predicted to influence how the X chromosome evolves . In particular , the theory suggests that the single copy of the X in males could facilitate faster evolution of the X , although this faster evolution could be either adaptive or non-adaptive . We measured gene expression across the chromosomes in several different Drosophila species and also in several inbred strains of D . melanogaster for both embryos and adults . We found that gene expression is evolving significantly faster between species in the embryos , yet harbours significantly less variation within inbred strains . In adults , evolution between species appears to be much slower than in the embryos , yet they also harbour significantly lower levels of gene expression variation on the X chromosome in inbred strains . Overall , our results are consistent with there being an excess of adaptive evolution on the X chromosome in Drosophila embryos . Finally , we underscore the importance of biological context for understanding how chromosomes evolve in different species .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "developmental", "biology", "population", "genetics", "biology", "evolutionary", "biology", "population", "biology", "genetics", "and", "genomics", "evolutionary", "developmental", "biology" ]
2012
An Excess of Gene Expression Divergence on the X Chromosome in Drosophila Embryos: Implications for the Faster-X Hypothesis
Holliday junctions ( HJs ) are cruciform DNA structures that are created during recombination events . It is a matter of considerable importance to determine the resolvase ( s ) that promote resolution of these structures . We previously reported that C . elegans GEN-1 is a symmetrically cleaving HJ resolving enzyme required for recombinational repair , but we could not find an overt role in meiotic recombination . Here we identify C . elegans proteins involved in resolving meiotic HJs . We found no evidence for a redundant meiotic function of GEN-1 . In contrast , we discovered two redundant HJ resolution pathways likely coordinated by the SLX-4 scaffold protein and also involving the HIM-6/BLM helicase . SLX-4 associates with the SLX-1 , MUS-81 and XPF-1 nucleases and has been implicated in meiotic recombination in C . elegans . We found that C . elegans [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants showed a similar reduction in survival rates as slx-4 . Analysis of meiotic diakinesis chromosomes revealed a distinct phenotype in these double mutants . Instead of wild-type bivalent chromosomes , pairs of “univalents” linked by chromatin bridges occur . These linkages depend on the conserved meiosis-specific transesterase SPO-11 and can be restored by ionizing radiation , suggesting that they represent unresolved meiotic HJs . This suggests the existence of two major resolvase activities , one provided by XPF-1 and HIM-6 , the other by SLX-1 and MUS-81 . In all double mutants crossover ( CO ) recombination is reduced but not abolished , indicative of further redundancy in meiotic HJ resolution . Real time imaging revealed extensive chromatin bridges during the first meiotic division that appear to be eventually resolved in meiosis II , suggesting back-up resolution activities acting at or after anaphase I . We also show that in HJ resolution mutants , the restructuring of chromosome arms distal and proximal to the CO still occurs , suggesting that CO initiation but not resolution is likely to be required for this process . Homologous recombination is important for error-free DNA double-strand break ( DSB ) repair and for meiotic crossover ( CO ) formation . Meiosis is a specialized series of two sequential cell divisions that ensures the reduction of the diploid genome and results in the production of haploid gametes . During meiosis COs generate genetic diversity . Moreover , CO products , which at the level of chromosomes become visible as chiasmata , provide stable connections between maternal and paternal homologous chromosomes ( homologues ) . The connection provided by chiasmata is required for accurate homologue segregation in the first meiotic division . Meiotic recombination is initiated by the introduction of programmed DSBs [1] by the conserved meiosis-specific Spo11 protein [2] . These DSBs are resected to produce 3′ single-stranded DNA overhangs that , aided by RecA like recombinases ( RAD-51 in C . elegans ) , initiate strand invasion into a homologous donor sequence [3] . In most organisms studied so far , the estimated number of induced DSBs during meiosis exceeds the number of COs generated , with ratios as variable as 2∶1 in S . cerevisiae up to 20∶1 in maize [3]–[9] . In C . elegans only one DSB per homologue pair will result in a CO event [10] , [11] . Following strand invasion by the 3′ single-stranded overhang the first recombination intermediate ( RI ) is referred to as ‘D-loop’ ( for review [12] , [13] ) . Helicase-driven D-loop disassembly can occur , which in budding yeast is driven by the Sgs1/BLM-like helicase [14] . Such activities are also ascribed to BLM in animals and further helicases such as RTEL are likely to play a similar role [15] . After D-loop disassembly , the invading 3′ single strand , which has been extended by DNA synthesis , can capture the other broken DNA end and synthesis-dependent strand annealing ( SDSA ) occurs . SDSA occurs relatively early during meiosis and appears to be set up independently of later RIs which can result in COs , at least in yeast [16]–[19] . Interestingly , in C . elegans deletion of the RTEL helicase , which can promote D-loop disassembly in vitro , leads to an elevated number of meiotic COs [15] , [20] . In contrast , deletion of him-6 , the C . elegans BLM homologue , results in reduced meiotic CO formation consistent with the occurrence of an increased number of unconnected homologues visible as univalents in oocytes of strong him-6 mutants [21] . When the D-loop remains intact , second DNA end capture by the extended invading single-strand leads to a cruciform DNA structure called Holliday junction ( HJ ) . Such RI was originally postulated in 1964 [22] and a refined model predicted that the majority of HJs occur as double HJs ( dHJs ) [23] . Direct evidence for the occurrence of dHJs as RIs during meiosis ( and during DSB repair in diploid mitotic cells [24] ) was obtained in budding yeast [25] , [26] , while in fission yeast single HJs appear to be predominant [25] . dHJs can be processed in various ways and result in either a CO or a non-CO ( NCO ) . In a process referred to as dHJ dissolution , coupled helicase and topoisomerase activities conferred by Sgs1/BLM and Top3-Rmi1 can disassemble dHJs , resulting in a NCO [27] . Alternatively , dHJs can be resolved by nucleases ( for review see [28] , [29] ) . Depending on the symmetry of the cleavage , either COs or NCOs arise . Canonical HJ resolvases , such as RuvC and RusA , were first described in bacteria and bacteriophages [30]–[32] . These resolvases confer symmetrical cleavage of HJ substrates so that cleavage products can be re-ligated in vitro . In other organisms , nuclear ‘canonical’ resolvases remained elusive [33] . The first such purified activity was shown to be conferred by an N-terminal fragment of the human Gen1 nuclease albeit a lower level activity towards FLAP structures is detectable [34] . The respective budding yeast ( Yen1 ) and C . elegans proteins ( GEN-1 ) also confer in vitro HJ resolution [34] , [35] . In budding yeast yen1 single mutants do not show an obvious recombinational repair or meiosis defect [36]–[38] . Gen1 is absent in fission yeast . In C . elegans gen-1 mutants are defective in recombinational repair and DNA damage checkpoint signalling while no overt meiotic phenotype is apparent [35] . There is emerging evidence that HJ resolution might not necessarily be conferred by symmetrically cleaving ‘canonical’ resolvases . Rather ( combinations of ) non-symmetrically cleaving nucleases as well as helicases might confer the resolution of HJs . A dominant role of the Mus81 nuclease and its regulatory subunit Eme1/Mms4 in meiotic HJ resolution is evident in fission yeast , and the associated meiotic defect can be bypassed by expressing bacterial RusA resolvase [39] . Mus81 catalyses multiple structure-specific nuclease reactions: it cleaves FLAP structures and D-loops and has a very high affinity for nicked HJs in vitro . Cleavage of intact HJs by Mus81 in vitro occurs with low activity ( for review [29] ) . In budding yeast mus81 yen1 double mutants meiotic chromosome segregation is perturbed due to persistent chromatin linkages [40] . Yen1 is kept inactive in the first meiotic cell division by phosphorylation , but becomes active in the second meiotic division , where it appears to provide a back-up function if chromosomes remain entangled after the first meiotic division [40] . Nevertheless , the rate of meiotic recombination is only slightly reduced in mus81 yen1 double mutants [40] . MUS81 deletion confers only ‘minor’ meiotic phenotypes in mice [41] and in C . elegans MUS-81's activity only becomes apparent in mutants producing aberrant CO products [20] , [42] . Another possible factor contributing to HJ resolution is the conserved Slx4 scaffold protein with its associated nucleases Xpf1 , Mus81 and Slx1 [42]–[48] . Xpf1 is a FLAP endonuclease that together with Ercc1 is required for the 5′ incision in nucleotide excision repair [49] , as well as for cleaving FLAP structures in the single-strand annealing DNA repair pathway [50] , [51] . In the fruit fly mei-9/xpf1 mutants have dramatically reduced rates of meiotic recombination [52] , and this was also seen in mus312/slx4 , albeit with even lower meiotic recombination levels [43] . Genetic evidence suggests that MUS312/Slx4 and MEI-9/Xpf1 might act as a complex to exert this function in the fly [43] . A reduced recombination rate together with occasional DNA threads linking meiotic chromosomes were also reported for C . elegans slx-4 ( also termed him-18 ) [42] . An overt role of Xpf1 in meiotic HJ resolution has not been documented for any other organism . Recent evidence suggests that C . elegans SLX-1 does not affect the frequency but the distribution of meiotic CO , such that recombination events are shifted toward the centre of chromosomes in slx-1 mutants [47] . In budding yeast an sgs1 , mms4 ( mus81 ) , yen1 , slx1 quadruple mutant exhibits a severe reduction but not complete elimination of meiotic COs . It was also reported that the Exo1 nuclease and the mismatch-repair proteins Mlh1 and Mlh3 contribute to HJ resolution [53] . Accordingly , no COs were observed in yeast mlh3 , sgs1 , mms4 ( mus81 ) , yen1 , slx1 quintuple mutants , when RIs and CO products were assessed employing a recombination hotspot system [14] , [54] . It remains to be shown how the interplay of these nucleases and the Sgs1 helicase contributes to CO formation . In addition very little is known about meiotic HJ resolution in animals . Here we report a systematic analysis of the role of various nucleases in promoting the resolution of meiotic RIs , likely HJs , in C . elegans . We found no meiotic phenotypes associated with gen-1 neither as a single mutant nor in combination with him-6 or various nuclease mutants . In contrast , [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] but not [xpf-1; him-6] or [mus-81 slx-1] double mutants show synthetic meiotic phenotypes consistent with a defect in resolving/processing meiotic RIs . A large proportion of chromosomes fail to form bivalents , instead univalent structures linked by distinct chromatin bridges become apparent using high-resolution microscopy . Our data also indicate that XPF-1 , MUS-81 and SLX-1 might exert their meiotic function in complex with the SLX-4 scaffold protein . Our results are consistent with the existence of at least two redundant meiotic resolvase activities: one requiring HIM-6 and XPF-1 , and the other dependent on SLX-1 and MUS-81 . Furthermore , we found that CO designation as well as the subsequent differentiation of CO distal and proximal chromosome arms still occurs when HJ resolution is impaired and these events are therefore likely determined by an earlier step of CO maturation . Given the absence of an overt meiotic phenotype of YEN1/GEN1 in budding yeast and C . elegans we wished to investigate if C . elegans GEN-1 might act redundantly with other nucleases in meiosis . A reduction in viability and a high incidence of male ( him ) phenotype , associated with X-chromosome non-disjunction , can be indicative of a meiotic defect . While the progeny hatch-rate of gen-1 ( 99 . 1%±0 . 4% ) was similar to wild-type ( 99 . 7%±0 . 2 ) , a slight reduction was observed for xpf-1 ( 85%±2 . 7% ) , mus-81 ( 84%±5 . 1% ) , and slx-1 ( 83%±7 . 2% ) single mutants ( Figure 1A ) . him-6 and slx-4 mutants showed 43%±1 . 7% and 14 . 5%±1 . 2% viability respectively , in accordance with previous reports ( Figure 1A ) [21] , [42] . Combining gen-1 with any of these mutants , that were extensively outcrossed to N2 wild-type , did not result in a significant reduction in progeny viability ( Figure 1A ) . In contrast , viability was significantly reduced to ∼15–20% in [mus-81; xpf-1] , [slx-1; xpf-1] as well as in [mus-81; him-6] and [slx-1; him-6] double mutants ( P<0 . 01 in all cases ) ( Figure 1B ) . These double mutants as well as any other compound mutants with reduced viability were maintained as balanced lines and phenotypes were analysed in the first homozygous generation ( see Materials and Methods ) . Double mutants of slx-1 or mus-81 with a second him-6 allele resulted in a similar phenotype , as did [mus-81 ercc-1] or [slx-1 ercc-1] double mutants ( data not shown ) . Ercc1 forms a heterodimer with Xpf1 from yeast to human [55] . In contrast , progeny survival of [mus-81 slx-1] and [xpf-1; him-6] was not reduced compared to the respective single mutants ( Figure 1B ) . Analysing a [mus-81 slx-1; xpf-1; him-6] quadruple mutant revealed a reduction in viability similar to that observed in the double mutants ( Figure 1B ) . In summary , our genetic data indicate that these genes might act in two redundant pathways for viability: one requiring XPF-1 and HIM-6 the other requiring SLX-1 and MUS-81 . We also note that the reduction of viability observed in [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants equals the reduced viability observed in slx-4 mutants ( Figure 1A , 1B ) . In addition , the reduced viability of slx-4 is not enhanced when slx-4 is combined with mus-81 , slx-1 or xpf-1 ( Figure 1C ) . As previously reported [slx-4; him-6] double mutants showed 0% survival [42] , a rate which contrasts with the ∼15–20% hatch rate observed in the aforementioned double mutants and the [mus-81 slx-1; xpf-1; him-6] quadruple mutant ( Figure 1B , 1C ) . In summary , these results suggest that the XPF-1-HIM-6 pathway as well as the SLX-1-MUS-81 pathway both require the function of SLX-4 ( Figure 1D ) . This finding is consistent with recent observations identifying Slx4 as a scaffold protein for Mus81 , Slx1 and Xpf1 in C . elegans and mammalian cells [42]–[48] . The finding that the [slx-4 him-6] double mutant is 100% inviable , while the [mus-81 slx-1; xpf-1; him-6] quadruple mutant shows 15–20% viability indicates that SLX-4 has additional functions to those conferred by its interaction partners SLX-1 , MUS-81 and XPF-1 ( Figure 1D ) . Errors in meiotic chromosome segregation can originate from defects in early meiotic events , such as chromosome axis establishment , homologous chromosome pairing and synapsis . Such events could be defective in our double mutants , accounting for the loss of viability . In order to investigate axis morphogenesis , we analysed the localization of HTP-3 , a component of the C . elegans axial element [56] . Axial elements coordinate homologous pairing and synapsis , as well as homologous recombination . We found that overall chromosome morphology , as well as HTP-3 localization occurred normally during both pachytene and diplotene in all double mutants analysed . HTP-3 was found along the length of parallel DAPI tracks in pachytene ( Figure 2A ) and associated with chromatin in diplotene ( data not shown ) , a stage in which homologues start to desynapse . To analyse synapsis we immuno-stained for SYP-1 , a component of the synaptonemal complex ( SC ) central region [57] . As is the case for HTP-3 , SYP-1 localization in all double mutants was indistinguishable from wild-type during pachytene ( Figure 2B ) . To address chromosome pairing , we used FISH probes to detect the 5S ribosomal DNA locus on chromosome V . Two immuno-fluorescence signals were detected in close proximity to each other , colocalizing with the parallel DAPI-stained tracks on each pachytene nucleus , suggesting that homologue chromosome pairing is unperturbed in all double mutants analysed ( Figure 2C ) . Thus , it appears that the reduced viability observed in [mus-81; xpf-1] , [slx-1; xpf-1] as well as in [mus-81; him-6] and [slx-1; him-6] double mutants is not due to a defect in homologous pairing , chromosome axes or synaptonemal complex establishment . To assess if the synthetic phenotypes we observed were due to a defect in DNA repair processes , we analysed meiotic chromosomes in diakinesis . The morphology and number of diakinesis chromosomes can serve as a readout of meiotic recombination defects [58] . During diakinesis , homologous chromosomes pair and restructure forming bivalents . These bivalents can be observed as six DAPI-stained bodies in wild-type maturing oocytes . Defects in meiotic recombination can result in a failure to stably connect homologous chromosomes , which becomes apparent as univalents at diakinesis ( 12 when physical linkages between all six homologue pairs fail to form ) . In wild-type we observed six bivalents in the last two oocytes ( −1 and −2 ) prior to fertilisation ( Figure 3A , Figure 4B , Video S1 ) . In contrast 12 univalents were apparent in spo-11 mutants ( Figure 3A , Video S7 ) . Consistent with the previously described him ( high incidence of males through X chromosome non-disjunction ) phenotype for xpf-1 and him-6 [21] , [42] , univalents and bivalents were observed in these mutants ( Figure 3A , blue arrows , data not shown ) . The number of univalents was higher in him-6 consistent with the stronger him phenotype in this mutant ( Figure 3C , Table 1 , Table S2 ) . Analysis of slx-4 , as well as [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants revealed a distinct phenotype . Many chromatin masses looked like univalents but in contrast to spo-11 , pairs of ‘univalents’ were found associated with each other ( Figure 3A , red arrows ) . Importantly , by analysing series of Z-stacks , we found that chromatin bridges linked those pairs . This analysis clearly documented that ‘univalent pairs’ which we refer here after as dissociated bivalents , were connected in slx-4 , [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants ( Videos S2 , S3 , S4 , S5 , S6 ) . A careful examination of these dissociated bivalents in [mus-81; xpf-1] mutants using a FISH probe against the 5S ribosomal RNA locus revealed that the DNA linkages indeed connected two homologous chromosomes ( Figure 3B ) . Scanning through multiple Z-stacks for each genotype we estimate that the average number of dissociated bivalents per oocyte was 3 . 82 in [mus-81; xpf-1] , 2 . 35 in [slx-1; xpf-1] , 1 . 42 in [mus-81; him-6] and 1 . 57 in [slx-1; him-6] double mutants ( Figure 3C , Table S2 ) . None or low levels of dissociated bivalents were observed in wild-type and single mutant worms ( Figure 3C , Table S2 ) . We note that both [slx-1; him-6] and [mus-81; him-6] have fewer dissociated bivalents than [mus-81; xpf-1] and [slx-1; xpf-1] . Nevertheless , the increased incidence of these structures in [slx-1; him-6] and [mus-81; him-6] compared to him-6 is statistically significant ( P<0 . 01 in both cases ) ( Table S2 ) . The lower incidence of dissociated bivalents in [slx-1; him-6] and [mus-81; him-6] worms is likely due to the overall lower number of homologues that undergo meiotic recombination in him-6 backgrounds as previously reported [20] , ( Figure 3C ) . This is consistent with our observation that the number of univalents in him-6 single mutant and in [slx-1; him-6] and [mus-81; him-6] double mutants is comparable ( Figure 3C , Table S2 ) . In contrast , [xpf-1; him-6] as well as [mus-81 slx-1] mutants did not show increased numbers of dissociated bivalents further supporting our prior genetic analysis suggesting that XPF-1 and HIM-6 , as well as MUS-81 and SLX-1 might act in two redundant pathways to process joint molecules linking homologous chromosomes ( Figure 1B , 3C , Table S2 ) . To better visualize the linkages we also analysed diakinesis chromosomes by super-resolution structured illumination microscopy ( SIM ) . Individual chromosomes could be observed from different angles , allowing the generation of Z-stacks aligned with the orientation of individual chromosomes . This analysis confirmed that dissociated bivalents were connected by DNA bridges ( Figure 3D , 3E and Videos S8 , S9 , S10 , S11 , S12 , S13 ) . The analysis also showed that one to three such linkages occurred within each dissociated bivalent . Given that chromosomes often overlap in cytological preparations and that some bridges were at the limit of resolution , the number of linkages could not be assessed easily ( Figure 3D ) . To further investigate chromosome morphology at diakinesis , we used HTP-3 antibodies to stain for chromosomal axes and therefore further assess bivalent maturation . In wild-type and all single mutants we predominantly observed a cruciform HTP-3 pattern indicative of chiasma formation ( Figure 4 , upper left panels ) . In addition , HTP-3 stained as single tracks on him-6 univalent chromosomes . In contrast , in [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants the cruciform HTP-3 staining pattern was dramatically reduced and instead HTP-3 was detected along the single axes of dissociated bivalents ( Figure 4 , lower panels ) . This phenotype was even more prominent when analysed by SIM microscopy ( Figure 4 , upper right panel ) . Thus , where chromosomes are not connected by chiasmata , DNA linkages appear to provide the only physical connection . Mus81 , Slx1 , Xpf1 and BLM homologues have been implicated in DNA repair in mitotically dividing cells in many organisms . Thus , the chromatin linkages we observed could represent unresolved DNA repair intermediates , possibly carried over from mitotic cell divisions . Alternatively , these linkages might originate from SPO-11 induced double-strand breaks , and represent unresolved meiotic RIs . To distinguish between these possibilities we combined [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants with spo-11 to generate the respective triple mutants . Analysis of all triple mutants ( except for [mus-81; him-6 spo-11] ( see below ) ) indicated that chromatin linkages disappeared , and univalents could be observed , as was the case in spo-11 single mutants ( Figure 5A ) . We thus conclude that the linkages likely represent SPO-11-induced RIs . It has been shown that the loss of bivalent formation in spo-11 mutants can be rescued by IR-induced DSBs [59] . To further establish that the linkages we observed represent unrepaired meiotic RIs , we irradiated [mus-81; xpf-1; spo-11] , [mus-81; him-6 spo-11] and [slx-1; him-6 spo-11] mutants as well as [mus-81; spo-11] , [him-6 spo-11] and [slx-1; spo-11] double mutants with 20 Gy of ionizing radiation . While all un-irradiated strains that contain spo-11 showed univalents ( except for [mus-81; him-6 spo-11] , see below ) , irradiation restored bivalent formation in spo-11 as well as [mus-81; spo-11] , [slx-1; spo-11]; and [him-6 spo-11] double mutants ( Figure 5B ) . In contrast , in [mus-81; xpf-1; spo-11] , [slx-1; him-6 spo-11] and [mus-81; him-6 spo-11] triple mutants dissociated bivalents arose at a high frequency ( Figure 5B ) . In summary , our data strongly suggest that the linkages detectable in the double mutant backgrounds result from unresolved meiotic RIs . We note that [mus-81; him-6 spo-11] triple mutants ( not treated with radiation ) showed a mixture of bivalents , dissociated bivalents and univalents , and occasionally also structures that looked like chromosome fusions . We speculate that these structures result from excessive DSBs occurring in pre-meiotic S-phase in [mus-81; him-6] double mutants that bypass the requirement for SPO-11 . The depletion of Mus81 in cell lines derived from BLM patients leads to excessive genome instability is consistent with our results [60] . In C . elegans only one of several SPO-11 generated DSBs engages in CO formation between homologues [6] , [59] , [61] , [62] . Inter-homologue RIs can also be resolved as gene conversion events . Defects in the processing of the respective intermediates might lead to the dissociated bivalent phenotype we observe . In addition it is also known that sister chromatids can be used to repair SPO-11 induced DSBs [63] , [64] . Thus , to further establish if the linkages we observed indeed occur between two homologues , we examined the dynamics of meiotic chromosomes through the two meiotic divisions and also the first ensuing zygotic mitotic cell cycle . We reasoned that anaphase of meiosis I might be affected if a DNA linkage remains present between two homologues . To assess meiotic chromosome dynamics by live imaging we used an integrated Histone H2B::GFP fusion ( his-11::GFP ) . Overall , we observed that single mutants behaved like wild-type ( Videos S14 , S15 , S16 , S17 , S18 , Figure 6A , B ) : during anaphase I homologous chromosomes separate . One set of chromosomes decondenses and is extruded as the first polar body . The remaining sister chromatids separate from each other during anaphase II . One set of sister chromatids is extruded as the second polar body , while the other set decondenses and undergoes DNA replication . Maternal and paternal pronuclei then meet at the centre of the zygote and fuse before the first zygotic division ensues . In contrast to wild-type and the single mutants , in [mus-81; xpf-1] , [slx-1; xpf-1] and [mus-81; him-6] double mutants anaphase I chromosomes did not readily separate ( Videos S19 , S20 , S21 , Figure 6A , B ) . It appeared as if one set of chromosomes dragged the other set of chromosomes , which decondensed , and formed the first polar body . Chromatin bridges were not always visible , likely because they were stretched and/or imaging during time-lapse microscopy was focused on a single plane . However , the first polar body remained in close vicinity to chromosomes undergoing the second meiotic division ( Figure 6A , B ) . Only one set of anaphase II chromosomes eventually separated from the chromatin mass of the polar body . These chromosomes decondensed and engaged in the first zygotic division ( Videos S19 , S20 , S21 ) . During this division a modest level of chromatin bridge formation was visible . Taken together , our results suggest a defect in the segregation of homologous chromosomes during the first meiotic division , consistent with defects occurring in the resolution of inter-homologue recombination intermediates . We next wished to directly test if meiotic recombination was reduced in [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] double mutants as predicted from our genetic and cytological data . CO frequency and distribution can be investigated by meiotic recombination mapping [10] , [65] , [66] . This procedure is facilitated by using multiple SNP markers along an entire chromosome that differ between the wild-type N2 ‘Bristol’ strain and the polymorphic CB4856 ‘Hawaii’ strain . We therefore generated the respective single and double mutants with chromosome V being heterozygous for Hawaii and N2 . To score for recombination frequency and distribution we employed five single nucleotide polymorphisms ( snip-SNPs ) , detectable by a change in a restriction enzyme recognition site , which together cover 92% of chromosome V ( see Material and Methods , Figure 7A ) . slx-1 , mus-81 and xpf-1 single mutants did not show an altered CO recombination frequency as compared to wild-type ( Figure 7A ) . Moreover , him-6 showed a reduced recombination rate as previously reported [21] ( Figure 7A ) . Consistent with our idea of there being two redundant pathways for resolution comprising XPF-1-HIM-6 and MUS-81-SLX-1 , we observed markedly reduced recombination frequencies in [mus-81; xpf-1] and [slx-1; xpf-1] double mutants when compared to the respective single mutants ( P<0 . 05 ) ( Figure 7A ) . Moreover , a small , but consistent number of double COs was detectable indicating that CO interference might be slightly impaired in double mutants ( Figure 7A ) . Analysis of [mus-81 him-6] and [slx-1; him-6] double mutants did not reveal a statistically significant reduction in recombination frequency when compared to him-6 . It is possible that a further reduction of him-6 CO frequency by mus-81 and slx-1 is masked by the high frequency of chromosome V being present as univalents ( Figure 3C , [30] ) . In summary , we observe a reduced frequency of CO recombination in [mus-81; xpf-1] and [slx-1; xpf-1] to a level comparable to the reduction described for slx-4 [42] . Consistent with the frequency of the dissociated bivalent phenotype , as well as with the survival rates of the double mutants , we postulate that the reduction but not abolishment of CO formation indicates a reduced frequency in meiotic RIs resolution , likely HJs . The localisation of MSH-5 , ZHP-3 , and COSA-1 into distinct foci is interdependent and has been correlated with CO designation [61] . In wild-type germlines , ZHP-3 staining initially occurs along chromosome axes and in early diplotene congresses into six foci , one for each pair of homologues [67] , [68] . In all single and double mutants analysed ∼six distinct foci eventually formed ( Figure 7B , C ) . However , we observed a delay in the retraction of ZHP-3 from a thread-like pattern colocalizing with SYP-1 ( green and red lines respectively , Videos S22 , S23 , S24 ) to six robust foci in slx-1 , xpf-1 and him-6 single mutants ( data not shown ) as well as in double mutant germlines ( Figure 7C , Videos S22 , S3 , S24 ) . Similar observations had been previously reported for the slx-4 mutant [42] . This analysis together with the reduced CO frequency observed in slx-4 [42] , [mus-81; xpf-1] and [slx-1; xpf-1] further substantiates the possibility that ZHP-3 marks a stage related to a CO precursor as opposed to a mature CO . In C . elegans the establishment of an inter-homologue CO is thought to trigger extensive structural reorganisation of chromosomes during the late stages of meiotic prophase [69]–[71] . Therefore , we wished to address if this CO-induced chromosome restructuring depends on CO initiation or completion . In diplotene the SC asymmetrically disassembles along the paired homologues and SYP-1 localization becomes restricted to the region between the CO and the nearest chromosome end . At this stage SYP-1 can be detected as six robust threads ( one for each homologue-pair ) ( see also Figure 8A ) . We clearly detected SYP-1 retracting to six robust threads after de-synapsis in late pachytene/diplotene in [mus-81; xpf-1] and [slx-1; xpf-1] double mutants ( Figure 8A ) . As expected in the absence of COs ( in spo-11 mutants ) , SYP-1 was detected dispersed along entire chromosomes ( Figure 8A ) . SYP-1 localization was variable in him-6 mutant backgrounds , consistent with the occurrence of bivalents and univalents in these strains ( data not shown ) . During diakinesis , the chromosomal region in which SYP-1 is maintained matures into the short arm of the bivalent . On the short arm cohesion will be lost at the onset of anaphase I . SYP-1 localization is reciprocal to the pattern of the HTP-1/2 chromosome axis components [70] , [72] ( Figure 8B ) . HTP-1/2 becomes restricted to the long arm of the bivalent which will maintain cohesion during anaphase I . The differentiation of the CO distal and CO proximal arm is generally thought to require CO completion . We could detect SYP-1 as six robust threads in the mid-bivalent region and HTP-1/2 reciprocally localizing as a linear thread along the long-arm region of the bivalent in diakinesis oocytes of all single mutants . In [mus-81; xpf-1] , [slx-1; xpf-1] , [slx-1; him-6] and [mus-81; him-6] SYP-1 and HTP-1/2 distribution was similar to wild-type ( see below ) ( Figure 8C ) . These results indicate that CO initiation but not completion is likely to be required for the timely establishment of this asymmetrical localization . Our combined results suggest that XPF-1 and HIM-6 , as well as SLX-1 and MUS-81 are each likely to act in a redundant pathway to resolve meiotic HJs . Both “resolvase activities” require the SLX-4 scaffold protein . Our hypothesis is supported by genetic and cytological evidence . Overall , [mus-81; xpf-1] , [slx-1; xpf-1] , [mus-81; him-6] and [slx-1; him-6] but not [xpf-1; him-6] and [mus-81 slx-1] double mutants show a similar reduction in viability as observed for slx-4 and [mus-81 slx-1; xpf-1; him-6] quadruple mutants . In slx-4 as well as in the double mutants with reduced viability , a large proportion of chromosomes fail to maintain a bivalent structure , and dissociated bivalents linked by chromatin bridges visible by high-resolution microscopy become apparent . Chromatin linkages have also been identified during the first mitotic division in the embryo and in diakinesis nuclei of slx-4 mutants [42] . However , the prevalence of this phenotype in meiotic cells was likely underestimated . Importantly , we clearly show that these linkages largely depend on SPO-11 , consistent with the hypothesis that XPF-1 and HIM-6 as well as SLX-1 and MUS-81 are required to resolve meiotic SPO-11 induced RIs . Using SIM microscopy we found that in many cases more than one chromatin linkage can be found between dissociated bivalents . Thus , the number of linkages between each dissociated bivalent is higher than the number of CO events indicating that the resolution of HJs leading to gene conversion and CO recombination might be affected . Our results predict that XPF-1 in conjunction with HIM-6 as well as MUS-81 in conjunction with SLX-1 might act as two distinct resolvases ( Figure 9 ) . The notion that XPF-1 and MUS-81 act in two different pathways is fully consistent with the parallel reports by O' Neil and Saito et al . [48] , [73] . Based on the known activities of these proteins in vitro we speculate that these meiotic unresolved RIs are likely HJs . The study of O' Neil et al . further corroborates our prediction that unresolved HJs indeed accumulate in these double mutant backgrounds . By injecting an N-terminal fragment of human GEN1 , the authors could rescue the dissociated bivalent phenotype in [mus-81; xpf-1] double mutants [73] . GEN1 symmetrically cleaves HJs , but also has some activity on FLAP structures in vitro [34] . While we report ∼15%–20% viability for [mus-81; him-6] and [slx-1; him-6] double mutants , these mutant combinations lead to 0% viability in Saito et al and O'Neil et al . [48] , [73] . To maintain double mutant lines both studies used the nT1 balancer . We similarly observed 100% lethality when deriving double mutant homozygous lines from nT1 balanced him-6 ( data not shown ) , whereas viability is only reduced to ∼15% viability when the hT2 balancer is used . We think that the ∼15% viability is the genuine double mutant phenotype , as we were able to propagate [mus-81; him-6] and [slx-1; him-6] double homozygous mutants derived from [mus-81/hT2 him-6] and [slx-1/hT2 him-6] for several generations . Furthermore , the same phenotype was observed with a second allele of him-6 . How do our genetic data , which do not exclude the possibility of further proteins acting in the XPF-1-HIM-6 and the SLX-1-MUS-81 pathways , fit with the known activities of the respective enzymes ? The known activities of Mus81 and Slx1 suggest a way how those two enzymes might act in conjunction to process HJs ( Figure 9 ) . Nicked HJs are a preferred substrate of Mus81 . In vitro , the activity of Mus81 towards these structures by far exceeds its activity towards HJs [29] . It appears likely that Slx1 could generate such nicks . Slx1 has been shown to cleave a variety of substrates including HJs . Thus it is highly plausible that C . elegans SLX-1 might exert such a nickase activity at HJs [29] , [47] . Given that SLX-1 and MUS-81 both bind to SLX-4 the activities of those two enzymes could be coordinated to achieve the orderly processing of HJs . Such a mechanism would be akin to classical resolvases which generally act as dimers , and which function by first conferring a nick immediately followed by a counter-nick , resulting in a complete symmetrical cleavage of a HJ [74] ( Figure 9 ) . Biochemical studies with human SLX1-SLX4 and MUS81-EME1 indeed indicate that the two nucleases act cooperatively to promote nicking and counter-nicking reactions that result in HJ resolution within the lifetime of the protein-DNA complex ( HDM Wyatt , T Sarbajna , J Matos and SC West , personal communication ) . S . cerevisiae and human Rad1/Xpf1 have been shown to cleave splayed arm , bubble and 3′ flap structures in vitro consistent with Xpf1's function in nucleotide excision repair and DNA single-strand annealing ( reviewed in [29] ) . Symmetrical cleavage of a HJ substrate by Rad1 has been reported , but the interpretation of the results was disputed [75] , [76] . Rad1 mutants do not have a meiotic phenotype and the ‘HJ cleavage activity’ was only observed on a ‘mobile HJ substrate’ that contains a 12 bp core of homology ( X12 substrate ) . Such a composition allows migration of the actual junction along the core , leading to transient single-stranded structures that resemble bubble structures observed during nucleotide excision repair . Thus under certain conditions Xpf1 might introduce nicks on flexible HJ junctions without acting as a canonically resolvase that symmetrically cuts HJs such that the resulting products are readily re-ligatable . Indeed Xpf1 is discussed as a HJ resolvase/HJ processing enzyme in the fruit fly where the respective mei-9 mutation shows a dramatically reduced level of meiotic COs [52] . Interestingly , the extent of meiotic gene conversion is not reduced in this mutant . Xpf1 might act as a HJ processing enzyme . Intriguingly , an even stronger meiotic recombination defect occurs in fly mus312/slx4 mutants , and it has been argued that MUS312 besides MEI-9 might also need SLX1 to fully process HJs [43] , [77] , [78] . If C . elegans XPF-1 were to act as a HJ nicking enzyme , it appears possible that the HIM-6 helicase might help to unwind thermodynamically unstable HJs occurring in the context of entire chromosomes ( Figure 9 ) . It is noteworthy that electron-microscopic pictures of HJs derived from S . pombe meiotic cells revealed HJs that were open at their centre [25] . Thus , HIM-6 could at least transiently increase the single-strandedness of thermodynamically flexible HJ structures , thus facilitating HJs being nicked by XPF-1 . At present we cannot exclude the possibility that XPF-1 and HIM-6 might act at an earlier step during meiotic recombination , acting on ‘joint molecules’ occurring prior to the formation of HJs . We know very little about HIM-6 function during C . elegans meiosis , but it is established that the rate of meiotic CO recombination is reduced in him-6 mutants albeit the mechanism is not known [20] . The S . cerevisiae and human HIM-6 homologs Sgs1/BLM are thought to be involved in D-loop disassembly [13] , [79]–[81] . Thus , the absence of HIM-6 could lead to an increased number of joint molecules , the processing of which might require MUS-81 or SLX-1 . CO recombination is reduced but not eliminated in [mus-81; xpf-1] and [slx-1; xpf-1] double mutants , while a reduction beyond the level observed in him-6 mutants cannot be detected in [mus-81; him-6] and [slx-1; him-6] . As Saito et al . [48] , we did not detect reduced overall CO frequencies in slx-1 , mus-81 and xpf-1 when analysing chromosome V . It is possible that the reduced CO frequency on chromosome III reported by O'Neil et al . [73] , relates to chromosome-specific differences . In addition the recombination assays employed by O'Neil et al . , reflect recombination rates in both male and female germ cells , while we measured recombination rates in the female germ line . We think that these findings are consistent with our cytological observations . More dissociated bivalents are found in [mus-81; xpf-1] and [slx-1; xpf-1] while the formation of an equal number of such structures is prevented in [mus-81; him-6] and [slx-1; him-6] by the reduced rate of recombination in him-6 which results in a reduced number of bivalents formed . Irrespective , it is evident that further factors capable of resolving HJs must exist in the C . elegans germline . In principle there are two ways as to how such residual resolution might occur: 1 ) Redundant HJ resolving enzymes might act at the same time as SLX-4 and its associated nucleases before the onset of anaphase I . Consistent with an ‘early’ function of those redundant resolvase activities , wild-type bivalents are still present in slx-4 mutants as well as in all double mutants . In budding yeast mlh3 , sgs1 , mms4 ( mus81 ) , yen1 , slx1 quintuple mutants show a complete absence of CO products where recombination hotspot systems are employed [14] , [54] . Thus EXO-1 , the MutL complex and GEN-1 as well as other nucleases encoded in the C . elegans genome are possible candidates . 2 ) HJs missed by the SLX-4 associated nucleases might be processed by a backup mechanism occurring during anaphase I , or even in the second meiotic division . Such a mechanism is supported by our finding that anaphase I chromosomes appear to be linked , and only in the second meiotic division chromosomes finally seem to separate from each other . A precedent for such a mechanism is the budding yeast Yen1 resolvase [40] . This resolvase , which only acts at late stages of meiosis rescues the meiotic chromosome segregation defects associated with mus81 . Although C . elegans GEN-1 is expressed in late stage oocytes ( AG and Bin Wang , unpublished ) it does not appear to affect meiotic HJ resolution , even when gen-1 and slx-4 deletions are combined . Thus other nucleases might act to ensure complete HJ resolution during anaphase I and during the subsequent second meiotic division . However , such ‘backup mechanisms’ might be rather un-physiological as they only take place in the absence of various nucleases and might fail to accurately process HJs , thus leading to a loss of genetic information . Indeed , the progeny of [slx-1; him-6] , [mus-81; him-6] , [mus-81; xpf-1] and [slx-1; xpf-1] mutants have a fluctuating viability in subsequent generations ( BM and AG , unpublished ) . In addition , it appears possible that HJs could be torn apart by the force exerted by the spindle in the first and second meiotic divisions . The resulting DSBs would need to be repaired , likely by error-prone mechanisms . Our quantitative analysis of [mus-81; xpf-1] and [slx-1; xpf-1] diakinesis nuclei reveals a >50% penetrance of the dissociated bivalent phenotype . If those ∼six chromosome pairs were not linked , a much higher rate of chromosome non-disjunction would be predicted . Thus , a higher incidence of males , a phenotype resulting from meiotic X chromosome non-disjunction would occur . In our hands the him phenotype observed in [mus-81; xpf-1] , [slx-1; xpf-1] , [slx-1; him-6] and [mus-81; him-6] double mutants is not severely enhanced compared to the phenotype observed in the respective single mutants . Chiasmata are normally needed to counteract spindle tension to ensure faithful meiotic chromosome segregation . The chromatin linkages we observed might therefore partially bypass the requirement of a chiasma to counteract tension thus explaining the relatively high rate of correct X-chromosome segregation . During diplotene and diakinesis chromosomes become highly condensed and extensive remodelling occurs to form characteristic cruciform bivalents . Chiasmata are important for the differentiation of chromosomes into short and long arms relative to the CO site [71] . The area between the CO site and the closest chromosome end differentiates into a short arm , where sister chromatid cohesion will be lost in anaphase I in order to allow for the segregation of homologous chromosomes . Cohesion loss at the onset of anaphase is mediated by AIR-2 , and the direct AIR-2 dependent phosphorylation of REC-8 [82] , [83] . Conversely , the long arm relative to the CO site maintains cohesion during the first meiotic division [71] . This asymmetric differentiation can be visualized by the reciprocal localization of various proteins . Synapsis proteins SYP-1 , 2 , 3 and 4 become restricted to the short arm beginning from early diplotene , while HTP-1/2 axis components and LAB-1 localize to the long arm [69] , [70] , [72] , [84]–[86] . How this asymmetric differentiation is regulated remains enigmatic . The high penetrance of the dissociated bivalent phenotype , which we interpret as a failure in CO resolution allowed us to address if this asymmetry and chiasma formation depend on CO initiation or CO completion . It is clear that SPO-11 dependent DSBs are required to form chiasmata . We show that the chiasmata do not form on dissociated bivalents , thus CO completion is required for chiasma formation . In contrast , CO designation marked by six distinct ZHP-3 foci , one for each CO designated site , still occurs in slx-4 and [mus-81; xpf-1] , [slx-1; xpf-1] , [slx-1; him-6] and [mus-81; him-6] double mutants . Interestingly , ZHP-3 foci formation is delayed in the double mutants and importantly also in most single mutants we analysed ( Figure 7 C , Videos S23 , S24 and data not shown ) . Thus , SLX-1 , XPF-1 and MUS-81 are likely to be required for the timely specification of CO designated sites . The details of these dependencies will need to be investigated in future studies . Importantly , our data suggest that CO initiation at CO designated DSB sites but not completion might be sufficient to establish the correct bivalent subdomains of meiotic chromosomes . This is evident by the predominant SYP-1 localization to the short arm of chromosomes starting from early diplotene as it occurs in wild-type . Furthermore , the reciprocal localization of SYP-1 and HTP-1/2 still occurs when linked chromosomes that lack a chiasma are analysed . We note that a faint SYP-1 signal could be occasionally observed co-localising with HTP-1/2 on the long arm in [mus-81; him-6] and [mus-81; xpf-1] , double mutants ( data not shown ) . This result might suggest defects in the correct SC disassembly consistent with O'Neil et al . [73] . In future work it will be important to address how CO initiation , CO designation and the establishment of chromosomal asymmetry is regulated . It is tempting to speculate why meiotic HJ resolution might not take advantage of symmetrically cleaving HJ resolution enzymes . Canonical HJ resolvases , which are highly active enzymes , would in principle lead to CO and gene conversion products with equal frequency . The production of CO intermediates during the repair of DSBs in mitotic cells would result in the loss of heterozygosity . With hindsight it is thus not surprising that mutants solely defective in the GEN1 HJ resolvase have no overt DSB repair defects in most organisms . In meiosis CO recombination is highly regulated and importantly restricted to a small subset of CO-designated DSB sites . Thus to maintain meiotic CO homeostasis evolution might have chosen and adapted multiple conserved nucleases to more efficiently and robustly ensure orderly meiotic CO recombination . It will be interesting to uncover further redundant nucleases required for CO recombination and to study their functional interplay . Strains were grown at 20°C under standard conditions [87] unless indicated otherwise . N2 Bristol was used as the wild-type strain . CB4856 Hawaii was used to generate strains for CO recombination frequency analysis . Mutant strains used in this study are listed in Table S1 . The following rearrangements and balancers were used [88]: LG I: hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48]; LG III: dpy-17 ( e164 ) unc-32 ( e189 ) /qC1[dpy-19 ( e1259 ) glp-1 ( q339 ) ]; LG IV: nT1[qIs51] , nT1[unc- ? ( n754 ) let- ? qIs50] and mIS11 ( myo2::GFP insertion near dpy-20 ) The slx-1 ( tm2644 ) , ercc-1 ( tm1981 ) , mus-81 ( tm1937 ) and xpf-1 ( tm2842 ) mutants were generated and kindly provided by Shohei Mitani of the National Bioresource Project for the Nematode , Japan . All mutants are null alleles and eliminate a sizable proportion of the respective open reading frames . Details are described at the National Bioresource Project for the Nematode and on www . wormbase . org . All mutants were outcrossed for a minimum of four times to the wild-type strain to eliminate background mutations . The TG2512 gtIs2512[Ppie-1::his-11::GFP unc-119+] strain was generating by biolistic bombardment of pAZ132 of unc-119 ( ed3 ) mutants [89] . For immunostaining of germlines , 8 to 10 ( 24 h post L4 stage ) adults were dissected per slide . Germlines were isolated in 8 µl of 1× EBT ( 250 mM HEPES pH 7 . 4 , 1 . 18 M NaCl , 480 mM KCl , 20 M EDTA , 5 mM EGTA , 0 . 1% Tween 20 , 20 mM sodium azide ) . An equal volume of 2% formaldehyde in EBT was added to the slide carefully pipetting to allow for homogenization . Fixation was done for 5 minutes at room temperature , followed by immersion in liquid nitrogen . Coverslips were quickly removed , and post fixation was done in −20°C methanol for 1 minute , followed by permeabilization by washing 3×5 minutes in PBST ( 1× PBS , 0 . 1% Tween ) at RT . Blocking was performed in PBST supplemented with 3% BSA ( PBSTB ) incubated for 30 min at room temperature . Primary antibodies were diluted in PBSTB and covered with a parafilm coverslip , followed by over-night incubation at 4°C in a dark humid chamber . Slides were then washed 3×10 min in PBST . Secondary antibody incubation was done at room temperature for 2 hours in PBSTB supplemented with 2 µg/µL DAPI . After washing 3×10 min in PBST , the samples were mounted in Vectashield mounting medium ( Vector Laboratories , Inc . ) and sealed . Primary and secondary antibodies were used at the indicated dilutions: rabbit anti-HTP-3 ( 1∶500 ) [90]; guinea pig anti-ZHP-3 ( 1∶250 ) [67]; guinea pig anti-SYP-1 ( 1∶500 ) ( gift from Kentaro Nabeshima ) ; rabbit anti-HTP-1 ( 1∶200 ) ( Martinez-Perez et al . 2008 ) . Cy3 conjugated secondary antibodies ( 1∶250 ) ( Jackson Immunochemicals ) and Alexa 568 labelled donkey anti-rabbit ( 1∶750 ) ( Molecular Probes ) . For DAPI staining the final concentration used was 2 µg/µL . PCR-amplified 5S rDNA was used as a probe for the right end of chromosome V . The 5S rDNA was labelled by PCR with cy3-dUTP ( GE healthcare ) . Gonads were dissected as described for immunostaining , fixed in 7 . 4% formaldehyde , freeze cracked in liquid nitrogen and then fixed in methanol , methanol: acetone , acetone for 5 min each . FISH was performed as described previously [84] , except for doing washes with PBST , and NaSCN incubations at 78°C for 10 min . Preparations were mounted in Vectashield/DAPI . Embryos were dissected in isotonic growth medium for blastomeres containing 35% bovine FCS ( Shelton and Bowerman , 1996 ) . Before use , bovine FCS ( heat treated for 30 min at 56°C; Invitrogen ) was added . Embryos were mounted on 2% agarose pads . Vaseline patches on the slide were used to reduce the pressure of the coverslip on the embryo . Images were captured every 10 or 30 seconds using a widefield DeltaVision microscope . Exposure time was 250 milliseconds and binning used was 2×2 . Microscopy images were acquired with a Delta Vision Image restoration system ( Applied Precision ) . Raw data obtained were analysed and deconvolved using softWoRx Suite and softWoRx Explorer software ( AppliedPrecision , Issaquah , WA , USA ) . For SIM microscopy established protocols were followed [91] , [92] . Images were acquired using a UPlanSApochromat 100× 1 . 4NA , oil immersion objective lens ( Olympus , Center Valley , PA ) and back-illuminated Cascade II 512×512 electron-multiplying charge-coupled device ( EMCCD ) camera ( Photometrics , Tucson , AZ ) on the SIM version 3 system ( Applied Precision ) equipped with 405- , 488- , and 593-nm solid-state lasers . Samples were illuminated by a coherent scrambled laser light source that had passed through a diffraction grating to generate the structured illumination by interference of light orders in the image plane to create a 3D sinusoidal pattern , with lateral stripes approximately 0 . 2 µm apart . The pattern was shifted laterally through five phases and through three angular rotations of 60° for each Z-section , separated by 0 . 125 µm . Exposure times were typically between 100 and 200 ms , and the power of each laser was adjusted to achieve optimal intensities of between 2 , 000 and 4 , 000 counts in a raw image of 16-bit dynamic range , at the lowest possible laser power to minimize photo bleaching . Raw images were processed and reconstructed to reveal structures with greater resolution [93] implemented on SoftWorx , ver . 6 . 0 ( Applied Precision , Inc . ) . The channels were then aligned in x , y , and rotationally using predetermined shifts as measured using 100 nm TetraSpeck ( Invitrogen ) beads with the SoftWorx alignment tool ( Applied Precision , Inc . ) . non-GFP L4s were picked from balanced lines . Worms were irradiated with 20 Gy 20 h post L4 stage using a 137Cs source ( 2 . 14 Gy/min , IBL 437C , CIS Bio International ) . Adults were dissected and DAPI stained 24 h post IR as described previously [94] . Meiotic CO recombination frequencies were assayed essentially as described [42] , [65] , using five snip-SNPs on ChrV that differ between N2 Bristol and CB4856 Hawaii . Strains used to determine CO recombination assays were crossed into Hawaii to obtain mutant strains carrying ChrV homozygous for Hawaii DNA . Single and double mutant strains containing slx-1 and mus-81 were balanced with hT2 . GFP positive balanced mutant males with ChrV homozygous Hawaii were then crossed with hermaphrodites of identical genotype in the N2 Bristol background to obtain mutant strains heterozygous for Hawaii . Non-GFP homozygous mutant F1 cross-progeny hermaphrodites were then crossed with males of CB5584 , a myo-2::GFP expressing strain , which expresses high levels of green fluorescent protein in pharyngeal muscles , allowed to lay eggs for 24–48 h before removing them for genotype confirmation by PCR and DraI digest . 100–200 individual F1′ GFP-positive embryos and larvae were lysed and analysed for CO recombination by PCR and DraI digest . Statistical analysis of CO recombination frequencies was performed using two-tailed Fisher's exact test . Primers used: Chromosome V
Meiosis is a specialized cell division , where a single S-phase is followed by two rounds of cell divisions to ensure the production of haploid gametes . Meiotic crossover ( CO ) recombination is required for genetic diversity and for the proper segregation of chromosomes during the first meiotic division . In addition , in organisms with holocentric chromosomes COs are required for differentiating meiotic chromosomes into distinctly organized CO distal and CO proximal domains . Holliday junctions ( HJs ) are crucial intermediates during meiotic recombination , but we still know very little about how they are processed to ensure CO recombination , especially in animals . In this study we analyse the combined requirement of C . elegans nucleases and the conserved HIM-6/BLM helicase to regulate the processing of meiotic recombination intermediates . Based on genetic and cytological analysis we propose that HIM-6/BLM and the XPF-1 nuclease , as well as the SLX-1 and MUS-81 nucleases act in two redundant pathways to promote HJ resolution . Furthermore , we provide evidence that CO initiation but not CO resolution is likely important for the differentiation of meiotic chromosomes into CO distal and CO proximal domains .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genetics", "biology" ]
2013
Combinatorial Regulation of Meiotic Holliday Junction Resolution in C. elegans by HIM-6 (BLM) Helicase, SLX-4, and the SLX-1, MUS-81 and XPF-1 Nucleases
Malignant tumors shed DNA into the circulation . The transient half-life of circulating tumor DNA ( ctDNA ) may afford the opportunity to diagnose , monitor recurrence , and evaluate response to therapy solely through a non-invasive blood draw . However , detecting ctDNA against the normally occurring background of cell-free DNA derived from healthy cells has proven challenging , particularly in non-metastatic solid tumors . In this study , distinct differences in fragment length size between ctDNAs and normal cell-free DNA are defined . Human ctDNA in rat plasma derived from human glioblastoma multiforme stem-like cells in the rat brain and human hepatocellular carcinoma in the rat flank were found to have a shorter principal fragment length than the background rat cell-free DNA ( 134–144 bp vs . 167 bp , respectively ) . Subsequently , a similar shift in the fragment length of ctDNA in humans with melanoma and lung cancer was identified compared to healthy controls . Comparison of fragment lengths from cell-free DNA between a melanoma patient and healthy controls found that the BRAF V600E mutant allele occurred more commonly at a shorter fragment length than the fragment length of the wild-type allele ( 132–145 bp vs . 165 bp , respectively ) . Moreover , size-selecting for shorter cell-free DNA fragment lengths substantially increased the EGFR T790M mutant allele frequency in human lung cancer . These findings provide compelling evidence that experimental or bioinformatic isolation of a specific subset of fragment lengths from cell-free DNA may improve detection of ctDNA . Increased quantity of cell-free DNA in the circulation has been associated with malignant solid tumors [1] . Longitudinal studies have reported reductions in cell-free DNA quantity in response to therapy and elevations associated with recurrence suggesting quantification of cell-free DNA may be useful for monitoring disease status [2–4] . However , quantifying cell-free DNA as a marker of disease and its extent has been limited . The quantity of cell-free DNA has not correlated well with stage and histological subtype [5 , 6] . In addition , large inter-subject variations of cell-free DNA quantification have been described leading to overlap between malignant disease , benign tumors , and healthy controls [7 , 8] . Moreover , increased quantity of cell-free DNA is non-specific to cancer and has been associated with other conditions such as autoimmune disease and environmental exposures [9 , 10] . Finally , except in patients with advanced metastatic disease , tumor-derived cell-free DNA ( i . e . , circulating tumor DNA , ctDNA ) forms only a small minority of the cell-free DNA in circulation against a background of fragments mostly derived from normal cells . Therefore , the quantification of cell-free DNA alone is of little prognostic value . As an alternative , detecting specific variants or mutational hotspots in ctDNA may have important clinical implications in the shift towards personalized medicine for diagnosing and/or monitoring malignancies . In lung cancer , EGFR mutations in ctDNA have been associated with prognosis and utilized for determining therapy ( e . g . , activating mutations that confer sensitivity to tyrosine kinase inhibitors ) [11] . However , molecular ctDNA studies in a variety tumor types have largely focused on advanced or metastatic disease in which ctDNA is more readily detectable compared to localized disease [12] . Bettegowda et al . reported a substantial reduction in detectability of ctDNA in localized disease compared to metastatic tumors for breast , colon , pancreas , and gastroesophageal cancers [13] . Moreover , ctDNA from glioblastoma multiforme ( GBM ) , a primary brain tumor associated with neovascularization and disruption of the blood-brain barrier , was undetectable [13] . This latter finding supports the general perception that detection of ctDNA from non-metastatic solid tumors is particularly challenging since GBM does not metastasize beyond the central nervous system . Emerging approaches to improve detection of ctDNA include amplicon-based strategies in colorectal cancer [14] and integrated digital error suppression during deep sequencing in lung cancer [15] . While the latter methods seek to eliminate artifacts during sequencing to improve bioinformatic analytic sensitivity of mutant allele detection , the former techniques exploit apparent size differences between ctDNA and cell-free DNA . Specifically , previous amplicon-based studies have shown that ctDNA is highly fragmented and occurs most commonly at a size <100 bp , while normal cell-free DNA is proportionally more represented at a size >400 bp [16] . In this study , we initially sought to determine the feasibility of detecting ctDNA associated with GBM by utilizing a xenograft tumor model to exploit genomic species differences to separate ctDNA from the background host animal benign cell-free DNA . In so doing , we identified precise differences in fragment lengths between ctDNA and normal cell-free DNA , which were more narrow and more consistent than previously described [16 , 17] . In addition , we found strong evidence of a 10 bp periodicity in ctDNA that was less prominent in normal cell-free DNA . These observations led us to explore if similar findings were present in tumors outside the brain and subsequently translated to cell-free DNA samples obtained from cancer patients . Collectively , the results described herein demonstrate that the fractional selection of cell-free DNA with a specific size range that is 20–50 bp shorter than the size of normal healthy cell-free DNA may substantially enrich for ctDNA in human cancer . Established human GBM stem-like cell lines ( GBM4 and GBM8 ) [18 , 19] were implanted in the nude rat brain . Control animals underwent an identical surgical procedure and were inoculated with medium only . Quantitative magnetic resonance imaging techniques were implemented on a 3T whole-body clinical scanner ( Philips Achieva ) to phenotype the tumors . Fast bound-pool fraction imaging ( FBFI ) , a method validated with histology to measure myelin density and identify tumor associated disruption of normal brain tissues [20] , was used to produce bound-pool fraction maps ( f maps ) to detect and differentiate between bulky and infiltrative lesions . The variable flip angle method [21] was used to measure T1 relaxivity ( R1 maps , where R1 = 1/T1 ) before and after administration of gadolinium ( gadopentetate dimeglumine , Bayer HealthCare ) , an intravenous contrast agent that shortens T1 and identifies disruption of the blood-brain barrier ( i . e . , hyperintense signal on post-contrast R1 maps relative to pre-contrast R1 maps ) . Our initial experiments found that GBM4 yielded small , focal , non-enhancing lesions ( Fig 1A and 1B , S1A and S1B Fig ) . In contrast , GBM8 produced heterogenous lesions that ranged from large , well-circumscribed tumors with strong contrast enhancement ( i . e . disruption of the blood-brain barrier ) to infiltrative lesions with absent or minimal contrast enhancement ( Fig 1A and 1B , S1A and S1B Fig ) . Detection of human ctDNA associated with GBM4 was not greater than the control animals ( Fig 1C ) , which was attributable to the small tumor size and absence of blood-brain barrier disruption . Human ctDNA was detected in all animals implanted with GBM8 including infiltrative lesions with absent ( e . g . , GBM83 , Fig 1A and 1B ) to minimal ( e . g . , GBM82 , S1A and S1B Fig ) disruption of the blood-brain barrier ( Fig 1C , S1C Fig ) . The percent human ctDNA in the buffy coat , where some residual plasma remains present , appeared correlated with the fraction in plasma , but much lower , indicating that neither intact tumor cells nor a high molecular weight fraction of ctDNA were present in the circulation ( Fig 1C ) . Unexpectedly , there was a precise difference in fragment length between human ctDNA and rat cell-free DNA . The most common fragment lengths in human ctDNA were 134 bp and 144 bp ( Fig 1D , S1D Fig ) , which was in contrast to the most common fragment length of 167 bp in rat cell-free DNA ( Fig 1F ) . Human ctDNA fragment lengths also exhibited a strong ~10 bp periodicity that was not as evident in the rat cell-free DNA . This pattern was consistent across all animals where human ctDNA was detected ( Fig 1E ) . To determine if the fragment length and periodicity extended beyond the GBM8 cell line , nude rats were again implanted with either GBM4 or GBM8 . Animals implanted with GBM4 were serially imaged until the presence of blood-brain barrier disruption was evident ( i . e . , contrast-enhancement on MRI ) or animals lost more than 10% bodyweight . As before , GBM8 animals developed tumors that were large and exhibited a range of phenotypes ( Fig 2A and S2 Fig ) . Fragment length and periodicity was consistent with that present in the initial experiment ( Fig 2C ) . After a post-surgical interval nearly twice as long as GBM8 , GBM4 tumors developed ( Fig 2 and S2 Fig ) . GBM4 tumors tended to grow more anteriorly towards the olfactory bulbs , which led to weight loss in animals before tumor size was similar to GBM8 . In a single animal implanted with GBM4 , ctDNA was adequately detected and a similar fragment length and periodicity as seen with GBM8 was identified ( Fig 2C ) . To evaluate the role of both GBM and the blood-brain barrier in determining fragment length and periodicity , human hepatocellular carcinoma cells ( Hep G2 ) were implanted subcutaneously in the flank of three nude rats . A palpable tumor ( approximately 10 mm at maximal diameter ) , confirmed with histology , formed in a single animal ( Fig 2D ) . The fragment length of ctDNA was consistent with that described in GBM4 and GBM8 ( Fig 2E ) . There was evidence for a similar periodicity , but the relatively low amount of detected ctDNA may have contributed to a noisier distribution of fragment size . Regardless , the replication of results in a xenograft model of hepatocellular carcinoma suggested that the periodicity and reduced fragment length of ctDNA may be general properties of ctDNAs in cancers beyond GBM . We next considered the effects of the xenograft model on ctDNA fragment length and periodicity and sought to determine if evidence of the observed differences in fragment length were present in other types of solid tumors such as melanoma . In contrast to the xenograft models , the cell-free DNA from tumor patients represented an indistinguishable mix of both ctDNA and cell-free DNA derived from normal healthy cells . By densitometry ( TapeStation 2200 ) , the cell-free DNA from melanoma patients had globally shorter fragment lengths compared to healthy controls ( Fig 3A ) . Potential differences in fragment length size between tumor patients and healthy controls were explored by sequencing the cell-free DNA from a melanoma patient with an elevated concentration of cell-free DNA ( 36 . 4 ng/mL plasma; Fig 3A , black arrow ) to obtain a large sample for comparison to sequencing results from a pooled sample of control cell-free DNA . The most common fragment length in the melanoma patient was shorter than the most common fragment length in the control sample ( 145 bp vs . 165 bp , respectively; Fig 3B ) . There was also evidence for more pronounced fragment length periodicity in the cell-free DNA from the melanoma patient ( Fig 3B ) . In the melanoma patient cell-free DNA , the BRAF V600E allele frequency was increased at shorter fragment lengths compared to the WT allele ( Fig 3C ) . Of note , the broad distribution of the WT allele ( Fig 3C , blue line ) included a substantial proportion of overlapping fragment sizes with the mutant allele since the BRAF V600E mutation is heterozygous and tumor cells also introduced shorter fragment lengths into the circulation with the WT allele . Subsequently , fragment length for the melanoma patient and the healthy volunteer were binned ( e . g . 50 = 50–59 bp; 60 = 60–69 bp , etc . ) and the frequency of mutant allele and WT allele was determined , respectively . For a given fragment length , the proportion of the V600E BRAF allele to the WT allele was highest in the 110–140 bp fragment length , which was in contrast to the WT allele in the pooled healthy control sample that occurred at the highest frequency between 160–180 bp ( Fig 3D ) . Importantly , there were limited observations of ctDNA fragments <100 bp in the melanoma patient ( Fig 3D , black line ) , which were likely present but not well recovered by current approaches to library preparation [22] . These collective findings indicated an overall shortening of ctDNA fragment size relative to cell-free DNA that was not an effect of the xenograft model , but rather inherent to ctDNAs across different tumor types . We then sought to characterize tumor-related differences in cell-free DNA and ctDNA associated with human lung cancer . A comparison of cell-free DNA from 15 lung cancer patients and 9 healthy controls found a statistically significant difference in plasma concentration of cell-free DNA ( 31 . 0±23 . 3 vs . 11 . 3±4 . 6 ng mL/plasma , p = 0 . 006; respectively ) ; however , the range of concentration in tumor patients was broad and overlapped with the concentrations present in healthy controls ( S3 Fig ) . Libraries made with duplex truncated molecular barcoded adapters , which added ~99 bp to each strand of cell-free DNA , were created to enable loading of a consistent concentration ( 2 ng/μL ) of each sample and clear identification of upper/lower markers for direct comparison of densitometry data ( TapeStation 2200; S4 Fig ) . Consistent with our observation in melanoma patients , peak fragment length by densitometry was significantly shorter compared to healthy controls ( 277 . 0±4 . 7 vs . 283 . 7±4 . 1 bp , p = 0 . 002; respectively; S3B Fig ) indicating a global shift towards smaller fragments in lung cancer patients . However , there was also considerable overlap of peak fragment length between tumor patients and controls ( S3B Fig ) . There was not an association between peak fragment length by densitometry and plasma concentration of cell-free DNA in the lung cancer patients ( Pearson’s r = –0 . 20 , p = 0 . 47; Fig 4C ) or the healthy controls ( Pearson’s r = 0 . 19 , p = 0 . 63; S3C Fig ) . For a subset of samples ( tumor , N = 7; control N = 5 ) , cell-free DNA was converted to Illumina sequencing libraries and enriched for cancer-relevant genes using a 16-gene capture panel . Utilizing fragment lengths from the complete 16 gene capture panel , we observed that the cell-free DNA from tumor patients ranged from a shorter fragment length with ( Fig 4A ) and without ( Fig 4B and S5A–S5D Fig ) a strong periodicity to indistinguishable ( Fig 4C and S5E–S5G Fig ) in fragment length distribution from healthy controls . Cell-free DNA from the tumor patients did not exhibit a fragment length larger than the controls ( S5 Fig ) , which was consistent with densitometry ( S3B Fig ) . Cell-free DNA from two lung cancer patients ( LC5 and LC10 ) contained the classic EGFR L858R mutation [23] . Fragments containing the mutant allele , which originate from the tumor rather than from breakdown of normal cells , were shorter than those bearing the WT allele in healthy controls ( Fig 4D ) . This difference was especially pronounced in one sample ( LC5; Fig 4E ) with a relatively high mutant allele frequency ( 74 . 6%; likely due to EGFR amplification , S6 Fig ) . Cell-free DNA from six of the lung cancer patients contained the EGFR T790M mutation . In 5 out of 6 patients , the mutant allele frequency was relatively low ( 0 . 2–6 . 6% ) . However , the general trend in these samples was for mutant alleles to occur at shorter fragment lengths ( Fig 4F ) . In one sample ( LC9 ) with a relatively high mutant allele frequency ( 25 . 1%; most likely due to an EGFR amplification , S5 Fig ) the mutant allele more commonly occurred at shorter fragment lengths compared to the fragment lengths from healthy controls ( Fig 4G ) . The distribution of fragment lengths of the EGFR WT allele between tumor patients and healthy controls largely reflected differences seen in S5 Fig , although noisier due to fewer total reads ( S7 Fig ) . Within each lung cancer patient with the mutant T790M allele , comparison of the distribution of the EGFR WT allele and the mutant T790M allele fragment lengths identified a general trend for the mutant allele to occur more commonly at shorter fragment lengths ( Fig 4H ) . As with the melanoma patient ( Fig 4C ) , fragment length analysis of the WT allele from tumor patients included an indistinguishable mixture of ctDNA and normal cell-free DNA since the mutant T790M allele is heterozygous . As such , the representative WT allele fragment length distribution from tumor patients included WT alleles derived from tumor cells . This observation may explain , at least in part , why the differences in fragment length between the WT allele and the mutant T790M allele presented in Fig 4H were less pronounced than differences observed between the WT allele from healthy controls and the mutant T790M allele shown in Fig 4F . We next set out to determine whether selection for shorter fragment lengths could be used to enrich for ctDNA fragments against the large background of cell-free DNA derived from normal cells . Cell-free DNA sequencing libraries from four lung cancer patients ( LC1 , LC3 , LC4 , and LC10 ) with EGFR T790M mutations and one healthy control ( C5 ) were selected for serial fraction collection . By sequencing , LC1 and LC3 had EGFR T790M mutant allele frequencies of 1 . 2% and 6 . 6% , respectively , and evidence of overall shorter cell-free DNA fragments compared to healthy controls ( Fig 4B and S5B Fig , respectively ) . LC4 and LC10 had EGFR T790M mutant allele frequencies of 2 . 3% and 1 . 7% , respectively , and a similar size distribution of cell-free DNA fragments compared to healthy controls ( S5G Fig and Fig 4C , respectively ) . None of the samples had an EGFR amplification present ( S6 Fig ) . For each sample , 1 μg of sequencing library was loaded onto an 8% native polyacrylamide gel and six adjacent gel fragments were collected ( S8 Fig ) . Extracted DNA ( 5–10 ng ) from each gel fragment was then amplified using the full-length adapter primer and the EGFR T790M mutant allele frequency was determined via digital droplet PCR ( Fig 5 ) . Compared to the mutant allele frequency in the library , three samples ( LC1 , LC4 , and LC10 ) demonstrated a 2 . 5-fold to 9 . 1-fold increase in the mutant allele frequency in a subset of fractions that contained a shorter distribution of cell-free DNA fragments relative to the peak fragment length in the library ( Fig 6 and S9–S11 Figs ) . The fraction associated with the greatest increase in mutant allele frequency for each tumor patient is identified in Fig 6A–6C . In one sample ( LC1 ) , the mutant allele frequency did not increase in any fraction relative to the mutant allele frequency in the library ( S12 Fig ) . However , a decrease in the mutant allele frequency was observed in fractions containing longer fragments , while fractions with shorter fragments contained a relatively consistent mutant allele frequency ( Fig 6D and S12 Fig ) . Enrichment for the mutant allele was greatest in fractions that were centered approximately 20–50 bp shorter than the peak fragment length associated with each corresponding library ( Fig 6E ) . The increase in mutant allele frequency was greatest in LC10 ( Fig 5 and S11 Fig ) and LC4 ( S10 Fig ) , which were the two tumor patients with a similar fragment size distribution profile as that seen in the healthy controls ( Fig 4C and S5G Fig , respectively ) . This finding suggests that the fractional selection of shorter cell-free DNA fragment lengths may improve mutant allele sensitivity when ctDNA is not the predominant component of cell-free DNA . Also notable is that the percentage of mutant allele detected in a sample low in ctDNA prior to enrichment may not represent the true allele frequency present in the tumor due to dilution by normal cell-free DNA . In LC1 ( S12 Fig ) and LC3 ( S9 Fig ) , the tumor patients with evidence of overall shorter cell-free DNA fragments compared to healthy controls , the increase in mutant allele frequency in fractions 20–50 bp shorter than the peak fragment length associated with each library was not as substantial; however , selecting these fractions also did not diminish the mutant allele frequency ( Fig 6E ) . In contrast , the selection of fractions longer than the library’s peak fragment length substantially reduced the mutant allele frequency in three of the tumor samples ( LC1 , LC4 , and LC10; Fig 6E and S10–S12 Figs ) . Similarly , the selection of fractions containing cell-free DNA fragments >50 bp shorter than the library’s peak fragment length reduced the mutant allele frequency in all of the samples ( Fig 6E ) . This latter observation may be a consequence of recovery during library preparation as discussed earlier ( Fig 3D ) [22] . Regardless , these observations provide compelling evidence that the fragment length of ctDNA is shorter than cell-free DNA from healthy cells and selection of shorter cell-free DNA fragments may improve mutant allele frequency . Of note , the EGFR T790M mutant allele was not present above the noise level associated with digital droplet PCR in the fractions obtained from the control sample ( S13 Fig ) . Our broad observation that the fragment length of ctDNA differs from cell-free DNA is supported by earlier reports that utilized amplicons of varying length to identify large categorical size differences between ctDNA associated with colorectal cancer and cell-free DNA from healthy controls [16 , 24] . In addition , deep sequencing has been previously used to identify ctDNA shortening in hepatocellular carcinomas with specific aneuplodies [17] . However , this latter study also identified fragment lengths larger than healthy controls associated with low ctDNA concentrations in patients with hepatocellular carcinoma which is difficult to reconcile [17] . The collective findings described in our study builds upon these previous works by utilizing massively parallel sequencing to define distinct differences in fragment length between ctDNA and cell-free DNA . Specifically , animal models of GBM and hepatocellular carcinoma found that the most common fragment lengths of ctDNA were 134 and 144 bp , which was in contrast to the most common 167 bp fragment length present in normal cell-free DNA . These findings replicated in human patients with melanoma . Moreover , selection of cell-free DNA fractions containing shorter fragment lengths substantially increased mutant allele frequency in human lung cancer patients , particularly when the distribution of cell-free DNA fragment lengths in tumor patients was similar to the distribution seen in healthy controls . As such , the findings described herein provide strong evidence that a more general process that shortens ctDNA fragment length relative to normal cell-free DNA from healthy cells is present and is independent of copy number alterations . The overall distribution of fragment lengths identified for ctDNA and cell-free DNA in our study was consistent with cellular apoptosis rather than necrosis [25] . In addition , the observed ~10 bp periodicity has been well-described in association with nuclease-cleaved nucleosome activity [26] . However , the etiology of the shorter fragment length associated with ctDNA remains unclear . Lo et al . previously reported similar findings from maternal serum with regards to fragment length differences between fetal cell-free DNA and maternal cell-free DNA [27] . Differences in cell-free DNA fragment lengths between donor-derived and host cell-free DNA in organ transplant patients has also been observed [28] . The extent of cell-free DNA shortening across disparate tissue contexts , in health and disease , suggests that tissue-specific processes may contribute to certain cell-free DNA fragment length sub-populations . One plausible hypothesis is that tissue-specific differences in nucleosome wrapping [29] result in fragment lengths that differ between hematopoietic cells ( which contribute the majority of the plasma cell-free DNA ) and other tissues of origin . Understanding the specific mechanism behind this phenomenon may prove valuable in oncology . Regardless of etiology , enriching for a specific subset of cell-free DNA fragment lengths may improve detection of ctDNA associated with non-metastatic solid tumors . More sensitive detection of mutations present in ctDNA may lead to non-invasive diagnosis of malignancy , improved detection of tumor recurrence , and better monitoring of response to therapy . A limitation of this study was that very short rat cell-free DNA fragments ( <100 bp ) were detected in the GBM41 animal ( Fig 1F , red line ) and very short human ctDNA fragments ( <100 bp ) were detected in the Control1 animal ( S1D Fig , blue line ) that were not present in the other animals . In the former , these very small fragments created a unique bimodal distribution of normal rat cell-free DNA . In the latter , these fragments were associated with an increased proportion of human ctDNA compared to other control animals ( Fig 1C ) . As such , it was unclear if low levels ( <0 . 01% ) of ctDNA in tumor-bearing animals were a true signal or noise . Earlier use of a xenograft model for detection of ctDNA via PCR found a very high species sensitivity and specificity [24] . Although the very short fragments identified in our study were most likely secondary to contamination or sample handling , future xenograft-based studies utilizing species specific genomes obtained from massively parallel sequencing to separate ctDNA from cell-free DNA would benefit from determination of sensitivity and specificity . A second limitation is the accuracy of densitometry measurements ( S14 Fig ) . Although densitometry tended to preserve relative differences between samples , we found that estimation of true fragment length was often over-estimated . As such , sequencing results may provide a more accurate measure of fragment length assuming sufficient reads of different sized inserts are available to reduce size profile noise . All human subject research was approved by the University of Utah Institutional Review Board prior to study initiation . Written informed consent was obtained for samples from melanoma patients and healthy controls according to IRB approved studies 10924 and 7740 . Informed consent was not obtained for the lung cancer samples as specimens were obtained from residual clinical samples scheduled for disposal and after de-identification according to IRB approved study 7275 . Adult male RNU rats were used in this study . All procedures were approved by the University of Washington Internal Animal Care and Use Committee prior to study initiation . For surgery , rats were anesthetized with ketamine and xylazine administered IP . For imaging , rats were anesthetized with isoflurane mixed with oxygen . Rats were euthanized with Beuthanasia-D administered IP . Established human GBM stem-like cell lines ( GBM4 , GBM8 ) [18 , 19] were maintained in serum-free Neurobasal medium ( ThermoFisher Scientific ) with 2 mM glutamine , 5 μg/mL heparin , 100 U/ml penicillin-streptomycin , N2 at 0 . 5X , B27 supplement minus vitamin A at 0 . 5X , and bi-weekly pulsing of FGF and EGF ( 20 ng/mL each ) . Human hepatocellular carcinoma cells ( Hep G2; ATCC ) were maintained in Williams’ medium E with glutamine and 10% fetal bovine serum . All cells were maintained in a humidified incubator at 37°C in 5% CO2 . For implantation , single cell suspensions of GBM4 and GBM8 were achieved using heparin-EDTA and trituration followed by spin and wash ×2 with Neurobasal medium , then spin and resuspend in Neurobasal medium with DNase ( 4k U/ml ) , trituration , and incubation ×5 minutes at room temperature . Cells were then washed ×2 with Neurobasal medium to remove DNase and resuspended in Neurobasal medium for cell counting . Cells were counted with a hemacytometer after suspension in Trypan blue . For implantation , 1×106 cells were resuspended in 10 μL of Neurobasal medium . Hep G2 cells were harvested by heparin-EDTA , counted using a hemocytometer after suspension in Trypan blue . For implantation , 5×106 cells were resuspended in 100 μL of Williams’ medium E . Adult male RNU rats ( Charles River Laboratories , Wilmington , MA ) were used in this study . All procedures were approved by the University of Washington Internal Animal Care and Use Committee prior to study initiation . Rats were anesthetized with 60 mg/kg ketamine and 5 mg/kg xylazine administered IP . For intracranial inoculation ( GBM4 and GBM8 ) , the head was immobilized in a stereotactic head set with ear bars and a teeth bar . The skull was exposed by a 2 cm midline incision , and a burr hole was created on the right side 1 mm anterior and 2 mm lateral to the bregma . A microsyringe ( Hamilton , Reno , NV ) was used to inject the 10 μL aliquot of 106 cells into the frontal lobe at a depth of 5 mm from the skull surface over a period of 5 minutes . The needle was kept in place 2 minutes after injection to prevent backflow prior to removal . The burr hole was filled with bone wax ( Ethicon , Somerville , NJ ) . The skin was closed with surgical staples that were removed prior to MR imaging . For flank injections ( Hep G2 ) , a 22-gauge needle attached to a TB syringe was used to inject the cells subcutaneously into the right flank . After the final imaging time point , the rats were anesthetized with Beuthanasia-D ( 2 mL/kg ) . A midline abdominal incision followed by thoracotomy was made to access the left ventricle of the heart . A 22-gauge needle attached to a syringe containing heparin was used to remove as much blood as possible ( 6–10 mL ) . Subsequently , 4% paraformaldehyde ( PFA ) was injected into the left ventricle ( total volume 150 mL ) as the right atrium was opened . Brains were subsequently removed intact , held in 4% PFA×24 hours under gentle agitation , and then maintained in PBS . After fixation , brains were sectioned to correspond with the anatomic coronal plane . Brains were subsequently embedded in paraffin and sections ( 5 μm thick ) were stained with hematoxylin-eosin . Stained slides were scanned using an Olympus VS110 virtual microscopy system ( Olympus , Center Valley , PA ) for display on NDP . view ( v2 . 3 . 1 ) . Rats were imaged on a 3 . 0 T Philips Achieva whole-body MRI scanner ( Philips Medical Systems , Best , Netherlands ) using a dual coil approach . A quadrature transmit/receive head coil ( Philips Medical Systems ) was utilized for RF transmission , and an in-house-built combined solenoid-surface coil [30] dedicated to high spatial resolution whole-brain rat imaging was used for RF reception . After induction in an anesthesia chamber with 5% isoflurane mixed with oxygen , the rats were positioned within the dual coils and maintained on 2% isoflurane mixed with oxygen via nose cone inhalation . Total scan time for all images was < 1 hour . Images necessary for construction of bound-pool fraction maps in the rat brain were acquired as previously described [20] . Briefly , Z-spectra data points were acquired for each rat using a 3D MT-prepared spoiled gradient echo ( GRE ) sequence with TR/TE = 42/4 . 6 ms , excitation flip angle α = 10° , NEX = 1 , and three offset frequencies ( Δ = 4 , 8 , and 96 kHz ) of the off-resonance saturation pulse ( effective flip angle = 950° ) . Complementary R1 maps necessary for parameter fitting were obtained using the variable flip angle method [21] with a 3D spoiled GRE sequence ( TR/TE = 20/2 . 3 ms , α = 4 ( NEX = 3 ) , 10 ( NEX = 1 ) , 20 ( NEX = 2 ) , and 30° ( NEX = 3 ) ) . All Z-spectral and VFA images were acquired with a FOV = 29×29×19 . 8 mm3 , matrix = 97×97×66 , acquisition resolution = 0 . 3×0 . 3×0 . 3 mm3 ( zero-interpolated to 0 . 15×0 . 15×0 . 15 mm3 ) , and full-Fourier acquisition . Whole-brain 3D B0 and B1 maps were acquired to correct for field heterogeneities . For B0 mapping , the GRE-based dual-TE phase-difference method [31] was used with TR/TE1/TE2 = 20/4 . 7/5 . 7 ms and α = 10° . B1 maps were obtained using the actual flip angle imaging method [32] and the following sequence parameters: TR1/TR2/TE = 25/125/6 . 6 ms and α = 60° . 3D B0 and B1 maps were acquired with a FOV = 29×29×19 . 8 , matrix = 64×64×33 , acquisition resolution = 0 . 45×0 . 45×0 . 6 mm3 ( zero-interpolated to 0 . 15×0 . 15×0 . 15 mm3 ) , and NEX = 1 . All images were acquired in the coronal plane . For administration of gadolinium ( gadopentetate dimeglumine , Bayer HealthCare; 0 . 5 M/L ) a 22 Gauge angiocatheter ( Becton-Dickinson , Sandy , Utah ) was inserted into the rat tail vein . The catheter was attached to a small bore bifurcated extension ( Smiths Medical , Dublin , OH ) containing a dilution of gadolinium in one arm and a normal saline flush in the other . The catheter setup was maintained with a saline lock until immediately prior to imaging . At time of injection , 0 . 2 mmol/kg ( 0 . 167 M/L ) of gadolinium was manually injected at 50 μL/s followed by a 250 μL flush of normal saline at 50 μL/s . Complementary pre-contrast R1 maps necessary for parameter fitting and post-contrast R1 maps obtained 5 minutes after contrast injection were acquired using the variable flip angle method [21] with a 3D SPGR sequence ( TR/TE = 4 . 6/20 ms , α = 4 ( NEX = 3 ) , 10 ( NEX = 1 ) , 20 ( NEX = 2 ) , and 30° ( NEX = 3 ) ) and FOV = 24×24×8 . 25 mm3 , matrix = 64×64×5 . 5 for an acquisition resolution of 0 . 38×0 . 38×1 . 5 mm3 ( zero-interpolated to 0 . 19×0 . 19×0 . 75 mm3 ) . Pre-contrast B1 maps using the actual flip angle imaging method [32] were acquired with the following parameters: TR1/TR2/TE = 25/125/6 . 7 ms and α = 60° . 3D B1 maps were acquired with a NEX = 1 and an identical resolution as the variable flip angle data points . All images were acquired in the axial plane . Fast bound-pool fraction parametric maps ( f maps ) were constructed consistent with a previously described methodology [20] for single parameter determination of f . Briefly , R1 maps were used to define R1F and reconstructed from VFA data using a linear fit to the signal intensities ( S ) transformed into the coordinates [S ( α ) / sin α , S ( α ) / tan α][21] after voxel-based B1 corrections were applied to α . In the MT data , the Δ = 96 kHz Z-spectra images were used to normalize the Δ = 4 and 8 kHz data points and voxel-based B0 and B1 corrections were applied to Δ and α , respectively , during voxel-based fitting for f . The parameters k , T2FR1F , and T2B were constrained to 29 x f/ ( 1-f ) s-1 , 0 . 030 , 10 . 7 μs , respectively , as previously determined [20] . R1B , the longitudinal relaxation of the bound-pool , was set to a fixed value of 1 s-1 by convention [33–35] . Pre- and post-contrast R1 maps were similarly constructed from the respective VFA data that was acquired in the axial plane . Corresponding pre-contrast B1 maps were similarly applied for correction of α during fitting of both pre- and post-contrast R1 maps . Image processing dedicated to whole-brain voxel-based determination of f maps and R1 maps was performed using in-house written Matlab ( The Mathworks , Natick , MA ) and C/C++ language software . Whole blood acquired from each animal was centrifuged at 1 , 600 g ×10 minutes at 4°C . The plasma layer was removed and centrifuged at 16 , 000 g ×10 minutes at 4°C . The buffy coat was then collected and stored at -80°C . After centrifugation , plasma was removed excepting a residual amount near the bottom that may have been in contact with any debris and stored at -80°C . Both plasma samples and the buffy coat were stored at -80°C <1 hour from time of collection from the animal . DNA was isolated from buffy coat cell pellets using the Qiagen DNeasy Blood and Tissue kit . Shotgun sequencing libraries were constructed with 50 nanograms of gDNA from each animal using the Nextera DNA library prep kit ( Illumina ) . Following the manufacturer’s direction , sample index sequences were added during the PCR step to allow libraries to be pooled for multiplexed sequencing on a single lane . Cell-free DNA was extracted from rat plasma using the QIAamp Circulating Nucleic Acid kit . DNA yield was measured with a Qubit dsDNA HS assay ( Invitrogen ) and 1–10 ng of cell-free DNA was used as input for library construction with the Thruplex-LC kit ( Rubicon Genomics ) . For samples with low input concentration ( <100 pg/ul ) , cell-free DNA was first concentrated across Zymo Clean-Concentrate-5 column ( Zymo Research ) . During library construction , enrichment PCR was performed using a BioRad MiniOpticon real-time thermocycler , with SYBR Green I dye ( Invitrogen ) added to each reaction at a final concentration of 0 . 25X . Reactions were individually removed upon entering log-phase amplification as indicated by SYBR signal ( 7–17 cycles ) . Libraries were normalized to 2 nM each and pooled for paired-end 101-bp sequencing across four lanes on an Illumina Hiseq 2000 instrument . A 9-bp index read was also collected and used to demultiplex reads according to input sample , requiring fewer than 2 mismatches to the known indices . For each buffy coat and cell-free DNA library , adapter sequences were trimmed and paired end reads were mapped to human and rat reference assemblies ( hg19 and rn5 , respectively ) using bwa [36] . For each read pair , the species origin ( rat or human ) was then determined using the mapping status against both references . Only reads that could be unambiguously mapped to one or the other species were included: reads with low mapping quality score ( <30 ) in both species’ references were discarded , as were reads of comparable mapping quality to both references ( absolute difference in map quality scores <20 ) . Tumor DNA abundance in each cell-free DNA and buffy coat fraction was then computed as ( # human read pairs ) / ( # human read pairs + #rat read pairs ) . Fragment length were then takes as the absolute distances between the outermost bases of each pair of forward and reverse ends . As a quality control check , an aliquot of each xenografted cell line at the time of implantation was genotyped across a panel of 96 human polymorphisms using a custom BeadArray assay performed by the Northwest Genomics Center . Cell lines with identical genotype calls in ≥ 95 of 96 markers were considered to be identical in origin , whereas all other pairs of cell lines shared genotypes at many fewer markers ( 34–45; S15 Fig ) . All procedures were approved by the University of Utah Internal Review Board prior to study initiation . Blood samples were collected in Streck BCT tubes , stored at 4°C , and processed within 24 hours of collection . Plasma was separated by centrifugation for 10 minutes at 1900g and aspiration to a new tube . Plasma was further centrifuged for 16 , 000g x 10 minutes to remove any cellular debris , and resulting supernatant was stored at –20°C until cell-free DNA isolation . Custom kits that combined Qiagen lysis and binding buffer with Zymo silica-based columns were assembled to reduce expense during isolation of cell-free DNA . Cell-free DNA was prepared from 8 mL of plasma by adding 800 μL of Proteinase K ( 20 mg/mL ) and 6 . 4 mL Buffer ACL ( Qiagen ) followed by incubation at 60°C x 30 minutes . Next , 14 . 4 mL of buffer ACB ( Qiagen ) was added to the lysate and incubated on ice for 5 minutes . DNA was isolated from the lysate with Zymo DNA Clean and Concentrator 100 kit according to the manufacturer’s instructions and eluted in 150 μL . A final purification step was performed using two volumes of Ampure XP magnetic beads followed by elution in 25–30 μL 10mM Tris ( pH 8 . 0 ) . For continuous variables , the means and standard deviations ( SDs ) were calculated for each group . The student’s independent t-test assuming equal or unequal variance based on Levene’s test was used to compare mean values between tumor patients and healthy controls . Pearson’s r was used to identify correlations between continuous variables . Statistical analyses were performed with SPSS for Windows ( Version 12 . 0 , SPSS , Chicago , IL ) . Statistical significance was defined as P < 0 . 05 .
During cell death , DNA that is not contained within a membrane ( i . e . , cell-free DNA ) enters the circulation . Detecting cell-free DNA originating from solid tumors ( i . e . , circulating tumor DNA , ctDNA ) , particularly solid tumors that have not metastasized , has proven challenging due to the relatively abundant background of normally occurring cell-free DNA derived from healthy cells . Our study defines the subtle but distinct differences in fragment length between normal cell-free DNA and ctDNA from a variety of solid tumors . Specifically , ctDNA was overall consistently shorter than the fragment length of normal cell-free DNA . Subsequently , we showed that a size-selection for shorter cell-free DNA fragments increased the proportion of ctDNA within a sample . These results provide compelling evidence that development of techniques to isolate a subset of cell-free DNA consistent with the ctDNA fragment lengths described in our study may substantially improve detection of non-metastatic solid tumors . As such , our findings may have a direct impact on the clinical utility of ctDNA for the non-invasive detection and diagnosis of solid tumors ( i . e . , the “liquid biopsy” ) , monitoring tumor recurrence , and evaluating tumor response to therapy .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
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2016
Fragment Length of Circulating Tumor DNA
Weekly iron-folic acid ( IFA ) supplementation and regular deworming is effective for the prevention of iron deficiency and anaemia in women of child-bearing age . Between 2006 and 2013 , a program of weekly IFA and biannual deworming was implemented in Yen Bai province , Vietnam . In this study we aimed to determine the effectiveness of the program in reducing anaemia and the prevalence of hookworm infection after 72 months ( six years ) . This prospective cohort study followed up a cohort of 389 women of child-bearing age from baseline until six years after the introduction of the weekly IFA ( one tablet containing 200 mg ferrous sulphate , 0 . 4mg folic acid ) and deworming ( one 400mg tablet of albendazole given twice yearly ) program ( May 2006 to 2012 ) . In each of the six surveys ( baseline and five follow-up surveys ) we measured haemoglobin and ferritin , and the burden of soil transmitted helminth ( STH ) infections , and in the 72 month survey we also administered a questionnaire to assess adherence and possible impediments to participating in the program . Two hundred and fifty six ( 65 . 8% ) of the original 389 women enrolled in the cohort attended the final 72 month survey . Haemoglobin levels were 122 g/L [95% C . I . 120 , 124] at baseline and increased to 135g/L [95% C . I . 133 , 138] after 72 months . The prevalence of anaemia was 37 . 8% [95% C . I . 31 . 0 , 44 . 7] at baseline and reduced to 14 . 3% [95% C . I . 9 . 5 , 19 . 1] . Hookworm infection prevalence , 75 . 9% [95% C . I . 68 . 1 , 83 . 8] at baseline , reduced to 10 . 2% [95% C . I . 5 . 4 , 15 . 0] with no moderate or heavy intensity infections . Seventy-two percent of participants reported still taking at least 75% of the weekly supplements , and 85 . 0% had taken the most recent deworming treatment . Anaemia rates fell significantly during the six-year program , and STH infections were eliminated as a public health risk . Adherence was well maintained but long-term sustainability is challenging in the absence of ongoing external support . Anaemia ( haemoglobin < 120g/L ) is estimated to affect 29 . 0% of non-pregnant women world-wide . [1] Iron deficiency anaemia ( IDA ) is the most common form of anaemia in many resource-poor settings . Nutritional anaemia can also be caused by vitamin deficiencies ( A , B2 , B6 , folate , B12 , C , E ) and deficiencies of other minerals—such as copper , zinc , and in some cases selenium; and severe protein-energy malnutrition . [2] Intestinal infections causing diarrhoea , malabsorption and blood loss ( especially hookworm infection ) may cause depleted body iron stores and worsen the risk of other micronutrient deficiencies by interfering with digestion and absorption ( e . g . , vitamin A ) . [3] The consequences of IDA are most evident in women of child-bearing age and children . In pregnancy IDA has been linked to premature delivery , higher maternal morbidity , and infants with low birth weight ( LBW ) , lower iron stores and higher anaemia rates . [4 , 5] Iron deficiency anaemia in infants and young children may lead to impaired development [4] with long term health implications . [6 , 7] Weekly iron-folic acid ( IFA ) supplementation is now recommended by WHO for nonpregnant women of child-bearing age living in areas with a prevalence of anaemia above 20% [8 , 9] , with the aim of improving a women’s iron and folate status prior to conception . The rationale for using intermittent rather than daily supplemental iron relates to the adverse impact of high levels of luminal iron in the gut and the concept that taking iron less frequently may facilitate absorption of iron by mucosal cells and lead to fewer side-effects [10–12] . WHO also recommends that preventive chemotherapy for soil transmitted helminths ( STH ) be considered in this group in endemic areas where the prevalence is 20% or higher . [13] However , it is not clear that compliance and effectiveness will be maintained over many years . Long-term sustainability is also of concern , especially when program implementation is dependent on external donor funding . Although the cost of weekly IFA supplementation per woman is estimated to be as little as USD 0 . 76 cents per year , this still equates to $76 , 000 . 00 per 100 , 000 women per year , a cost few local health administrations can afford . [14] Between 2006 and 2013 , we initiated and supported a program of weekly IFA supplementation , with regular deworming , to a target population of approximately 250 , 000 women of child-bearing age in Yen Bai Province , Vietnam . [15–17] Our objectives in this study were to document the adherence and effectiveness of weekly IFA supplementation and deworming on rates of hookworm infection , anaemia , and iron deficiency in a cohort of participants followed from baseline to 72 months ( 6 years ) post intervention . We also sought to identify administrative challenges and barriers to ongoing sustainability . The intervention has been described previously . [18] Briefly , a demonstration project of weekly IFA ( one 200mg tablet of Ferrous Sulphate—equivalent to 60mg elemental iron , 0 . 4mg folic acid ) supplementation combined with four monthly deworming ( Albendazole 400mg ) for non-pregnant women of child bearing age was initiated in May 2006 in two districts in Yen Bai province over a period of 12 months . Tran Yen and Yen Binh districts were selected for the intervention , being easy to reach , and with both Kinh and ethnic minority populations . All nonpregnant women of reproductive age between 16 and 45 years were eligible for the intervention . Supplements were supplied free of charge . Village health workers ( VHWs ) were central to the delivery of the intervention to women in their communities , and worked closely with the Women’s Union to mobilize the target population . A baseline survey was undertaken in November 2005 in a randomly selected cohort of women who were then followed up at 3 and 12 months post introduction of the intervention . [19] Sample selection for the cohort used a stratified multi-stage cluster design , in which 'probability proportional to size' random sampling was used to select primary sampling units ( villages ) within each district , and secondary sampling units ( women ) were selected randomly from each village using provincial lists . A sample size of at least 280 was required in the baseline and follow-up surveys to detect an increase in haemoglobin of 5 g/L with a power of 0 . 9 , a type 1 error of . 05 , and accounting for clustering with an intraclass correlation of 0 . 2 . This number was also sufficient to detect a reduction in hookworm prevalence of 30% . There was no control group as it was considered unethical to actively withhold IFA supplementation and deworming treatment from this group over several years . After 12 months of the demonstration project , improvements were seen in all measured indices of women’s health: haemoglobin , serum ferritin , anaemia ( Hb < 120 g/L ) , iron deficiency ( serum ferritin < 15 mcg/L ) and STH prevalence and intensity of infection . [15] As a result , the provincial authorities supported the expansion of the intervention to target reproductive-aged women in all districts of the province ( some 250 , 000 women ) . The community-based program was administered from the Yen Bai Centre for Malaria Control , through the District Centres for Preventive Medicine to Commune Health Stations and VHWs . The expanded program consisted of a weekly IFA tablet ( 200mg Ferrous Sulfate ) and one tablet of Albendazole ( 400mg ) given twice a year . Eligible women were encouraged to collect their supplements monthly from their VHW , who recorded the woman's name and date of distribution and advised about side-effects and safe storage of supplements . Albendazole was given as observed treatment on locally designated days either at the commune health station or supervised in the village by a commune health worker . National oversight of the program and support for training and educational material development and production was provided by the National Institute of Malariology , Parasitology and Entomology , which also has responsibility for the national hookworm control program . The Provincial Health Department provided salary support for distribution through the health system . WHO donated albendazole tablets but external donor funding was required for the IFA supplements , training and training materials and educational and promotional materials . Thus , the program was not fully supported by the national health system , remaining partly dependent on external financial and administrative support . The same cohort of women who participated in the baseline , three and 12 month surveys during the demonstration project ( as described above ) were invited to participate in the 30 month , 54 month , and 72 month follow-up surveys if they were still resident in the same villages . In all surveys participants were asked to provide a venous blood sample and a faecal sample . Haemoglobin was measured by HemoCue 201+ ( HemoCue AB , Angelholm , Sweden ) and the STH burden was determined using the Kato-Katz technique as described by Ash et . al . [20] Classification of helminth infection intensity ( eggs per gram , EPG ) was according to WHO cut offs: 1 ) Hookworm infections: light = 1–1999 , moderate = 2000–3999 , heavy ≥ 4000 2 ) Ascaris lumbricoides: light = 1–4999 , moderate = 5000–49999 , heavy ≥ 50000 , and 3 ) Trichuris trichiura light = 1–999 , moderate = 1000–9999 , heavy ≥ 10000 EPG . For previous surveys , serum ferritin was measured using a sandwich immunoenzymatic assay ( IEA; Beckman Coulter Access Reagents , Fullerton , CA ) . Due to a change in technology at the original laboratory and a subsequent change in the laboratory used , serum ferritin for the 72 month survey was analysed using a Cobas immunoturbidometric test kit ( Roche Diagnostics GmbH , D-68298 Mannheim ) . The structured interview administered during the 72 month survey sought information about whether women had taken the last deworming treatment and how regularly they had taken IFA supplements during the previous 10 weeks , and reasons for noncompliance . It also asked about other factors that may influence adherence such as access to , or provision of , supplements and direct or indirect costs related to travel or lost work time . Adherence with the supplementation regime was defined as taking at least 75% of the supplements provided by the VHW . Data of surveys collected before year 6 have been analysed and reported previously . [21] By pooling all available survey data we extended the former semi-cross-sectional , semi longitudinal panel design with data collected as part of the final survey . Data analysis was conducted using Stata/IC 11 . 2 ( College Station , TX ) . Cross-sectional summary data was obtained via linear ( haemoglobin , log transformed ferritin ) and logistic ( prevalence ) regression models that were fitted per survey time point , incorporating clustering at village level ( Huber-White Sandwich estimator ) to obtain robust standard errors . Ferritin data was right-skewed and therefore log transformed to normalise the data . Arithmetic mean haemoglobin , geometric mean ferritin , and prevalence ( anaemia , iron deficiency , IDA , hookworm , ascaris , trichuris , and total STH infection ) with 95% confidence intervals are presented . At each survey time point and for every outcome , the analysis sample consisted of the available outcome data of all eligible women . Data from women who became pregnant during the study were not excluded from the analysis sample . Longitudinal repeated measures mixed linear and logistic regression was used to investigate the change from baseline to year 6 , while accounting for clustering at individual and village level . Adherence data on weekly IFA supplementation and deworming treatment was summarized descriptively by survey as percentages with 95% confidence intervals . Differences in changes over time in anaemia prevalence were examined by ethnic group within district . The odds ratio of being iron deficient at each post-implementation time point compared to baseline was explored . At 72 months , prevalence of iron deficiency was compared between subgroups formed by district , ethnic group , and gender . Changes in prevalence over time by severity of hookworm , ascaris , and trichuris infection are presented graphically . Extensive consultation was undertaken between the project team , communities and community leaders , as well as liaison with village , district and provincial health staff . Village health workers provided participants with information regarding the surveys and written informed consent was documented at the time of enrolment in the surveys . The National Institute of Malariology , Parasitology and Entomology and the Walter and Eliza Hall Institute of Medical Research and Melbourne Health approved of these consent procedures , which were standard NIMPE consent procedures . Potential recruits received a printed plain language statement and oral consent and documented signatures were obtained prior to participation . Participants were informed that they could withdraw from the study at any time and that withdrawal would not affect their routine medical treatment . Participants were all adult women between the ages of sixteen and forty-five; there were no minors included . The project was approved by the Human Research Ethics Committees of the National Institute of Malariology , Parasitology and Entomology ( Hanoi , Vietnam ) , and the Walter and Eliza Hall Institute of Medical Research and Melbourne Health ( Melbourne , Australia ) and all ethics committees specifically approved the use of participants of reproductive age between sixteen and forty-five years of age . The timeline and participation rates for this and previous surveys are shown in Fig 1 . Of the 389 women originally surveyed in 2005 , 256 returned for the survey in 2012 . Two hundred and fifty two women provided blood samples , 216 provided stool samples and six women left before completing the interview . One hundred and seventy eight women ( 72 . 0% [95% C . I . 63 . 6% , 80 . 4%] ) were still taking at least 75% of the supplements they received . A further 29 women received the supplements but either only took them sometimes or gave them to someone else . The forty-three remaining women did not receive the supplements . These latter women were concentrated in six communes in Tran Yen district . Deworming treatment was received by 85 . 0% ( 95% C . I . 79 . 5 , 90 . 5 ) of women ( 212/249 ) during the last campaign but two of them did not take it . The adherence over time with taking IFA supplements and deworming treatment is shown in Table 1 . The change in mean haemoglobin and ferritin , and the prevalence of anaemia , iron deficiency anaemia and moderate/heavy STH infection over the 72 month period of program implementation are shown in Table 2 . By 2012 the overall mean haemoglobin level was 135g/L [95% C . I . 133 , 138] . Based on the mixed-effects model this represents an increase from baseline of 13g/L [95% C . I . 11 , 15] . The prevalence of anaemia reduced from 38% [95% C . I . 31 , 45] to 14% [95%C . I . 9 , 19] . Iron deficiency anaemia reduced from 14% [95%C . I . 10 , 19] to 3 . 9% [95% C . I . 2 , 6] . The relative change in anaemia over time by district and ethnic group of Kinh or non-Kinh is shown in Fig 2 . The anaemia prevalence dropped significantly from previous levels in all population groups , in the first 12 months of the intervention . In the following years anaemia prevalence continued to decrease significantly , in both the Kinh and non-Kinh ethnic groups , in Yen Binh district . However in Tran Yen district it remained static in the following 5 years , between 11 and 17% for the Kinh , and between 21 and 29% for the non-Kinh . The prevalence of iron deficiency in the 72 month survey was 43/252 ( 17% , [95%C . I . 10 , 24] ) . This was an increase on previous levels and corresponded to falling adherence rate ( Fig 3 ) . There was a higher prevalence of iron deficiency in Tran Yen , 30/140 ( 21% , [95% C . I . 15 , 28] ) compared to Yen Binh , 13/112 ( 12% , [95%C . I . 6 , 18] ) . Iron supplements were reportedly taken by 25/29 ( 86% , [95%C . I . 73 , 100] ) of iron deficient women in Tran Yen , and 9/13 ( 69% , [95% C . I . 40 , 98] ) in Yen Binh district . Iron deficiency was more prevalent among women from ethnic minority groups ( non-Kinh ) 23/95 ( 24% , [95% C . I . 16 , 33] ) than Kinh women , 20/157 ( 13% , [95%C . I . 7 , 18] ) . The main reason for not taking supplements was unavailability , but some women also reported not needing them because they felt well . The overall prevalence of STH infection fell from 83 . 7% [95% C . I . 77 . 2 , 90 . 2] to 13 . 9% [95% C . I . 8 . 7 , 19 . 1] , and hookworm infection from 75 . 9% [95% C . I . 68 . 1 , 83 . 8] to 10 . 2% [95% C . I . 5 . 4 , 15 . 0] , while moderate and heavy infections were essentially eliminated ( Fig 4 ) . We report the effectiveness of a community-wide weekly IFA supplementation and regular deworming program in a population of non-pregnant rural Vietnamese women after 72 months . It is one of the few studies to evaluate an intermittent iron supplementation and deworming program for nonpregnant women over a period of many years and offers unique insights into the effectiveness and sustainability of the WHO-recommended approach to prevention of iron-deficiency anaemia in this population . Haemoglobin levels remained well above the baseline mean and the prevalence of anaemia continued to fall in most sections of the population . Moderate and heavy intensity STH infections were virtually eliminated and only 10% of women still had light infections ( mostly hookworm ) . In 2011 , WHO recommended weekly IFA supplementation for non-pregnant women of reproductive age in populations with an anaemia prevalence of 20% or higher , given in three month cycles with a three month gap between each cycle . [8] In the Yen Bai setting , it took 12 months of weekly supplementation for the population prevalence of anaemia to drop below 20% and up to 6 years ( 72 months ) for the prevalence to be significantly below the 20% level . This slow rate of decline in anaemia levels has also been noted in other studies [22 , 23] and suggests greater benefits if weekly or biweekly supplementation is given continuously , at least in the first year , and continued for several years . The increased risk of iron deficiency in women of child bearing age is often compounded by hookworm infection in endemic areas . WHO has previously recommended that this group be included in preventive chemotherapy programs for STH ( except during the first trimester of pregnancy ) , and suggest achieving synergy by packaging this intervention with other interventions . [13] These guidelines are currently being updated and will provide more detail to assist program managers considering this intervention . [24] We observed reduced but still reasonable adherence with weekly IFA after 54 and 72 months ( 76% and 72% respectively ) , suggesting that the program remained popular with the target population . However , despite the relatively high reported adherence rates in Tran Yen district we noted a rise in the prevalence of iron deficiency since the 54 month survey . We found that the supply of IFA supplements had been interrupted in certain communes in Tran Yen district during this time , which may explain the rise in iron deficiency in this district . The failure to achieve a consistent supply of supplements in these communes may be due to inadequate training of new health staff over the 6 years of implementation as there was considerable turnover of commune staff and VHWs ( GC personal communication ) . It is important to note that STH infections of moderate and heavy intensity for any STH species remained at or less than 1% . As these heavier worm burdens infections are main cause of morbidity , we conclude that the deworming intervention virtually eliminated all STH-related morbidity . Limitations of the study included a reduced participation rate in the later surveys , in spite of the efforts of local village and commune health workers publicising the surveys . This was most likely due to the long follow-up period , and the movement of some families out of the area . The relatively high loss to follow-up may have biased our estimates of adherence and effectiveness , as non-adherent women may have chosen not to take part , while healthier adherent women may have remained engaged . As well , women who were feeling tired , or had illness , and those with poorer economic circumstances may have been less likely to adhere and/or to attend for surveys . This would have resulted in a healthier cohort at the end of the program , making the intervention appear more effective . Other limitations were that adherence data relied on self-reporting rather than objective documentation , and women who attended the survey may have exaggerated their adherence . Ferritin levels were measured using different methodology in this , compared to previous surveys . However both were commercial assays and we have no reason to believe that this change contributed to the lower mean ferritin observed in this survey . We did not include a control group as the research team and provincial authorities felt this would be unethical for a long term program . However , we are unaware of significant improvements in economic conditions during the six year period that may have accounted for the results presented here . Indeed , the global financial crisis commenced soon after program expansion and so deterioration in community living standards may have been expected . Improvements in main road infrastructure did occur but we did not observe a change in living conditions at village level ( Casey , personal communication ) . The project was conducted in a remote rural region of Vietnam and may not be generalizable to other areas or ethnic groups where the prevalence and causes of anaemia may differ . The sustainability of weekly IFA/deworming programs for the large populations for whom they are recommended is country-specific . The program in Yen Bai province was mainly externally funded , and so was never fully incorporated as a national or provincially-funded program . In post program debriefings , provincial health and finance officials emphasised that , while the program was well accepted by the population and effective and cheap on a per person basis ( 0 . 76USD/woman/year ) , the cost of supplying weekly supplements to the target population ( approx . $200 , 000 per annum ) was beyond the capacity of the province’s health budget . While they were prepared to cover the human resource distribution costs , they were not able to support purchase of IFA supplements , development and production of educational materials , and training ( G Casey , T Tinh , personal communication ) . Multiple micronutrient supplementation is even more expensive , even though it may be indicated in settings with higher rates of micronutrient deficiencies . [25] There are however encouraging signs for the long-term sustainability of community-based WIFS/deworming programs in some other countries , especially India . [17 , 26] Based on sound evidence from the field , [23 , 27] the Indian Government has produced an operational framework for universal weekly IFA supplementation for adolescents in school and adolescent females not attending school . [28] Responsibility for the national program , from policy formulation and resource allocation to monitoring and review , has been allocated to the Ministry of Health and Family Welfare [29] . Given that this program is projected to cover 130 million adolescents , it may encourage more countries with at-risk populations to provide resources for similar national programs . Likewise , in Cambodia , the use of weekly iron and folic acid supplementation has been progressively extended , over a 10 year period , to cover most schools ( LTC-S personal communication ) . A revolving fund approach can help sustain the program , by selling the supplements . This approach was successfully used in the weekly IFA supplementation programme of Hai Duong province , Viet Nam , where the supplements were sold to non-pregnant women through the Women’s Union network and provided free of charge when women were pregnant , according to the Vietnamese health policy [30] . Over a year , a non-pregnant woman would spend the equivalent of US$0 . 96 , which was acceptable for rural women in Vietnam . Funds gained from the sales of the supplements were used to pay for an incentive for Women’s Union collaborators to sell the supplement ( 20% ) , and for management costs and regular communication and promotion activities in the communes ( 30% ) . The remaining 50% was held in a local bank under the supervision of a district steering committee , and used to purchase new supplements , to continue the programme beyond its initial financing period . [30] A review of weekly IFA supplementation programs conducted in Cambodia , The Philippines and Viet Nam concluded that women are willing and able to purchase supplements when they are widely available and affordable , including in poor rural areas and schools . [31] In the Cambodian factories , where supplements had to be provided free of charge because local laws forbade their sale , WRA asked that the supplements be sold outside the factories so that they could continue taking them in the future . In each country , the programme’s success led to expanding weekly iron-folic acid supplementation through larger-scale programmes . The variety of social marketing and community mobilization strategies used in the three countries in schools , factories , and communities ( discussed in the above mentioned programme review ) provide valuable lessons for replicating this approach in other countries . [31] An analysis of 10 weekly IFA programmes for the prevention and control of anaemia in women , which took place in 6 countries , confirmed that high compliance in taking the supplements can be achieved , irrespective of supervision , provided recipients are convinced of the benefits through an effective communication strategy , with the participation of several stakeholders , and a system in place for monitoring consumption . [17] In conclusion , the program of free weekly IFA supplementation and regular deworming for women of reproductive age in Yen Bai province ran successfully for 6 years with external inputs of supplements , training and education . It was well received by the population , with good adherence , and resulted in major reductions in anaemia and STH infection . Sustainability will probably require full integration into Vietnam’s national health system . A complementary approach to be considered , successfully used both elsewhere in Viet Nam and in other countries , is to sell the supplements at an affordable price while promoting them through social marketing , thus creating and maintaining demand for the product .
Weekly iron-folic acid ( IFA ) supplementation combined with regular deworming for women of child bearing age is effective in the prevention of iron deficiency and anaemia . Following a baseline survey , a weekly IFA and regular deworming project was implemented in Yen Bai province , Vietnam in 2006 , and after 12 months expanded to the entire province . Haematological parameters , soil transmitted helminth ( STH ) burden and adherence to the program were monitored periodically until 2012 . We found anaemia prevalence fell from 37 . 8% to 14 . 3% during the six-year period , and haemoglobin levels increased from 122 g/L to 135g/L . STH infections were essentially eliminated as a public health risk . Seventy-two percent of participants continued to take at least 75% of the weekly supplements , and 85 . 0% took the most recent deworming treatment . These results show that prevention of anaemia in women of child-bearing age with weekly IFA and regular deworming is feasible and effective over a prolonged period . However , long-term sustainability may be a major challenge in some settings in the absence of ongoing external support .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "invertebrates", "medicine", "and", "health", "sciences", "helminths", "tropical", "diseases", "hookworms", "parasitic", "diseases", "animals", "anemia", "research", "design", "nutrition", "ferritin", "neglected", "tropical", "diseases", "surveys", "research", "and", "analysis", "methods", "proteins", "iron", "deficiency", "hematology", "nutritional", "deficiencies", "biochemistry", "helminth", "infections", "iron", "deficiency", "anemia", "protein", "complexes", "survey", "research", "biology", "and", "life", "sciences", "soil-transmitted", "helminthiases", "organisms" ]
2017
Sustained effectiveness of weekly iron-folic acid supplementation and regular deworming over 6 years in women in rural Vietnam
Synonymous sites are generally assumed to be subject to weak selective constraint . For this reason , they are often neglected as a possible source of important functional variation . We use site frequency spectra from deep population sequencing data to show that , contrary to this expectation , 22% of four-fold synonymous ( 4D ) sites in Drosophila melanogaster evolve under very strong selective constraint while few , if any , appear to be under weak constraint . Linking polymorphism with divergence data , we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny . The function underlying the inferred strong constraint appears to be separate from splicing enhancers , nucleosome positioning , and the translational optimization generating canonical codon bias . The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression , particularly in the mid-late embryo , pupae , and adult developmental stages . Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways . Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila , the role of synonymous sites in genetic disease and adaptation should be reevaluated . As there are 64 codons and only 20 amino acids , most amino acids can be encoded by more than a single codon . Mutations that alter coding sequences ( CDS ) , but do not alter amino acid sequences are referred to as synonymous mutations . Synonymous sites are then the collection of potential synonymous mutations present in a gene . Predicated on the assumption that the CDS of a gene is simply the recipe for making the protein , synonymous mutations were long thought to have no functional effect , in other words to be “silent” and thus selectively neutral [1] , [2] . As a result , synonymous variation is often used as the neutral reference when measuring selection at functionally important , non-synonymous sites [3]–[7] . The observation of codon usage bias in many organisms was the first indication of possible functionality encoded by synonymous sites [8] , [9] . Different codons for the same amino acid are often utilized at unequal frequencies across the genome . Highly expressed genes and codons encoding functionally important amino acids generally display particularly biased patterns of codon usage [9]–[11] . This observation led to the theory that selection for translation optimization generates higher levels of codon bias [12]–[15] . In other words , it is thought that the speed and accuracy of mRNA translation is higher for a subset of codons , referred to as “optimal” ( “preferred” ) codons [14]–[19] . Such codons are translated more accurately and more efficiently because they are recognized by more abundant tRNA molecules with more specific anti-codon binding [14] , [20] , [21] . While this kind of selection acting on synonymous mutations is widely accepted , it is generally estimated to be weak - nearly , if not quite , neutral [22]–[31] . Synonymous variation is therefore still often thought to lack any major functional or evolutionary importance . In this paper , we further investigate the functionality of synonymous sites through detecting the action of purifying selection . If synonymous sites harbor highly deleterious variants under strong purifying selection , then that must change our view of the functional importance of synonymous sites and their potential role in genetic disease , as a possible source for adaptation , and as the neutral foil in tests for selection . Previous tests for selection on synonymous sites have often been consistent with the presence of weak purifying selection operating on synonymous variation . Using the rate of divergence between species , the signal of purifying selection comes from a lower number of inferred substitutions on a phylogenetic tree at sites allowing for synonymous mutations , compared to the expectation provided by a neutral reference . Simply comparing the rate of evolution between a test and a neutral reference set can be problematic when weak purifying selection and mutational biases interact [32] . Nonetheless , synonymous sites do indeed appear to evolve slower than expected under neutrality for many organisms in a manner seemingly consistent with weak selection [22] , [29]–[31] , [33]–[40] . More evidence for weak selection acting at synonymous sites comes from the study of polymorphism within species . Purifying selection reduces the frequency of deleterious alleles in the population . To measure its effect , the site frequency spectrum ( SFS ) tabulates the fraction of observed SNPs in all frequency classes across the sites of interest . The overabundance of low frequency SNPs relative to the neutral expectation is the signal of purifying selection operating on the test sites . From this signal , one can calculate the strength of the selective force and the proportion of the test sites it affects [41] , [42] . Such methods have been applied to studying the effects of selection on synonymous sites in a variety of Drosophila species , and have found evidence of weak selection - often favoring optimal codons [24]–[28] . Studies using divergence and polymorphism to infer selection as described above are , however , unable to detect the action of strong purifying selection . Tests that rely on divergence are limited in power to distinguish strong purifying selection from weak or moderate purifying selection . The problem lies in the efficacy of purifying selection ( constraint ) over a tree: a small , linear increase in the strength of constant purifying selection causes a large , exponential drop in the rate of evolution [43]–[45] . Weak to moderate constraint is thus capable of conserving sites over even large phylogenetic distances and increasing the number of species/tree length results in only a limited increase in power to distinguish strong from moderate or weak purifying selection [32] . Unlike tests on divergence that have difficulty distinguishing between strong and weak constraint , tests using the SFS of observed polymorphism can miss strong purifying selection entirely . While both weak and strong constraint eliminate variation from the population , strong selection does so far more efficiently . Therefore , at sites of strong constraint there are few SNPs and only at very low frequency in the population . Without sequencing enough members of a population to attain a deep sample , such SNPs will not be in the SFS of observed polymorphism . With no signal in the shape of the SFS from shallow population sequencing data , any strong selection acting on synonymous sites could not be detected via these methods . While strong selection does not significantly affect the shape of a shallow-sample SFS , the lack of polymorphism can itself be a powerful signal of the action of selection [46] , [47] . Knowing how many mutations should be present in the population sample , as compared to the amount actually present , can allow the estimation of the fraction of sites under strong selection . To do this , one needs a large sample of sites as the density of polymorphism is always low - on the order of a few percent . Differentiating between low densities in the test set and the neutral reference thus requires a large number of sites from each . Note that both weak purifying selection and lower rates of mutation can likewise cause a paucity of SNPs . Ultra-low frequency variants can distinguish the signal of strong constraint from that of a variation in the mutation rate between the neutral reference and the set of sites being tested . While mutational cold spots only lead to a lower number of SNPs , under strong purifying selection some mutations should still be observable at very low frequencies in a deep enough sample of the population . Weak selection , meanwhile , will affect the shape of the spectrum beyond the rare alleles and can be estimated from that . Combined , the lack of polymorphism and the excess of rare variants from a genome-wide , deep sample , could give the necessary power to quantify the intensity of the strong constraint and the fraction of sites it affects . Thus , our dataset needs to include both a wide sample of sites from the genome , as well as a deep sample from the population . The Drosophila Genetic Reference Panel ( DGRP ) for D . melanogaster provides such a dataset [48] . With 168 sequenced-inbred lines , this data set represents the whole genome ( thus providing us with the widest possible sample of sites from the genome ) . The data also provides a deep sample of the variation within the D . melanogaster population of North Carolina . Using DGRP polymorphism , we estimate that , contrary to long held expectations , a substantial fraction of the synonymous sites in D . melanogaster is evolving under strong selective constraint . The discovery of strong selection on codon usage in Drosophila should dramatically change our collective perspective on the functional and evolutionary significance of synonymous sites . Figure 1B shows the SFS for the SNPs in short introns and 4D sites from one bootstrap run . The shapes of the short intron and 4D spectra appear nearly identical . However , this similarity in the shapes of the spectra for 4D and short intron sites belies a large disparity in the density of polymorphism between the two sets . We measured the density of polymorphism in short intron and 4D sites and calculated the standard error of our measurement over 10 bootstrap runs . We find that 4D sites have approximately 22 . 1% ( +/−0 . 6% ) fewer segregating sites as compared to short introns ( Figure 1C ) . To account for the relative paucity of polymorphism in 4D sites when the spectra of 4D and short introns SNPs are so similar , we combined both facets of information in a maximum-likelihood method allowing for the effects of multiple selective forces and demography on polymorphism ( see Materials and Methods ) . We extended the SFS to include the number of non-polymorphic sites , the “zero”-frequency class , in our 4D and short intron bootstrap samples . Using such “amplitude” information along with the distribution of alleles over the observed frequency classes enables better maximum-likelihood estimation for parameters of strong selection . In this model , selection is parameterized by the effective selection coefficient 4Nes: where s is the selection coefficient and Ne is the effective population size of the organism . In our maximum-likelihood model , we used three categories of selection , neutral: 4Nes = 0 , weak purifying: |4Nes|<5 , strong purifying: |4Nes|>100 . The point estimates for the fraction of sites and the strength of constraint in each selection category can be seen in Table 1 . While there is no evidence of extant weak selection acting differentially on 4D sites and short introns , ∼22% of 4D sites are estimated to be under very strong constraint , 4Nes∼−283+/−28 . 3 ( standard error estimate by bootstrap ) . When a coarse-grained demographic correction was applied to the SFS we obtained results that , though quantitatively are somewhat different ( 4Nes∼−370 . 1+/−105 ) , are qualitatively similar in that for both cases 100<< |4Nes| <<700 – the calculable limit of our program ( see Text S1 ) . Exposing the action of the strong constraint on divergence between Drosophila species affirms the functional importance of these 4D sites across evolutionary history and reveals how these constrained synonymous sites evolve . If the strong constraint at 4D sites we identified within D . melanogaster has been constant across Drosophila , we would expect it to result in the complete conservation of the constrained 4D sites . If , on the other hand , the strong constraint is not constant and there is functional turnover at these sites , then we would expect to see substitutions occurring even at constrained sites along the Drosophila species tree . In order to compare the divergence between species to the constraint within a species , we considered only those 4D sites in amino acids conserved across the twelve Drosophila species from D . melanogaster to D . grimshawi . This simplifies the analysis as only the synonymous third position of the codon has been allowed to change over time . Thus , we can focus solely on the evolution of the synonymous site itself rather than consider the evolution of the entire codon . Figure 1C shows that the conservation of the amino acid has no bearing on the fraction of missing polymorphism in 4D sites . As such , the 4D sites of conserved amino acids provide a representative sample with which to study the strong constraint over the evolution of all 4D sites . The gene orthologs in the other species were obtained from the 12 Drosophila Genome Consortium data realigned by PRANK [53] , [68] , [69] . We used the established 12 Drosophila species tree and re-estimated the branch lengths on the aligned 4D sites with PhyML ( see Materials and Methods ) [70] . From these alignments we removed the sequences belonging to D . melanogaster and D . willistoni . The D . melanogaster sequences were removed because the polymorphism data was extracted from this species and we wished to avoid a false concordance between the results from polymorphism and divergence . The D . willistoni sequences were removed , because the branch length leading to D . willistoni is long and the codon bias of D . willistoni is significantly different than from the rest of the twelve Drosophila species [71] . Having removed these species , the expected number of substitutions over the now ten Drosophila species tree for synonymous positions in otherwise conserved four-fold amino acids is estimated by PhyML at 3 . 1 subs/site [70] . To obtain site-wise estimates of conservation , we then inferred the number of substitutions along this tree for each 4D site independently using GERP ( see Materials and Methods ) [72] , [73] . Figure 2 shows that the percentage of sites under strong constraint declines monotonically as the rate of evolution increases . 40 . 8% ( +/−1 . 9% ) of completely conserved sites ( 0 substitution class ) , and only 7 . 1% ( +/−3 . 0% ) of the fastest evolving sites ( ≥9 . 3 substitution class ) are predicted to be under strong constraint . This difference in the amount of constraint between fast and slow-evolving sites allowed us to carry out a further control for any variation in mutation rate between short introns and 4D sites . We carried out an identical bootstrap procedure but pairing slow-evolving 4D sites with neighboring fast-evolving 4D sites instead of short introns as a neutral reference . We recapitulated our result of strong constraint at 4D sites by using slow- versus fast-evolving 4D sites ( see Text S2C ) . This correlation between a 4D site's conservation across species and strong constraint within a species underscores the functional importance of these synonymous positions over the evolutionary history of the Drosophila clade . However , over 80% of the sites currently under strong constraint in D . melanogaster fall outside the 0 substitution class , i . e . are not conserved across the ten Drosophila species . Indeed , over 11% of 4D sites under strong constraint in D . melanogaster have each acquired 6 . 2 or more substitutions over the tree , evolving quickly at more than twice the average rate . As even a moderate amount of selection results in complete conservation if it has been consistent over the tree , this suggests there has been functional turnover at these functionally important synonymous sites . Codon bias is generally thought to be the product of background substitution biases combined with a weak selective force within genes skewing codon usage towards optimal ( preferred ) codons to increase translation efficiency and accuracy [19] . In Drosophila , translationally preferred codons are always G- or C-ending ( except for in D . willistoni ) [71] . The five four-fold degenerate amino acids have the following preferred codons: Alanine - GCC; Glycine - GGC; Proline - CCC; Threonine - ACC; and Valine - GTG [71] . Selection for codon bias is thus likely responsible for driving the GC content of 4D synonymous sites in D . melanogaster to 64% and to over 67% in the 4D sites of amino acids conserved over the 12 Drosophila species . While codon bias increases in conserved amino acids [17] , as stated above , the strong selection at synonymous sites inferred in this paper does not ( Figure 1C ) . To explore the relationship between codon bias and the strong constraint , we measured the fraction of sites under strong constraint within each codon , in unpreferred versus preferred codons conserved from D . sechellia-D . grimshawi , and across genes ranked by codon bias . Table 3 summarizes our analyses of how the extent of strong constraint is influenced by different genic features such as gene length , the location of the synonymous site along the gene , the chromosome on which the gene is located , whether or not the synonymous site falls within splice junctions , and nucleosome binding . Many of the associations below , while suggestive , are marginal in effect . The dominant pattern is that strong constraint at synonymous sites appears to be ubiquitous across different gene classes and functional elements within genes . To map how strong constraint at synonymous sites varies with gene expression over development , we ranked genes by their expression levels at each developmental time point in the ModEncode data set [84] . We split the genes evenly into three categories of expression - highly , moderately , and lowly expressed - within each developmental stage and ran 10 bootstraps for the 4D sites of the genes within each expression category in each developmental time point . The results are shown in Figure 5 . The overall gene expression level across development correlates well with the fraction of sites under strong constraint with lowly expressed genes tending to have fewer sites under strong constraint and highly expressed genes tending to have more sites under strong constraint . This pattern is strongest for the genes expressed highly in mid-late embryos , pupae , and adult males . The association of strong constraint with these developmental stages is further enhanced when the “high” expression group has been split in half into “high” and “very high” expression level categories ( see Figure S2 ) . In contrast to this preference of strong selection for genes highly expressed in embryo , pupal , and adult stages , codon bias is highest for genes whose expression peaks in larval stages [85] . The difference in density of polymorphism between 4D sites and short introns does not allow for precise measurements of constraint on the synonymous sites of single genes . To identify a set of genes that are under particularly strong constraint at synonymous sites , we ranked genes by the fraction of their conserved amino acids that are unpreferred and conserved from D . sechellia to D . grimshawi , in the 0-substitution class ( see Materials and Methods ) . Our method left 4 , 877 genes capable of being ranked of which we took the top sixth ( 812 genes , see Dataset S1 ) as our gene set enriched for strong constraint . To validate our method of selecting genes under strong constraint , we checked that our 812-gene set is indeed enriched for strong constraint at 4D sites . We performed a bootstrap analysis on the 4D sites of variable amino acids in the genes in and out of this top set . Estimating constraint using 4D sites from variable amino acids provides a measure of the fraction of synonymous sites under constraint independent from our surrogate using conserved amino acids . In the top 812 genes , we find a ∼30% reduction in polymorphism at 4D sites in variable amino acids; in all 4 , 065 genes not in the top 812 set , we find an average of ∼21% of 4D sites in variable amino acids under strong constraint . As such , our top 812 genes are enriched for almost 50% more 4D sites under strong constraint than the average gene . Note that any individual gene in the 812-set does not necessarily have elevated levels of strong constraint at its synonymous sites , nor does any individual gene of the 4 , 065 necessarily have a lower fraction of 4D sites under strong constraint . In order to examine whether genes under strong constraint at synonymous sites tend to be enriched for certain functions , we used DAVID 6 . 7 [86] , [87] . DAVID takes all the genes in the background data set ( 4 , 877 genes ) and all genes in the test data set ( 812 genes ) and looks for the enrichment of biological terms and gene families in the test set relative to the background . In Table 4 , we list a subset of those biological terms found by DAVID's functional annotation clustering run on high stringency ( for full information on the top 13 clusters , see Table S3 ) . We find that in genes enriched for strong constraint , we co-enrich for many important functional gene sets . In particular , we co-enrich for genes critical in pupae-to-adult morphogenesis and in late embryogenesis . This finding is consistent with the result that genes expressed highly in late embryos , pupae , and adults have elevated levels of strong constraint at 4D sites . Many other functional classes important to the basic development and functioning of D . melanogaster appear to have a higher fraction of synonymous sites under strong constraint including: transcription factors , ribosomal genes , immunoglobulin genes , genes regulating gamete production – particularly oogenesis , cell-signaling genes – particularly synaptic transmission , and more . The strong constraint at synonymous sites in D . melanogaster measured in this paper represents a powerful force . We estimate that ∼22% of synonymous sites are experiencing , on average , a selective pressure between 4Nes ∼−250–−500 against deleterious mutations . This strength of selection is as strong or stronger as has been measured via population genetic techniques at any class of sites , including non-synonymous ones [46] , [47] . Mutations at strongly constrained synonymous sites should never rise above low frequency in the population and certainly will never fix , barring tight linkage to a very advantageous allele or a shift in the functional properties of the site . While detectable within a population , these mutations are effectively lethal over evolutionary time . We tested a number of controls to rule out the possibility that our observation of strong purifying selection results from other forces with possibly similar signals: A lower mutation rate , for example , can cause a signal indistinguishable from strong selection in polymorphism if the sample depth of the population is too shallow . To account for this , and at the same time account for any variation in the amount of linked selection between 4D sites and short intron sites , we used a bootstrap to control for GC content and distance between the 4D and short intron sites . We also performed bootstraps controlling for dinucleotide content between 4D and short intron sites and performed bootstraps pairing slow-evolving 4D sites against fast-evolving 4D sites as the neutral reference . Neither revealed a mutational force underlying the ∼22% drop in 4D polymorphism compared to short introns . As revealed by simulations , the finite estimate we obtained of the strength of strong selection is itself evidence against a mutational force being responsible for our signal , as mutational variation would behave like infinite selection on 4D sites . While we do not have the frequency depth from the population necessary to estimate a full distribution of selection coefficients for the strong constraint force , our point estimate of 4Nes ∼−283 for these 22% of sites is statistically significantly different from the value of 4Nes ∼−700 ( the computational limit of our program ) expected if the signal was due to variation in mutation rate . We also controlled for deviations from mutation-selection equilibrium affecting both the 4D and short intron site frequency spectra using a frequency-dependent correction . Such deviations include demography , shared ( linked ) selection between 4D sites and short introns , and our own approximations to the SFS . Controlling for these deviations resulted in a higher estimate of the strength of selection ( 4Nes∼−370 ) with larger error bars , but still significantly far from the boundary of 4Nes∼−700 . A constant influx of weakly advantageous alleles in coding sequences , as is expected to occur in D . melanogaster [60] , could affect variation at nearby 4D sites more than at short introns . The resulting genetic draft generated by adaptive substitutions in coding sequences would weaken the apparent intensity of purifying selection on 4D sites by bringing strongly deleterious alleles to higher frequencies , making our above estimates of selection intensity conservative [88] . Even so , strong selection , rather than a mutational difference , would still underlie our signal , as genetic draft cannot alter the frequency of synonymous mutations that are simply absent from the population . On the other hand , sweeps of weakly advantageous alleles in coding sequences could eliminate polymorphism in 4D sites more so than in short introns . Narrow selective sweeps in coding sequences reducing variation at otherwise neutral 4D sites is , however , an unlikely explanation for our observations . When comparing 4D sites from different substitution rate classes against each other , we found a signal of strong constraint at conserved 4D sites relative to fast-evolving 4D sites . As sweeps should not affect the overall substitution rate of linked sites , strong purifying selection on synonymous sites is the best explanation for the lack of polymorphism at 4D sites relative to short introns . Our ability to detect strong selection and differentiate it from other forces critically depends on the availability of deep and genome-wide population data . Previous data sets could only find weak or no constraint , thus always confirming our collective biological intuition that synonymous sites had little functional or evolutionary importance . In a shallower sample of even genome-wide data , the highly deleterious variants would be simply missing from the sample and there would be no power to distinguish strong selection from a variation in the rate of mutation . As an example , we simulated 4D sites evolving under the selective regime inferred from the real data ( 22% of sites at 4Nes = −283 ) but with only 60 instead of 130 homozygous strains . Attempting to re-estimate the strength of selection from such a shallow sample results in the observation of seemingly infinite selection operating on 22% of 4D sites . Simulating 60 strains under a scenario where neutral 4D sites have a 22% lower mutation rate than do short introns results in the same inference of infinite selection . Genome-wide , deep population data sets were not available before recently and thus strong constraint could never before be unambiguously detected at synonymous sites . Interestingly , the strong constraint in D . melanogaster appears to be a largely orthogonal force to canonical codon usage bias , favoring an overlapping , but different set of codons with subtly different gene targets . Codon bias increases as the conservation of amino acids increases , while the strong constraint targets the 4D sites of both conserved and variable amino acids equally . We further identified the codons under strong constraint and , for any given amino acid , the codon ( s ) with the highest fraction of sites under constraint were not necessarily the optimal codon . Other studies have likewise noted signals of selection favoring non-optimal codons in Drosophila [25] , [30] , [33] , [89] , [90] . Overall , preferred 4D sites do have greater amounts of strong constraint acting on them , but the strong selective force targets a substantial fraction of the unpreferred 4D sites as well . There is also a weak anti-correlation between genes with a high fraction of constraint and genes with high codon bias , which extends to various gene features . Long genes are associated with higher levels of strong constraint at 4D sites as opposed to shorter genes , in opposition to codon bias in Drosophila [15] , [81] . X-linked genes have a lower fraction of 4D sites under constraint than autosomal genes , wheras codon usage bias is stronger on the X [28] , [82] . While both codon bias and the fraction of 4D sites under strong constraint are correlated with highly expressed genes , codon usage bias is strongest in genes with their highest expression in larval stages [85] as opposed to the strong constraint seen most often in genes expressed highly in mid-late embryo , pupal , and male adult stages . The pattern of conservation over 4D sites supports the existence of weak selection in Drosophila favoring the conservation of preferred 4D sites across the twelve species , but it appears to have been relaxed in D . melanogaster . In our SFS analysis , we were not only able to gauge the intensity of strong selection , but also show a lack of contribution from weak purifying selection to our signal . If any weak selection is still acting differentially on synonymous sites relative to short introns , then it is not powerful enough to be detected by our SFS model or contribute much to our signal of lost polymorphism . These results recapitulate some earlier results on D . melanogaster [24] , although see [25]–[28] . While weak selection on 4D sites in D . melanogaster may not have vanished completely , the large influx of mutations and substitutions away from optimal codons corroborates some relaxation of constraint for codon bias in D . melanogaster [25] , [30] , [31] , [33] , [38] . Overall , weak selection for codon bias would seem to be less of a force on synonymous sites in D . melanogaster than in its sister species where weak selection for codon bias can be detected with far less ambiguity [24] , [30] , [31] , [33] , [34] , [40] . Thus , evidence suggests that there are at least two major , orthogonal forces affecting the evolution of 4D sites in Drosophila: the weak selective force driving codon bias that favors optimal codons , present in other Drosophila species , but relaxed in D . melanogaster; and an extant strong selective force targeting both optimal and non-optimal codons in D . melanogaster and across the Drosophila phylogeny . The function engendering the strong constraint appears to be independent of the translation optimization for efficiency and accuracy governing canonical codon usage bias . The presence of splicing enhancers and nucleosomes do not explain the pattern of strong purifying selection either . However , the function underlying the strong constraint of synonymous sites may yet prove to be acting at the level of gene regulation . Those genes where strong selection on synonymous sites acts most frequently are often highly expressed regulatory proteins , operating in essential , tightly controlled developmental pathways . These are genes where the regulation of gene expression will matter most . Regulation of gene expression may be acting at the level of mRNA structures , mRNA stability , miRNA binding sites , and the modulation of translation rate [91]–[104] . Choice of synonymous codons might affect all of these levels of gene regulation . It should be noted that these various hypotheses are not mutually exclusive and may be intertwined . mRNA structures - as well as their avoidance , especially near the start of ORFs - may be involved in translation initiation/elongation , modulation of mRNA half-life , and accessibility of the mRNA to proteins and miRNAs [98] , [99] , [103]–[105] . Indeed , signatures of selection have been associated both with mRNA accessibility and mRNA structures and overall folding energy [97] , [99] , [105] , [106] . Our initial analysis found no enrichment of conserved unpreferred codons , a first-pass marker of the action of the strong constraint described in this paper , in either structured or unstructured mRNA as determined by ds/ssRNA sequencing [107] ( not shown ) . This analysis , however , is at best preliminary and a strong possibility remains that the function underlying the strong constraint at synonymous sites is related to mRNA structure . miRNAs also have a host of different functional effects in different species and different genes within a species but are well known in their role of mRNA degradation [108] , [109] . The dynamics of translation not only affect the overall rate at which proteins are created , but also affect how these proteins fold and even the mRNA half-life [91]–[94] , [110]–[112] . The possibility that strong selection acts at the level of modulating translation rate through the presence of slow/fast sites is interesting as the translation speed of a codon is not necessarily related to codon optimality and tight control has been inferred at the beginning and end of ORFs in some species [96] , [100]–[102] , [113] , [114] . Given the pattern of the strong constraint across the different codons both optimal and non-optimal , the strong selective force may be due to the abundance of wobble vs . Watson-Crick tRNAs available for that codon . Ascertaining the functional mechanism underlying the observed strong constraint acting on synonymous sites could reveal deep insights into the regulation of gene expression . Regardless of the specific functional mechanism underlying the strong constraint , experimental evidence from a wide range of species substantiates an important functional role for synonymous sites . Directed mutagenesis studies targeting synonymous sites as well as studies of natural polymorphism have found consequential changes in protein levels and functionality due to natural synonymous variation and induced mutations [111]–[113] , [115]–[127] . In an experiment done on the Alcohol dehydrogenase ( Adh ) gene in D . melanogaster , changing 10 wild-type preferred Leucine alleles to unpreferred alleles in the 5′ region of the gene lowers the enzymatic activity of collected Adh by 25% [119] . The authors proposed that disruption of the sites' translational efficiency and accuracy caused the drop in activity , but also noted that the functional effect was far larger than expected given the assumption of only weak selection on synonymous sites [119] . ‘Humanized’ versions of protein coding sequences , with codons replaced with synonymous , putatively optimal codons in humans , show much greater protein expression and function when transfected into mammalian cells than the originals or synthetic versions using a non-mammalian species' set of optimal codons [115]–[118] . Human gene Multidrug Resistance 1 ( MDR1 ) contributes to the drug resistance of cancer cells [122] . Both naturally occurring alleles as well as induced novel mutations at synonymous sites in MDR1 affect the resulting protein's conformation , altering its substrate specificity in human cell lines [122] . In the E . coli gene ompA , exchanging eight frequently-used codons for synonymous infrequently-used codons near the gene start results in a 3-fold reduction in mRNA levels and a 10-fold reduction in synthesis of protein OmpA [112] . Meanwhile exchanging codons with low-abundance tRNAs to synonymous codons with high-abundance tRNAs in E . coli gene sufI - or increasing the abundance of those tRNAs - results in misfolding of the protein in vitro and in vivo [110] . What about the presence of strong constraint in the synonymous sites of other species ? In addition to the above functional assays , there are reported to be a significant fraction of synonymous sites under an unknown intensity of constraint in many species [22] , [29] , [35]–[37] , [39] , [97] , [128]–[130] and there is evidence for strong selection in humans [47] . For example , when compared to “neutral” controls , there is a reduction in polymorphism density and/or a lower rate of divergence at synonymous sites for many tetrapods including chicken , hominids , murids , and mammals in general [22] , [29] , [35]–[37] , [128] . Further , some of these species have undetectable or weak levels of codon bias , presumably commensurate with their small effective population sizes and thus the weakness of selection in favor of optimal codons [36] , [131] . Using a similar model to the one described in this paper , Keightley and Halligan ( 2011 ) found evidence to support that weak selection alone is unable to explain the pattern of diversity at 4D synonymous sites in humans [47] . While that study lacked the sample depth of polymorphism to be able to gauge the intensity of the strong selection , they estimated that 11% of 4D sites are evolving under a strong selection regime of |4Nes|>40 [47] . Our results from Drosophila with a deeper population sample lend credence to the hypothesis that , in humans too , a force of strong constraint is responsible for the lack of polymorphism at 4D sites rather than a mutational force or other confounding factors . For many species , there has been no conclusion that the constraint on their respective synonymous sites is strong , but many of the signals are consistent with what we find in Drosophila with the fraction of sites under constraint , the amount of missing polymorphism , and the lack of relationship to codon bias . Thus with genome-wide , deep population SNP data becoming available for many of these other species , we may well find strong selection on synonymous sites to be ubiquitous . As synonymous sites have often been used as the neutral reference in tests for purifying and adaptive selection , many estimates of the fraction of sites under constraint in other classes , such as non-synonymous sites , UTRs , and many others , are likely to be conservative . This result from population genetics supports findings that synonymous sites may harbor many , important causal variants and that studies ignoring the potential contribution of synonymous mutations may be likewise unnecessarily conservative [91] . Turnover at these strongly constrained synonymous sites could also represent a significant source of interspecies functional divergence and adaptation . The potential of synonymous sites to be sources of adaptation and genetic disease merits further investigation . Although the functionality underlying this strong constraint remains unknown , recent studies have uncovered a myriad of different types of functional information encoded into the CDS of genes beyond the protein recipe , including controls for translational efficiency and accuracy , splicing enhancers , micro-RNA binding , nucleosome positioning , and more . With the discovery of a significant fraction of sites under strong constraint in Drosophila , two things become clear: the role of synonymous sites in the biology of genomes is far greater than the neutral , “silent” part they were once assumed to play; and we still have much to learn about the functionality encoded in genes . The SNP data set from DGRP ( http://dgrp . gnets . ncsu . edu/data/ ) consists of 168 inbred lines from a population of North Carolina D . melanogaster [48] . The SNPs were annotated as synonymous , non-synonymous , and intronic using Flybase release 5 . 33 ( ftp://ftp . flybase . net/genomes/Drosophila_melanogaster/dmel_r5 . 33_FB2011_01/ ) [132] . If a position was found in multiple gene annotations , only those sites where the SNP was synonymous in all sites was called synonymous . Short intron sites are defined as those sites falling in introns of less than length 86 bp , 16 bp away from the intron start and 6 bp away from the intron end in order to eliminate any functional sequences at the edges of the introns [52] . Eliminating 16 bp from each side did not change SNP density ( not shown ) . Any remaining purifying selection , especially strong purifying selection , in short introns makes our results more conservative . Four-fold ( 4D ) sites are the collection of 3rd codon positions for the following amino acids: Proline , Alanine , Threonine , Glycine , and Valine . All sites were resampled to a depth of 130 strains . All sites with sequence information for fewer than 130 strains were excluded . For SNPs at sites with more than 130 strains or which contained heterozygous lines at that position , a 130 allele subset was chosen randomly . If the SNP was no longer polymorphic after this random resampling , that position was moved into the non-polymorphic site class . We also removed any position with more than 2 alleles present . We restricted our analysis to genes with 1–1 orthologs across the 12 Drosophila species tree [53] and where the longest transcript annotation had remained intact in release 5 . 33 - even if it is no longer the longest transcript in release 5 . 33 . We used the remaining 5 , 709 coding sequences aligned with PRANK from Markova-Raina and Petrov ( 2011 ) [68] , [69] . To determine the distribution of selective effects on a group of sites based on the shape and the amplitude of the SFS , we assume a two-state framework where sites are either monomorphic in the wild-type state or polymorphic with a neutral or deleterious mutation at some observed frequency in the population . Using short introns as a neutral reference , our model aims to capture the fraction of synonymous sites falling into three broad selection categories – those with neutral , weakly deleterious , or strongly deleterious mutations – and estimate the effective selection coefficients acting on those mutations . Strong constraint can be difficult to capture as strong selection has a greater effect on the amplitude of the SFS , the total number of observed mutations , than on its shape , the frequency distribution of observed mutations . Using a similar expansion to the standard SFS to Keightly and Eyre-Walker ( 2007 ) [46] , we add the zero-frequency class , the fraction of monomorphic sites , to the SFS . The SNP density provides the additional information necessary to infer the action of strong constraint . Equal to 4Neμ , θ is mutation rate scaled by the effective population size and determines the neutral SNP density . The short intron SFS , used as neutral reference , anchors our estimate of θ which in turn allows us to estimate the amount of missing synonymous polymorphism in each selection category , c . As purifying selection increases , the overall density of observed polymorphism is reduced in the fraction of 4D sites in that selection class and the expected distribution of mutation is further skewed towards rare frequencies in the population . Each category has a single selection parameter , γc , a point estimate of the effective strength of selection , 4Nes , operating on the 4D sites in that class . For those 4D sites in the neutral category , γc = 0 . For those in the weakly deleterious category , 0<|γc|<5 . For those in the strongly deleterious category , |γc|>5 or 100 – the choice of boundary did not affect results . For our sample of n chromosomes from the population , assuming mutation-selection balance , we have the following analytical prediction for the SFS , g ( x ) – the expected fraction of 4D sites with SNPs at frequency x in the sample [43]: ( 1 ) ( 2 ) g ( x , c ) is the contribution of each selection category to the overall SFS . L is the total number of 4D sites while fc is the fraction of 4D sites in each selection category c . ( 3 ) ( 4 ) g ( 0 ) are the zero-frequency class , monomorphic , sites and are what gives the SFS “amplitude” information – the density , rather than just the shape , of the spectrum . While m is the total number observed SNPs in the sample . The theoretical SFS for intronic sites is the same as above , only all sites are assumed to be neutral . However , any real SFS does not reflect the true frequency distribution of the SNPs in the population , but rather a binomial sampling of those SNPs and frequencies . The above is thus an approximation , as the probability of a site with a SNP at a given frequency in the sample from the population is not quite the same as the probability of a site with a SNP at a given frequency in the population as a whole . However , it is much more computational efficient for both speed and memory to use the approximation . With this theoretical prediction of the distribution of sites over each frequency class in both the neutral reference ( short intron SFS ) and test set of sites ( 4D SFS ) , we can use maximum-likelihood to fit the parameters of our model to real data sets . Our model has 5 free parameters: θ , ( γweak , γstrong ) , and ( fneutral , fweak , fstrong ) where fneutral = 1-fweak -fstrong . The total likelihood , λ , of the model's fit to the data , D , is equal to product of the fit the short intron and 4D sites spectra: ( 5 ) λ4D and λSI are the likelihood of the observed SFS given the expected SFS as determined by the free parameters and equations ( 1 ) – ( 4 ) . These likelihoods are the multinomial probability of observing a certain number of sites , k , with SNPs in frequency class x in the sample given theoretical expectations . Taking short intron sites as an example ( same for both ) : ( 6 ) Equation ( 6 ) is thus the probability that the folded theoretical SFS , g ( x ) , matches the empirical folded SFS , kx . We folded the spectrum to avoid any problems with inferring the ancestral state . We then maximized the parameters θ , ( fneutral , fweak , fstrong ) , and ( γweak , γstrong ) in Matlab using fminsearch , an implementation of the Nelder-Mead simplex method [133] , on the negative log-likelihood of λfull . The observed spectra were obtained from the bootstrapped 4D and short intron pairs . Where simulations were needed in this study , theoretical spectra were calculated using the above equations ( 1 ) – ( 4 ) and then the parameters were re-estimated by the outlined maximum-likelihood procedure on those theoretical spectra acting in place of the empirical data . We used the determined 15 species Insect tree topology from the UCSC genome browser ( http://hgdownload . cse . ucsc . edu/goldenPath/dm3/phastCons15way/ ) and paired it down to the 12 Drosophila species [134] . We then input that tree topology into PhyML v3 . 0 ( http://www . atgc-montpellier . fr/phyml ) [70] and allowed it to re-estimate the branch lengths on all 4D sites in conserved amino acids using the HKY85 model [135] without a discrete gamma model and without invariant sites . The nucleotide frequencies and transition-transversion rate ratio were inferred by maximum-likelihood . The resulting tree can be found in Text S4 . GERPcol from GERP++ ( http://mendel . stanford . edu/SidowLab/downloads/gerp/ ) [73] was run on the collection of all 4D sites from all 12 Drosophila species excluding D . melanogaster and D . willistoni , estimating the Rscore ( tree length - inferred # of substitutions ) for each site independently . We input into GERP the tree and transition-transversion ratio from the PhyML results . As these two programs use different parameterizations of the transition-transversion ratio , we translated one to the other ( see Text S4 ) . Our signal from polymorphism does not afford us a precise measurement of constraint on the 4D sites of a single gene ( not enough information ) . Therefore , we use a surrogate to infer the amount of strong constraint at the 4D sites of individual genes . Looking only at sites without SNPs , we use the percentage of 4D sites in conserved amino acids that are unpreferred and themselves conserved from D . sechellia to D . grimshawi ( i . e . in the 0-substitution class ) as our measure of how extensive the strong constraint has been on the 4D sites of the gene in question . As unpreferred 4D sites in the 0-substitution class have the highest fraction of sites under strong constraint ( 53% ) , the reasoning is that the more such sites exist in a gene , the more likely there has been extensive constraint acting on all 4D sites . Since not all genes have enough conserved amino acids to allow a reasonable calculation of the above surrogate , we used only those genes where at least 20% of the four-fold amino acids were conserved along the tree , leaving 4 , 877 genes in the analysis . We ranked genes by this surrogate and took the top 812 genes ( ∼ top sixth of genes ) . We then used the functional annotation clustering tool from DAVID 6 . 7 ( http://david . abcc . ncifcrf . gov/home . jsp ) set on high stringency to look for enrichment of GO category terms in this gene set [86] , [87] .
Synonymous mutations do not alter the sequence of amino acids encoded by the gene in which they occur . These synonymous mutations were thus long thought to have no effect on the function of the ensuing protein or the fitness of the organism . At four-fold degenerate sites , every possible mutation is synonymous . For this reason , they are often neglected as a possible source of important functional changes . Using a deep sampling of the variation within a population of the fruit fly Drosophila melanogaster , we show that , contrary to this expectation , 22% of synonymous mutations at four-fold degenerate sites are strongly deleterious to the point of absence in the Drosophila population . The underlying biological function disrupted by these mutations is unknown , but is not related to the forces generally believed to be the principal actors shaping the evolution of synonymous sites . Genes with many such possible deleterious synonymous mutations tend to be particularly functionally important , highly expressed , and often involved in key developmental pathways . Given that the observed functional importance of synonymous sites is likely not limited to Drosophila , the role of synonymous sites in genetic disease and adaptation should be reevaluated .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "mutation", "genetic", "polymorphism", "natural", "selection", "gene", "expression", "genetics", "population", "genetics", "biology", "evolutionary", "biology" ]
2013
Strong Purifying Selection at Synonymous Sites in D. melanogaster
As single-cell RNA-sequencing ( scRNA-seq ) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased . Navigating the vast sea of tools now available is becoming increasingly challenging for researchers . In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database ( www . scRNA-tools . org ) to catalogue and curate analysis tools as they become available . Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform . Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data . We see that many tools perform tasks specific to scRNA-seq analysis , particularly clustering and ordering of cells . We also find that the scRNA-seq community embraces an open-source and open-science approach , with most tools available under open-source licenses and preprints being extensively used as a means to describe methods . The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records the growth of the field over time . Single-cell RNA-sequencing ( scRNA-seq ) has rapidly gained traction as an effective tool for interrogating the transcriptome at the resolution of individual cells . Since the first protocols were published in 2009 [1] the number of cells profiled in individual scRNA-seq experiments has increased exponentially , outstripping Moore’s Law [2] . This new kind of transcriptomic data brings a demand for new analysis methods . Not only is the scale of scRNA-seq datasets much greater than that of bulk experiments but there are also a variety of challenges unique to the single-cell context [3] . Specifically , scRNA-seq data is extremely sparse ( there is no expression measured for many genes in most cells ) , it can have technical artefacts such as low-quality cells or differences between sequencing batches and the scientific questions of interest are often different to those asked of bulk RNA-seq datasets . For example many bulk RNA-seq datasets are generated to discover differentially expressed genes through a designed experiment while many scRNA-seq experiments aim to identify or classify cell types in complex tissues . The bioinformatics community has embraced this new type of data at an astonishing rate , designing a plethora of methods for the analysis of scRNA-seq data . Keeping up with the current state of scRNA-seq analysis is now a significant challenge as the field is presented with a huge number of choices for analysing a dataset . Since September 2016 we have collated and categorised scRNA-seq analysis tools as they have become available . This database is being continually updated and is publicly available at www . scRNA-tools . org . In order to help researchers navigate the vast ocean of analysis tools we categorise tools in the database in the context of the typical phases of an scRNA-seq analysis . Through the analysis of this database we show trends in not only the analysis applications these methods address but how they are published and licensed , and the platforms they use . Based on this database we gain insight into the current state of current tools in this rapidly developing field . The scRNA-tools database contains information on software tools specifically designed for the analysis of scRNA-seq data . For a tool to be eligible for inclusion in the database it must be available for download and public use . This can be from a software package repository ( such as Bioconductor [4] , CRAN or PyPI ) , a code sharing website such as GitHub or directly from a private website . When new tools come to our attention they are added to the scRNA-tools database . DOIs and publication dates are recorded for any associated publications . As preprints may be frequently updated they are marked as a preprint instead of recording a date . The platform used to build the tool , links to code repositories , associated licenses and a short description are also recorded . Each tool is categorised according to the analysis tasks it can perform , receiving a true or false for each category based on what is described in the accompanying paper or documentation . We also record the date that each entry was added to the database and the date that it was last updated . Most tools are added after a preprint or publication becomes available but some have been added after being mentioned on social media or in similar collections such as Sean Davis’ awesome-single-cell page ( https://github . com/seandavi/awesome-single-cell ) . To build the website we start with the table described above as a CSV file which is processed using an R script . The lists of packages available in the CRAN , Bioconductor , PyPI and Anaconda software repositories are downloaded and matched with tools in the database . For tools with associated publications the number of citations they have received is retrieved from the Crossref database ( www . crossref . org ) using the rcrossref package ( v0 . 8 . 0 ) [5] . We also make use of the aRxiv package ( v0 . 5 . 16 ) [6] to retrieve information about arXiv preprints . JSON files describing the complete table , tools and categories are produced and used to populate the website . The website consists of three main pages . The home page shows an interactive table with the ability to sort , filter and download the database . The second page shows an entry for each tool , giving the description , details of publications , details of the software code and license and the associated software categories . Badges are added to tools to provide clearly visible details of any associated software or GitHub repositories . The final page describes the categories , providing easy access to the tools associated with them . Both the tools and categories pages can be sorted in a variety of ways , including by the number of associated publications or citations . An additional page shows a live and up-to-date version of some of the analysis presented here with visualisations produced using ggplot2 ( v2 . 2 . 1 . 9000 ) [7] and plotly ( v4 . 7 . 1 ) [8] . We welcome contributions to the database from the wider community via submitting an issue to the project GitHub page ( https://github . com/Oshlack/scRNA-tools ) or by filling in the submission form on the scRNA-tools website . The most recent version of the scRNA-tools database as of 6 June 2018 was used for the analysis presented in this paper . Data was manipulated in R ( v3 . 5 . 0 ) using the dplyr package ( v0 . 7 . 5 ) [9] and plots produced using the ggplot2 ( v2 . 2 . 1 . 9000 ) and cowplot ( v0 . 9 . 2 ) [10] packages . When the database was first constructed it contained 70 scRNA-seq analysis tools representing the majority of work in the field during the three years from the publication of SAMstrt [11] in November 2013 up to September 2016 . In the time since then over 160 new tools have been added ( Fig 1A ) . The almost tripling of the number of available tools in such a short time demonstrates the booming interest in scRNA-seq and its maturation from a technique requiring custom-built equipment with specialised protocols to a commercially available product . Single-cell RNA-sequencing is often used to explore complex mixtures of cell types in an unsupervised manner . As has been described in previous reviews a standard scRNA-seq analysis in this setting consists of several tasks which can be completed using various tools [13–17] . In the scRNA-tools database we categorise tools based on the analysis tasks they perform . Here we group these tasks into four broad phases of analysis: data acquisition , data cleaning , cell assignment and gene identification ( Fig 2 ) . The data acquisition phase ( Phase 1 ) takes the raw nucleotide sequences from the sequencing experiment and returns a matrix describing the expression of each gene in each cell . This phase consists of tasks common to bulk RNA-seq experiments , such as alignment to a reference genome or transcriptome and quantification of expression , but is often extended to handle Unique Molecular Identifiers ( UMIs ) [18] . Once an expression matrix has been obtained it is vital to make sure the resulting data is of high enough quality . In the data cleaning phase ( Phase 2 ) quality control of cells is performed as well as filtering of uninformative genes . Additional tasks may be performed to normalise the data or impute missing values . Exploratory data analysis tasks are often performed in this phase , such as viewing the datasets in reduced dimensions to look for underlying structure . The high-quality expression matrix is the focus of the next phases of analysis . In Phase 3 cells are assigned , either to discrete groups via clustering or along a continuous trajectory from one cell type to another . As high-quality reference datasets become available it will also become feasible to classify cells directly into different cell types . Once cells have been assigned the focus of analysis turns to interpreting what those assignments mean . Identifying interesting genes ( Phase 4 ) , such as those that are differentially expressed across groups , marker genes expressed in a single group or genes that change expression along a trajectory , is the typical way to do this . The biological significance of those genes can then be interpreted to give meaning to the experiment , either by investigating the genes themselves or by getting a higher-level view through techniques such as gene set testing . While there are other approaches that could be taken to analyse scRNA-seq data these phases represent the most common path from raw sequencing reads to biological insight applicable to many studies . An exception to this may be experiments designed to test a specific hypothesis where cell populations may have been sorted or the interest lies in differences between experimental conditions rather than cell types . In this case Phase 3 may not be required , and slightly different tools or approaches may be used , but many of the same challenges will apply . In addition , as the field expands and develops it is likely that data will be used in new ways to answer other biological questions , requiring new analysis techniques . Descriptions of the categories in the scRNA-tools database are given in Table 1 , along with the associated analysis phases . The scRNA-tools databases is publicly accessible via the website at www . scRNA-tools . org . Suggestions for additions , updates and improvements are warmly welcomed at the associated GitHub repository ( https://github . com/Oshlack/scRNA-tools ) or via the submission form on the website . The code and datasets used for the analysis in this paper are available from https://github . com/Oshlack/scRNAtools-paper .
In recent years single-cell RNA-sequencing technologies have emerged that allow scientists to measure the activity of genes in thousands of individual cells simultaneously . This means we can start to look at what each cell in a sample is doing instead of considering an average across all cells in a sample , as was the case with older technologies . However , while access to this kind of data presents a wealth of opportunities it comes with a new set of challenges . Researchers across the world have developed new methods and software tools to make the most of these datasets but the field is moving at such a rapid pace it is difficult to keep up with what is currently available . To make this easier we have developed the scRNA-tools database and website ( www . scRNA-tools . org ) . Our database catalogues analysis tools , recording the tasks they can be used for , where they can be downloaded from and the publications that describe how they work . By looking at this database we can see that developers have focused on methods specific to single-cell data and that they embrace an open-source approach with permissive licensing , sharing of code and release of preprint publications .
[ "Abstract", "Introduction", "Design", "and", "implementation", "Results", "Availability", "and", "future", "directions" ]
[ "data", "acquisition", "engineering", "and", "technology", "rna", "analysis", "molecular", "biology", "techniques", "research", "and", "analysis", "methods", "computer", "and", "information", "sciences", "gene", "expression", "molecular", "biology", "molecular", "biology", "assays", "and", "analysis", "techniques", "programming", "languages", "data", "visualization", "source", "code", "database", "and", "informatics", "methods", "nucleic", "acid", "analysis", "software", "engineering", "genetics", "biology", "and", "life", "sciences", "software", "tools" ]
2018
Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database
In recent years there has been growing availability of individual-level spatio-temporal disease data , particularly due to the use of modern communicating devices with GPS tracking functionality . These detailed data have been proven useful for inferring disease transmission to a more refined level than previously . However , there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner . Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level . In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density . Our methodology is first tested using simulated datasets , validating our inferential machinery . The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa ( 2014-2015 ) . Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature , while revealing a significantly shorter distance of transmission . More importantly , in contrast to existing approaches , we are able to perform a more general model prediction that takes into account the susceptible population . Finally , our results show that , given reasonable scenarios , the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging . Epidemiological data collected by traditional public health surveillance often contain relatively coarse spatial and temporal information on infected individuals . In recent years , the amount and resolution of the spatio-temporal data have increased vastly due to the advent of ‘digital epidemiology’ along with the increased use of modern communication devices [1] , particularly through the use of mobile phones which drastically improves the tracking of human contacts [2–4] . Such data provide unprecedented opportunities for dissecting disease spread at a more localized , individual-to-individual level . The recent West Africa Ebola outbreak ( Fig 1 ) well demonstrated the increasing availability of such data , and , in particular , the GPS location data collected during the outbreak have been shown to be useful in identifying superspreaders and quantifying the impact of superspreading during the outbreak [4] . However , the growing availability of these more precise spatio-temporal data has not been accompanied by development of statistically sound mechanistic frameworks for modelling the underlying individual-to-individual transmission process . Developing such methods is an essential step for systematically extracting maximal information from such data , in particular , evaluating the efficacy of individually-targeted control strategies and enabling forward epidemic prediction at the individual level . Conventional compartmental models ( e . g . SEIR ) require an explicit account of the complete contact process which specifies both the successful contacts ( i . e . the infected in class E ) , and , more challengingly [6] , the unsuccessful contacts ( i . e . who has remained susceptible in class S ) . Representing unsuccessful contacts at the individual level is computationally challenging due to the need to build an explicit contact network among essentially all individuals in the population . One may consider adapting mechanistic compartmental disease models to accommodate these data . Important examples of these approaches include: 1 ) a patch-level approach that aggregates data points within pre-defined grids/patches [7–9] , and 2 ) a transmission-network-based approach which is essentially a partial-likelihood approach that considers only the infected individuals and ignores the unsuccessful contacts [4 , 10–12] . Fig 2 presents a schematic illustration of these two approaches . Although the patch-level approach conforms to the desirable SEIR-type mechanistic framework , in which both the successful infectious contacts ( E ) and unsuccessful contacts ( S ) are represented , at least on the patch level , the aggregation of data points can be arbitrary and it inevitably degrades the data resolution necessary for inferring , for example , the individual-to-individual transmission . The transmission-network-based ( partial-likelihood ) approach , on the other hand , preserves the ‘point nature’ of the data but fails to conform to the mechanistic framework by completely ignoring the general ( susceptible ) population and its relation to the infected class . Although the latter has been shown to be useful for sampling the relations among infections ( e . g . the transmission tree ) , it is inadequate for the purposes of complete forward epidemic prediction which needs to take into account the general ( susceptible ) population [4] . Spatio-temporal point processes ( see an introduction in [5] ) may also appear to be natural candidates for individual spatial data . However , it is not straightforward to integrate them with a mechanistic compartmental disease model such as the SEIR ( Susceptible-Exposed-Infectious-Recovered ) model . In particular , it is difficult to formulate conditional intensities for a spatio-temporal point process directly for the observations that respects the mechanistic modelling assumptions . If one observes the transitions made by individuals from the E to I classes and from the I to R classes then it may be natural to consider a marked spatio-temporal point process where points represent the transitions from E to I and marks quantify the subsequent sojourn time in the I class . Calculation of intensities conditional on the observation history , necessary for the construction of the likelihood , is difficult due to the transitions from E to I being unobserved . Other approaches which do not utilize the full likelihood ( e . g . , contact-type partial-likelihood approach [13 , 14] and likelihood-free ABC approach [15] ) may also be pursued . There also have been advances for more efficient parameters inference of certain classes of spatial models—for example , [16] proposes a double Metropolis-Hastings sampler for certain spatial models with intractable normalizing constants . Nevertheless , there is still a need of developing new statistical frameworks which allow for both full-likelihood-based model inference and , importantly , a statistically and biologically interpretable forward-prediction machinery that naturally integrates with mechanistic disease models and the general susceptible population . In this paper , we develop a framework that aims to accommodate individual-level spatio-temporal data , both in a mechanistic manner and accounting for the general ( susceptible ) population . The approach taken can be viewed as being rooted in spatio-temporal point processes . In essence , we view the process of transmission ( transitions from S to E ) as a marked spatio-temporal point processes where the marks are bivariate and specify the subsequent sojourn times in the E and I classes for the respective exposed individual . For this formulation the conditional intensity becomes tractable as described in Model and Methods . We then exploit ideas that are standard in Bayesian computation—in particular data augmentation—to accommodate the lack of observation of transmission events . We focus on epidemic outbreaks that are mainly attenuated by a time-varying transmissibility e . g . due to controls or seasonal changes of transmissibility , which is also the case for the recent West Africa Ebola outbreak [17 , 18] . We also allow the occurrence of infections to be moderated both by the distance dependency of spatial infectivity and the effect of spatially heterogeneous ( susceptible ) population density . Such a framework enables a machinery that can be used to infer system parameters from the history of outbreaks and , more importantly , to predict the future dynamics of an epidemic . Our work represents a key generalization and extension of the work in [4 , 19] , notably by accounting for the effect of heterogeneous population density and considering a broader class of disease models . Our methodology is first tested using simulated examples . We also compare our framework with the conventional , and often computationally challenging , individual-based SEIR model ( which takes into account each individual in the population explicitly ) . Finally , it is applied to the Ebola outbreak data ( Fig 1 and Ebola Outbreak Data ) , demonstrating its relevance to realistic epidemics of major current importance . We model spatio-temporal transmission , in continuous time and space and over a heterogeneous landscape with varying population density . The framework we apply to model transmission is closely related to the contact distribution model [20] . Consider the situation where there are n ( t′ ) infectious individuals at time t′ among an entirely susceptible population . A new infection occurs as the first event in a non-homogeneous Poisson process with a time-varying rate n ( t′ ) × β ( t ) with β ( t ) = β × exp ( - ω t ) , ( 1 ) for t ≥ t′ , where β represents the baseline transmissibility ( i . e . the baseline intensity ) of an infectious individual in the absence of control measures . Multiple-level baseline transmissibility βi , i = 1 , 2 , … may also be considered , for example , to represent heteregeneous transmissibility among different age groups ( see later Example: Application to the Ebola Outbreak Data ) . The parameter ω quantifies the efficacy of controls that serves to reduce disease transmissibilty [21 , 22] . Note that primary/background infection can be accommodated by adding a permanent infectious source presenting an additional rate α ( i . e . the total Poisson rate becomes α + β × exp ( −ωt ) ) . The source of infection of the newly infected/exposed individual is randomly chosen from the n ( t′ ) infectious individuals . It is assumed that the probability of the new infection being at a certain distance r and direction θ away from the source of infection , is determined by the movement patterns of infectious individuals and the density of the susceptible population . Specifically , G = ( r , θ ) is drawn from a density , g ( G ; η , s ^ ) = f ( r ; η ) × h ( θ | r , s ^ ) , ( 2 ) where s ^ is the population density across the study area . Following Eq 2 , the distance r is first drawn from f ( r; η ) , a monotonically decreasing density function that specifies the likelihood of spatial movement over distance [23–25] . Specifically , we assume r follows an Exponential ( η ) distribution , i . e . , f ( r ; η ) = η × exp ( - η r ) . ( 3 ) Given r , the position of the new infection is determined by a subsequent random draw θ from h ( θ | r , s ^ ) , the density of θ corresponding to the circle with radius r centered at the source of infection . When population density is homogeneous , θ may be drawn uniformly from 0 to 2π—i . e . , given the homogeneous population density , there is no a priori belief that one part of the circle ( i . e . the arc ) is more susceptible to the occurrence of new infection than another . We consider a more general scenario with varying population density s ^ . A natural approach in specifying h ( θ | r , s ^ ) is to use the population density along the circumference of the circle , denoted by σ ( l | r , s ^ ) , to account for the effect of heterogeneous landscape , so that ∫ 0 θ ′ h ( θ | r , s ^ ) d θ = ∫ 0 l ′ σ ( l | r , s ^ ) d l , ( 4 ) where l′ is the arc length corresponding to an arbitrary angle θ′ . It is noted that , when the source of infection is the primary/background , r and θ become irrelevant , and g ( G ; η , s ^ ) reduces to the ( normalized ) population density so that the probability of the new infection occurring in a neighbourhood of a particular point is proportional to the population density at that position . Subsequently , the new infected individual is assumed to spend random times in classes E and I which are modelled using an appropriate distribution such as a Gamma or a Weibull distribution . Specifically , following [4] , we use a Gamma ( γ , λ ) with mean γ and s . d . λ for the random time x spent in class E , and for the random time x spent in class I we use an E x p o n e n t i a l ( 1 φ ) with mean φ [4] . All sojourn times are assumed independent of each other given the model parameters . In S1 Text , we also provide a concise description of the algorithm for simulating from the described model . Let T be the duration of the observation period , and let χE ⊆ χI ⊆ χR denote the sets of individuals who have entered class E , class I and class R by T respectively . Also , let E = ( … , Ej , … ) denote the exposure times for j ∈ χE , I = ( … , Ij , … ) denote the times of becoming infectious for j ∈ χI and R = ( … , Rj , … ) denote the times of recovery or removal for j ∈ χR . The densities of the sojourn times in class E and class I are denoted by fE and fI respectively , with their corresponding cumulative distribution functions denoted by FE and FI . Also , as previously defined , n ( t ) is the total number of infectious individuals at time t . Finally , for j ∈ χE , let ψ = ( … , ψj , … ) denote the collection of sources of infection for infected individuals , and G = ( … , Gj , … ) denote their positions relative to the sources of infections where Gj = ( rj , θj ) . Assuming complete data z = ( E , I , R , G , ψ ) and model parameters Θ = ( α , β , γ , λ , φ , η , ω ) , we can express the likelihood as L ( Θ ; z ) = exp { - ∫ 0 T ( α + n ( t ) β ( t ) ) d t } × ∏ j ∈ χ E ( - 1 ) P ( j , ψ j ) × g ( G j ; η , s ^ ) × ( 1 / r j ) × ∏ j ∈ χ I f E ( I j - E j ; γ , λ ) × ∏ j ∈ χ R f I ( R j - I j ; φ ) × ∏ j ∈ χ E \ I { 1 - F E ( T - E j ; γ , λ ) } × ∏ j ∈ χ I \ R { 1 - F I ( T - I j ; φ ) } ( 5 ) Here χ E ( - 1 ) denotes χE with the earliest exposure excluded . The contribution to the likelihood arising from the infection of j by the particular source ψj is given by P ( j , ψ j ) = { α , if individual j is a primary/background case , β ( E j ) , if ψ j ∈ χ I at time E j . ( 6 ) The first two lines in Eq 5 together represent the contribution to the likelihood arising from the observed sequence of exposure events . The third and fourth lines represent the contribution to the likelihood of the sojourn times in class E and I respectively for the exposed individuals . For mathematical clarity , we have so far discussed a general case where the population density along the circumference σ ( l | r , s ^ ) is assumed to be continuous . In practice , however , the data of population density over a study area is often provided in a discrete form , mostly on the grid level [26] ( see also Fig 1 ) . We describe how this special case may be handled practically in S1 Text and S1 Fig . We conduct Bayesian inference of partially observed epidemics using the process of data augmentation supported by Markov chain Monte Carlo methods [4 , 27–29] . Given observed partial data y , including times of symptom onset and death times , the inference involves sampling from the joint posterior distribution π ( Θ , z|y ) ∝ L ( Θ; z ) π ( Θ ) , where z represents the complete data and π ( Θ ) represents the prior distribution of model quantities , such that the complete z is reconstructed , or ‘imputed’ . We use weak uniform priors U ( 0 , 100 ) . It is noted that , in analyzing the Ebola outbreak data ( see Example: Application to the Ebola Outbreak Data ) where z = ( E , I , R , G , ψ ) , other than the parameters in Θ = ( α , β , a , b , c , η , ω ) , the exposure times E and the sources of infections ψ ( i . e . the transmission tree ) are unobserved and are also to be inferred [4 , 27] . In this section we test our methodology using simulated datasets . 10 independent epidemics are simulated from the model described in Model and Methods , parameterized by a set of model parameter values arising from fitting to an Ebola outbreak data ( see Example: Application to the Ebola Outbreak Data ) . The same observation period , geographical area and population density as the Ebola data are considered . Fig 3a shows an exemplar simulated epidemic . Similar to the application to the Ebola outbreak data , we also consider age-specific baseline transmissibility of an infectious individual , i . e . β1 for age less than 15 and β2 for age greater than or equal to 15 . Subsequently , we fit our model to each of the simulated epidemics and obtain the posterior samples of the model parameters . Fig 3b suggests that the model parameters can be accurately estimated from the corresponding inferred posterior distributions which cluster around the true parameter values . We also test with another set of simulated datasets in which we assume a different distribution of population density , suggesting the similar accuracy in parameter estimations ( S2 Fig ) . Conventional SEIR models , which require an explicit account of the contact network among all subjects , have proven to be useful in studying patch-level level disease transmission ( Fig 2a ) , e . g . among farms , towns and cities [7 , 27] . While these models are not theoretically restricted to the patch-level , they are often computationally challenging for individual-level data arising from moderate- to large-size populations . Although these models are not preferable in the scenario considered in the paper , they may be utilized to generate ‘reference’ epidemics that can be subsequently used for further assessing our framework . In this section we perform simulation studies to understand how our framework may capture the temporal and spatial dynamics of the epidemics generated from the SEIR model . We focus on simulations from an individual-based and susceptible-explicit SEIR model , in a heterogeneous landscape , that give rise to epidemics in which around 5% of a study population becomes infected ( within 50 days of the initial infection ) . We note that the prevalence we consider is significantly higher than that found in the recent Ebola outbreak and matches more closely other , more transmissible viruses such as influenza [30] . We consider simpler scenarios with no control measures and known latent period distribution . Details of the SEIR model are given in S1 Text . Fig 4 suggests that our framework can capture key temporal and spatial dynamics of the epidemic simulated from the individual-based SEIR model . Similar results are observed in testing with another set of simulated epidemics ( S3 Fig ) , in which we consider a scenario with a different population density distribution and a fatter tail in the spatial transmission distance . We also perform a comparison between the run-time of our model inference and that of performing full individual-based SEIR model inference , which suggests that ours can be about 780 times faster ( see also S1 Text ) . In contrast to a transmission-network based approach [4] , our framework establishes a relation between infections and the general ( susceptible ) population . Specifically , it proposes a mechanism for how a new infection , beyond the set of observed infected individuals , can arise among the general ( susceptible ) population . This in turn allows us to perform a more general forward simulation without conditioning on the set of observed cases . Fig 6 shows the ( posterior predictive ) distributions of some temporal and spatial summary statistics of the epidemics simulated from the estimated model , from which it can be discerned that the model can generate epidemics that are consistent with the observed one . We also show out-of-sample predictivity for the epidemic curve for the second-half of the epidemic duration ( Fig 6b ) . It is noted that in assessing the spatial fit , beside using a relatively crude global measure ( i . e . Moran’s I index ( Refs . [7] ) ) , we also consider Ripley’s L function [40 , 41] which is much more informative for characterizing clustering/dispersion of point data . More precise individual-level spatio-temporal data have become increasingly available in recent years due to the advent of ‘digital epidemiology’ [1] . One key challenge is how we may extract maximal information from such data , especially through concurrent development of new statistical methods , as existing approaches suffer from certain limitations ( see Introduction ) . In particular , as SEIR-type models can be computationally challenging for individual-level spatio-temporal data , new frameworks are needed to accommodate such data in a mechanistic manner . The recent Ebola outbreak in West Africa ( 2014-2016 ) highlights the need , in particular , for a statistically sound and computationally efficient framework that is both able to integrate individual temporal and spatial information and , more importantly , perform a more general forward prediction which needs to take into account the general susceptible population [4] . In this paper , we have proposed a novel mechanistic framework to address the research gap . Application to the Ebola outbreak data shows broad consistency of key epidemiological quantities with a previous analysis using a transmission-network-based partial-likelihood approach [4] , despite a significantly lower , and potentially more accurate [36] , median value of estimated distance of transmission ( 0 . 85km vs 2 . 51km ) . We have shown that our methods can be used in predictive mode to simulate epidemics ( among the general population ) that are consistent with the observed temporal and spatial patterns of the real outbreak , enabling a more general epidemic predictive framework . We also tested our model inference using simulated examples . Our model was also compared to the more explicit ( but computationally challenging ) individual-based SEIR model , showing that our model can be a reasonable and computationally-efficient surrogate . There are a few simplifying assumptions made in our paper . For example , we have focused on epidemic outbreaks that are mainly attenuated by a time-varying transmissibility e . g . due to controls or seasonal changes of transmissibility . Should susceptible depletion play a key role in attenuating the epidemics , our framework may be modified accordingly—e . g . , for a given region , adding a component that specifies the decreased likelihood of occurrence of new infections with increased density of existing infections , to mimic the effect of susceptible depletion . Nevertheless , the effect of susceptible depletion may only be significant on a very local scale such as that of the individual household . Moreover , it does not appear to be a determining factor in controlling the recent Ebola outbreak , at least on the ‘global’ scale [17] ( Fig 6 ) . We have considered random movement patterns of infectious individuals that may be reasonably abstracted by a monotonically decreasing density function [23 , 24] . For future work , this assumption may be relaxed to model more complicated scenarios , such as spread of splash-dispersed fungal pathogens [43] in which the spreading distance may also depend on the susceptible population . In this case , one may modify the density for the distance by also taking into account the distribution of susceptible population in the annuli along the radius of the circle centered at a particular source of infection . The transmission rate of an infectious case in our model is independent of the ( local ) susceptible population density . This assumption may be relaxed to allow for more “localized” transmission rates . For example , a model taking into account the heterogeneity of the susceptible population more explicitly may be obtained by allowing the infection rate for each case to be dependent on the local density of susceptibles by taking an appropriate weighted average of the latter with respect to the kernel function , at the expense of increased computational complexity . When spatial heterogeneity is present at a scale that is fine with respect to the range of transmission , then such an average may exhibit little variability over cases . Nevertheless , we note the ability of our approach to identify a kernel that matches that identified when the full SEIR model is fitted . Moreover , our model appears to be reasonable for the case of the Ebola outbreak ( Fig 6 ) . We have considered scenarios that the entire population is susceptible , an assumption which generally holds for newly emerging infections . Vaccination , for instance , decreases the proportion of susceptibles among the general population , and has an important impact on the geographical spread of viruses ( e . g . [44] ) . The effect of vaccination can be readily incorporated by our framework , for example , by reducing the ( effective ) susceptible population proportional to the vaccination rate in a particular region . The Ebola dataset we analyzed is likely to be subject to underreporting , which may have resulted in , for example , a biased ( lower ) estimate of the degree of superspreading [4] . Future work which takes into account the underreporting explicitly may be considered . We hope that our proposed framework can provide an essential step for the systematic modelling of the increasingly available individual-level disease data .
Availability of individual-level , spatio-temporal disease data ( e . g . GPS locations of infected individuals ) has been increasing in recent years , primarily due to the increased use of modern communication devices such as mobile phones . Such data create invaluable opportunities for researchers to study disease transmission on a more refined individual-to-individual level , facilitating the designs of potentially more effective control measures . However , the growing availability of such precise data has not been accompanied by development of statistically sound mechanistic frameworks . Developing such frameworks is an essential step for systematically extracting maximal information from data , in particular , evaluating the efficacy of individually-targeted control strategies and enabling forward epidemic prediction at the individual level . In this paper we develop a novel statistical framework that overcomes a few key limitations of existing approaches , enabling a machinery that can be used to infer the history of partially observed outbreaks and , more importantly , to produce a more comprehensive epidemic prediction . Our framework may also be a good surrogate for more computationally challenging individual-based models .
[ "Abstract", "Introduction", "Models", "and", "methods", "Results", "Discussion" ]
[ "epidemiological", "statistics", "population", "metrics", "infectious", "diseases", "medicine", "and", "health", "sciences", "simulation", "and", "modeling", "infectious", "disease", "epidemiology", "epidemiology", "biology", "and", "life", "sciences", "population", "biology", "spatial", "epidemiology", "population", "density", "infectious", "disease", "control", "epidemiological", "methods", "and", "statistics", "research", "and", "analysis", "methods" ]
2017
A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak
Host cells impose a broad range of obstacles to the replication of retroviruses . Tetherin ( also known as CD317 , BST-2 or HM1 . 24 ) impedes viral release by retaining newly budded HIV-1 virions on the surface of cells . HIV-1 Vpu efficiently counteracts this restriction . Here , we show that HIV-1 Vpu induces the depletion of tetherin from cells . We demonstrate that this phenomenon correlates with the ability of Vpu to counteract the antiviral activity of both overexpressed and interferon-induced endogenous tetherin . In addition , we show that Vpu co-immunoprecipitates with tetherin and β-TrCP in a tri-molecular complex . This interaction leads to Vpu-mediated proteasomal degradation of tetherin in a β-TrCP2-dependent manner . Accordingly , in conditions where Vpu-β-TrCP2-tetherin interplay was not operative , including cells stably knocked down for β-TrCP2 expression or cells expressing a dominant negative form of β-TrCP , the ability of Vpu to antagonize the antiviral activity of tetherin was severely impaired . Nevertheless , tetherin degradation did not account for the totality of Vpu-mediated counteraction against the antiviral factor , as binding of Vpu to tetherin was sufficient for a partial relief of the restriction . Finally , we show that the mechanism used by Vpu to induce tetherin depletion implicates the cellular ER-associated degradation ( ERAD ) pathway , which mediates the dislocation of ER membrane proteins into the cytosol for subsequent proteasomal degradation . In conclusion , we show that Vpu interacts with tetherin to direct its β-TrCP2-dependent proteasomal degradation , thereby alleviating the blockade to the release of infectious virions . Identification of tetherin binding to Vpu provides a potential novel target for the development of drugs aimed at inhibiting HIV-1 replication . In order to successfully infect human cells , HIV-1 has to neutralize cellular restriction factors that impede its replication at multiple steps . HIV-1 Vpu serves this goal by counteracting a blockade imposed by the newly identified protein tetherin [1]–[4] . Under basal conditions , tetherin is expressed in B and T cells , plasmacytoid dendritic cells and myeloid cells [5]–[7] . In addition , tetherin expression is strongly upregulated in many cell types by type-I interferon ( IFN ) , a situation typically encountered in viral infections [5] . Tetherin is a heavily glycosylated type-II transmembrane protein with an unusual topology , which is otherwise only found in mammals in a minor but pathologically important topological variant of the prion protein [8] , [9] . Tetherin is indeed linked to membranes both by its one-pass transmembrane domain and by a C-ter GPI anchor . This anti-viral factor is mostly intracellular , but it is also localized at the cell surface in lipid rafts , from where it is continually recycled to the trans-Golgi network [8] , [10] . In cells expressing tetherin , HIV-1 viruses deleted for the Vpu gene can bud normally but remain tethered to the cell surface through a protein bond [1] , [9] . The mechanistic details of this phenomenon remain to be clarified . A hypothesis , that still awaits confirmation , is that tetherin itself forms the protein tether between the cell surface and the virion owing to its ability to form stable dimers [11] . The affected virions are then endocytosed and probably degraded in lysosomes [1] . In addition to inhibiting HIV-1 , tetherin also blocks the replication of numerous retroviruses , as well as other non-related enveloped viruses [12]–[14] . The importance of this restriction in the cellular antiviral arsenal is underscored by the apparent positive selection that tetherin undergoes , which is the hallmark of an ongoing molecular fight with pathogens [15] . Vpu is a transmembrane protein which removes the HIV-1 CD4 receptor from the ER biosynthetic pathway [9] . This is thought to liberate the HIV-1 env glycoprotein from unwanted premature interactions with its receptor . For that task , Vpu bridges CD4 to β-TrCP [16] . β-TrCP ( actually representing the two homologues β-TrCP1 and β-TrCP2 ) is a substrate recognition unit of the SCF ( Skp1/Cullin/F-box protein ) E3 ubiquitin ligase that provides specificity to this machinery by binding to target proteins harboring a distinct motif ( DSGXXS , where both serines are phosphorylated ) , thereby inducing their ubiquitination and subsequent proteasomal degradation [17] , [18] . Vpu possesses a β-TrCP target motif , where the cytosolic serines S52 and S56 are constitutively phosphorylated , which allows efficient recruitment of β-TrCP [19] . Vpu itself escapes degradation by unclear means [16] , but instead induces the degradation of the CD4 molecules to which it associates . Of note , the mechanistic details of this action of Vpu are only partly understood , since a direct ubiquitination of CD4 in presence of Vpu is not yet demonstrated [16] , [20] . Besides that , Vpu-induced CD4 degradation requires a functional ER-associated degradation pathway ( ERAD ) , which mediates the dislocation of proteins targeted for degradation from ER membranes [21] . Although it had been previously shown that Vpu downmodulates tetherin level from the cell surface [3] , [22] , the mechanistic details have just begun to be unraveled . It was recently shown that Vpu targets tetherin for proteasomal and/or lysosomal degradation , through a β-TrCP-dependent mechanism [23] , [24] . Here we confirm that Vpu leads to a depletion of tetherin from cells . We further show that Vpu performs this action by interacting with tetherin in a ternary complex that also comprises β-TrCP . Importantly , we found this depletion to be functionally relevant since it is required for the efficient counteraction of tetherin-mediated restriction , both in overexpression settings and upon IFN-α-induced endogenous tetherin expression . By generating several cell lines stably knocked-down for β-TrCP1 or β-TrCP2 expression , we further show that β-TrCP2 , but not β-TrCP1 , is required for this depletion . Furthermore , we confirm that this reduction of tetherin level occurs at least for a large part through the proteasome . The depletion is indeed blocked by a proteasome inhibitor , as well as the K48R mutant of ubiquitin , which allows monoubiquitination of targeted proteins but not the subsequent elongation of the polyubiquitin chains required for proteasomal degradation . In addition , our data are also compatible with a model where some fraction of the Vpu-induced tetherin depletion is due to a β-TrCP2-dependent lysosomal degradation . However , Vpu-induced tetherin degradation explained only a part of its activity against the antiviral factor . Binding of Vpu to tetherin was indeed sufficient for a partial rescue of viral release , even in absence of tetherin degradation . Finally , we show that the mechanism underlying the degradation of tetherin uses a cellular machinery at least partly overlapping with the cellular ERAD pathway . In order to investigate the mechanistic details of Vpu action against tetherin , we generated constructs of human and mouse tetherin tagged with HA at their cytosolic N-terminus . We expressed these in 293T cells , which do not express endogenous tetherin [2] . In the absence of Vpu , both constructs potently blocked the release of HIV-1 virions as scored by titrating the viral output ( Fig . 1A ) or by measuring released physical particles by RT assay ( data not shown ) . The lower antiviral activity of murine tetherin is explained by its lower expression level , as indicated by a dose-response assay ( data not shown ) . HIV-1 Vpu expression relieved the blockade imposed by human tetherin , but was only marginally active against murine tetherin , as previously reported ( Fig . 1A ) [13] . We obtained similar results when the HA tag of tetherin was replaced by a Flag tag ( data not shown ) . This indicates that our system recapitulates the reported restriction imposed by tetherin , at least in its measurable functional consequences . Interestingly , the cellular content of tetherin was markedly reduced in the presence of HIV-1 , but not in the presence of the Vpu-deleted version of this virus ( Fig . 1B ) . Paralleling the viral output data , murine tetherin expression levels were not decreased in cells expressing HIV-1 as compared to cells expressing Vpu-deleted HIV-1 . Of note , the fact that murine tetherin is not affected by Vpu , although its expression is driven by the same promoter as human tetherin argues against a non-specific transcriptional effect from the viral protein . Additionally , human tetherin depletion was observed when expressed from different unrelated promoters , again arguing against a transcriptional mechanism for Vpu-induced tetherin depletion ( data not shown ) . Finally , we confirmed a very potent and dose-dependent Vpu-mediated human tetherin depletion in cells where HIV-1 Vpu and the antiviral factor are co-expressed ( in absence of other viral proteins ) ( Fig . 1C ) . In order to strengthen these observations , we asked whether the Vpu-induced tetherin depletion quantitatively correlated with its ability to rescue viral release . Increasing the dose of Vpu , as expected , proportionally decreased the level of tetherin , which paralleled the decrease in the antiviral activity of the cellular factor ( Fig . 2A ) . The correlation was statistically significant , as indicated by calculating the Pearson coefficient of correlation . Of note , at any given Vpu dose , the decrease of the antiviral activity seemed more efficient than the observed decrease of tetherin level . This most likely reflects depletion-independent activity of Vpu against tetherin . Finally , we determined that the depletion was observed at all tested time points after Vpu and tetherin co-expression ( ranging from 17 h to 44 h ) , and in all these cases , the decrease of tetherin level paralleled the decrease of antiviral activity in a statistically significant manner ( Fig . 2B ) . Overall , these data indicate that Vpu depletes human tetherin from cells in a dose dependent manner , and that this phenomenon is functionally connected to the rescue of viral release exerted by the viral protein . We wondered whether Vpu depletes tetherin via a mechanism related to its downregulation of CD4 . We therefore first asked whether Vpu required an intact β-TrCP interaction motif . For that purpose , we generated a Vpu mutated for one ( S52A ) or both ( S52A and S56A , thereafter coined Vpu 2S/A ) of the serines crucial for β-TrCP recruitment [16] , [19] , and monitored the ability of these constructs to deplete tetherin from transfected 293T cells . Strikingly , both mutants were unable to downregulate tetherin expression ( Fig . 3A ) . Consistent with a crucial role of Vpu-mediated tetherin depletion for HIV-1 replication , we showed that Vpu serine mutants were severely impaired for their ability to counteract tetherin antiviral action ( Fig . 3B ) . We next assessed the importance of β-TrCP recruitment motif of Vpu for tetherin counteraction in cells expressing endogenously the antiviral restriction factor , as opposed to an overexpressed form of the protein . For that purpose , we treated 293T with IFN-α for 8 hours , which potently induced expression of endogenous tetherin both at mRNA and protein levels , as previously reported [2] ( Fig . 4A and 4B ) . In parallel , we transfected these cells with a Vpu-deleted HIV-1 in the absence or presence of wild type Vpu or a Vpu 2S/A mutant . The expression of either Vpu constructs had no significant effects on IFN-receptor signaling as monitored by the induction of RIG-I , a well known IFN-responsive gene ( Fig . 4A ) . Additionally , Vpu or a Vpu 2S/A mutant had no impact on IFN-mediated upregulation of tetherin mRNA ( Fig . 4B ) . Consistent with what we observed in overexpression settings , the cellular content of endogenous tetherin protein was reduced by wild type Vpu expression , but not by its serine mutated counterpart , indicating that Vpu-mediated downregulation of tetherin occurs post-transcriptionally ( Fig . 4A ) . The reduction of endogenous tetherin expression by Vpu in 293T cells treated with IFN-α is more modest than in co-transfection settings , which is expected since here all cells express endogenous IFN-induced tetherin , while only a fraction of these is successfully transfected with Vpu ( data not shown ) . Furthermore , the reduction of endogenous IFN-induced tetherin by Vpu indicates that the depletion observed with tagged versions of the protein does not simply stem from a cleavage of the tag off the tetherin protein . Importantly , the IFN-induced tetherin upregulation led to a defect in viral release for ΔVpu HIV-1 , which was rescued when wild type Vpu was added in trans ( Fig . 4C ) . Of note , the Vpu-mediated enhancement of viral release was less potent in these settings than upon tetherin overexpression , most probably because IFN treatment induces , apart from tetherin , additional anti-HIV-1 factors that are insensitive to Vpu activity [25] . Correlating with tetherin protein levels , when the double serine mutant of Vpu was used , HIV-1 viral release was only marginally increased . This data with endogenous IFN-induced tetherin confirms the importance of the β-TrCP-recruitment motif of Vpu to counteract tetherin-mediated restriction . To confirm the involvement of β-TrCP in the anti-tetherin action of Vpu , we tested the effect on Vpu action of a β-TrCP-ΔF deletion mutant , which was shown to abrogate the degradation of CD4 by Vpu [16] . This construct is a well characterized dominant negative of β-TrCP that cannot be anchored on the SCF E3 ligase since it lacks the so-called F-box domain , which mediates β-TrCP binding to the skp1 adaptor of this machinery [17] . This mutant , derived from a β-TrCP1 clone , has dominant negative activity on both β-TrCP1 and β-TrCP2 . Strikingly the concomitant expression of this dominant negative form of β-TrCP ( β-TrCP-ΔF ) completely abolished Vpu-mediated tetherin degradation ( Fig . 5 ) . β-TrCP-ΔF expression did not alter significantly Vpu protein levels , as expected . Expression of wild type β-TrCP1 ( Fig . 5 ) and wild type β-TrCP2 did not prevent and even slightly increased Vpu-mediated tetherin downregulation ( especially for β-TrCP2 ) ( data not shown ) . Altogether , these data strongly suggest a role for β-TrCP in the Vpu-mediated counteraction of tetherin . In order to further analyze the requirement for β-TrCP in Vpu anti-tetherin action , we generated 293T cell lines stably transduced with lentiviral vectors expressing microRNA-adapted shRNA ( shRNAmir ) specifically targeting β-TrCP1 or β-TrCP2 . We obtained one cell line harboring potent β-TrCP1 downregulation ( shRNAmir #325 ) , and three cell lines harboring potent β-TrCP2 downregulation ( shRNAmir # 187 , 190 & 192 ) , as measured by real-time RT-PCR ( Fig . 6A ) . In cells that expressed a control or β-TrCP1-targeting shRNAmir , Vpu depleted tetherin very efficiently ( Fig . 6B , lower panel ) . In contrast , in all three cell lines that harbored diminished levels of β-TrCP2 , Vpu-induced tetherin depletion was abolished . Importantly , measuring the effect of Vpu on release of HIV-1 in these different cell lines showed a complete correlation between the ability of Vpu to trigger tetherin depletion and its ability to functionally antagonize the antiviral factor ( Fig . 6B , upper panel ) . Of note , Vpu still exhibited a residual activity to rescue viral release in cells depleted for β-TrCP2 . Overall , our data demonstrated that Vpu induced tetherin depletion in a β-TrCP2-dependent manner . Finally , in situations where Vpu did not lead to tetherin degradation ( Vpu mutants or β-TrCP2 downregulation ) , we consistently observed that tetherin levels were increased to varying extents above basal levels ( Fig . 3A , 4A , 6B ) . This suggests that Vpu might stabilize tetherin when it is unable to target it to the degradative machinery , possibly via a direct interaction with the protein . In order to analyze whether Vpu could interact in eukaryotic cells with the antiviral factor , we transfected 293T cells with Vpu in the presence or absence of HA-tagged tetherin . Monitoring the lysates from these co-transfections confirmed Vpu-induced depletion of tetherin ( Fig . 7 , upper part , lanes 1 and 3 ) . By subsequently immunoprecipitating HA-tetherin with an anti-HA resin , we could show that Vpu was efficiently pulled down in the presence but not in the absence of tetherin ( Fig . 7 , lanes 1 , 2 and 3 ) . In addition , the dominant negative form of β-TrCP ( which binds to Vpu , but is unable to recruit the E3 ligase machinery ) also co-immunoprecipitated with tetherin . This demonstrates that a ternary complex exists between tetherin , Vpu and β-TrCP . Nevertheless , this experiment does not rule out the possibility that β-TrCP interacts with tetherin also in the absence of Vpu , although this seems unlikely as tetherin itself does not harbor a bone fide β-TrCP recruitment motif . Notably , the tetherin-Vpu interaction was easier to detect in the presence of the β-TrCP dominant negative ( ΔF-box ) ( lanes 4 and 5 ) or when a Vpu defective for β-TrCP recruitment ( Vpu 2S/A ) was used instead of wild type Vpu ( lanes 6 and 7 ) . This apparent increase in co-immunoprecipitation of tetherin-Vpu complexes might reflect a more stable association between Vpu and tetherin in conditions where the complex cannot be targeted to degradation , or alternatively simply results from higher levels of HA-tetherin present in these extracts , since in these conditions Vpu is not able to reduce tetherin cellular levels ( upper part , lanes 4 to 7 ) . These results demonstrate that the inability of Vpu 2S/A mutant to induce tetherin depletion does not stem from an inability to interact with tetherin , but rather originates from its inability to recruit β-TrCP . Finally , this data indicates that binding of Vpu to tetherin is not sufficient to induce its degradation or to fully counteract its antiviral activity , since the Vpu 2S/A mutant strongly binds to tetherin but is significantly impaired for both these activities . Our results point out towards a model where Vpu bridges tetherin to β-TrCP2 , which leads to the depletion of tetherin from cells and , as a consequence , alleviates the restriction imposed by the antiviral factor . In order to define if Vpu-tetherin-β-TrCP2 complexes were targeted to proteasomal degradation , we transfected 293T cells with an HA-tetherin construct in the presence or absence of Vpu . Forty hours later , the cells were either left untreated or treated with the proteasome inhibitor MG132 for 12 hours and then lysed . This revealed that proteasomal inhibition significantly rescued tetherin expression in presence of Vpu ( Fig . 8A ) . A modest increase of tetherin expression was also noted in the absence of Vpu . As a control , MG132 stabilized the Vpu-resistant murine tetherin to an equal extent in the absence or presence of Vpu ( data not shown ) . Overall , this indicated that Vpu , at least in part , targets tetherin for proteasomal degradation . To confirm this finding , we performed a Vpu and Flag-tetherin co-transfection , with the additional inclusion of wild type ubiquitin or its mutated K48R form , which blocks the formation of the polyubiquitin chains implicated in proteasomal targeting . This construct indeed can be attached to target proteins as a monomer , but due to the absence of the proper acceptor lysine 48 , impedes further covalent attachment of additional ubiquitin to the nascent chain [26] . Notably , while wild type ubiquitin had no impact on tetherin depletion , the K48R ubiquitin mutant partially blocked Vpu-mediated tetherin downregulation ( Fig . 8B ) . Finally , we were unable to directly detect ubiquitinated forms of tetherin in presence or absence of Vpu even after treatment with MG132 , either because tetherin is not directly ubiquitinated , or because of technical limitations ( data not shown ) . Altogether , these data indicate that Vpu binds to tetherin and concomitantly recruits β-TrCP2 to trigger the proteasomal degradation of the antiviral factor . The proteasomal degradation of trans-membrane proteins such as tetherin requires that the cell employs a specific machinery . Indeed , such proteins must be dislocated from membranes prior to their entry into the cytosolic proteasome complex [27] . In the ER , this dislocation is mediated by a series of distinct mechanisms , collectively known as the ERAD ( ER-associated degradation ) pathways . Briefly , the targeted protein is marked for degradation by a mostly unclear mechanism , which can include ubiquitination . The subsequent dislocation from the membrane is performed by a series of protein complexes which all require at some point the mechanical pulling force generated by the p97 ATPase ( also known as VCP ) . The dislocated protein is then targeted to proteasomal degradation by ubiquitination [27] . To address whether the ERAD pathway is required for Vpu-induced tetherin proteasomal degradation , we transfected 293T with a control siRNA or a siRNA pool specific for p97 , which led to a 50% downregulation of its mRNA level ( data not shown ) . This relatively low level of downregulation might be due to the constitutively very high expression of p97 [28] . Nevertheless , co-transfection of these cells with a Flag-tetherin plasmid in the absence or presence of Vpu revealed that p97 downregulation partially impaired Vpu-mediated tetherin degradation ( Fig . 9A ) . Interestingly , the involvement of a dislocation out of the ER membrane in Vpu-mediated tetherin degradation potentially exposes to the cytosolic milieu lumenal lysines that therefore also can serve as ubiquitin acceptors . This might explain our observation that a tetherin mutant with its two cytosolic lysines replaced by arginines ( KcytoR ) was still efficiently targeted for degradation by Vpu ( Fig . 9B ) . It has been known for a long time that HIV-1 deleted for the Vpu gene cannot be released efficiently from specific cell types such as macrophages or T cells [29] , [30] . The recent identification of the IFN-α induced restriction factor tetherin provides an explanation for this phenomenon [2] , [3] . Tetherin impedes release of newly budded virions and mediates their internalization , probably thereby targeting them for lysosomal degradation . Vpu efficiently counteracts this antiviral activity by a mechanism whose details only begin to be revealed [2] , [3] . Indeed , while it had been known from some time that Vpu downmodulates tetherin from the cell surface [3] , [22] , it was only recently shown that Vpu targets tetherin for proteasomal and/or lysosomal degradation [23] , [24] . We confirm here that Vpu expression indeed induces a sharp reduction of tetherin protein levels in cells ( Fig . 1 ) . This depletion strongly correlated with the extent of inhibition of tetherin antiviral action ( Fig . 2 ) . In addition , both the effects of Vpu on tetherin level and antiviral activity were dependent on the recruitment by Vpu of β-TrCP , a substrate recognition subunit of the SCF E3 ubiquitin ligase . Indeed , a Vpu mutant defective for β-TrCP recruitment was impaired for both these activities ( Fig . 3 ) . Importantly we also showed , by co-immunoprecipitation studies in eukaryotic cells , that Vpu interacts with tetherin , thereby forming a ternary complex with β-TrCP ( Fig . 7 ) . As a confirmation of the importance of the Vpu-β-TrCP interplay , Vpu anti-tetherin action was dependent on the presence of a functional β-TrCP2 , as determined by RNA interference studies and by using a β-TrCP dominant negative ( Fig . 5 & 6 ) . Of note , while preparing this work for publication , the specific involvement of β-TrCP2 in Vpu-mediated tetherin degradation was reported , as well as the interaction between Vpu and tetherin by co-immunoprecipitation [31] , [32] . Remarkably , we did not detect any role for the related protein β-TrCP1 . While this might appear surprising in regard to the high similarity between β-TrCP1 and β-TrCP2 , these proteins display a significant difference , as the first is nuclear , while the second is cytosolic [33]–[35] . Moreover , a differential functional activity of the two proteins has already been reported , for instance in their ability to induce the degradation of IκB [33] . An alternative explanation to our data could be that β-TrCP1 is not functional in 293T cells , where the experiments were performed . While unlikely , this may have gone unnoticed , as the majority of previous RNA interference experiments against β-TrCP were done with siRNAs targeting simultaneously both β-TrCP1 and β-TrCP2 . Importantly , we also demonstrated that Vpu requires β-TrCP-dependent tetherin degradation to antagonize the antiviral activity of endogenous IFN-induced tetherin ( Fig . 4 ) , in addition to overexpressed forms of the cellular restriction factor . IFN-induced tetherin is particularly relevant since it mimics conditions likely found during HIV-1 infection . For instance the recent article by Li et al . [36] demonstrates that during the early events of HIV-1 infection , plasmacytoid dendritic cells are attracted to the sites of initial infection in mucosal tissues where they secrete high amounts of IFN-α . We also showed that efficient Vpu-induced tetherin depletion required a functional proteasomal pathway ( Fig . 8 ) . Nevertheless , in addition to Vpu-induced tetherin proteasomal degradation , our results do not exclude additional mechanisms of depletion . Indeed , the proteasomal inhibitor MG132 , as well as a dominant negative ubiquitin K48R mutant , only showed a partial inhibition of tetherin degradation ( Fig . 8 ) . Of note , a role for lysosomal targeting in Vpu-mediated tetherin counteraction was recently proposed [24] , [31] . Our preliminary data indicated that , when using the lysosomal inhibitor bafilomycin and the ubiquitin K63R mutant , which dominantly inhibits the formation of K63-dependent polyubiquitin chains , we observed a partial rescue of tetherin degradation ( data not shown ) . Nevertheless , these results were complex to interpret since lysosomal inhibition also markedly altered the basal level of tetherin in the absence of Vpu , suggesting an important role of lysosomes in the normal trafficking of tetherin . Therefore it is possible that β-TrCP might not only trigger proteasomal degradation of tetherin , but also its lysosomal targeting through monoubiquitination or through the formation of non-conventional chains of ubiquitin linked together on their lysine 63 instead of lysine 48 , which is known to target proteins towards lysosomes [37] . In summary , β-TrCP recruitment to the Vpu-tetherin complex could lead to different fates ( lysosomal or proteasomal degradation ) depending on the cellular compartment where it occurs ( as discussed in [38] for other proteins ) . A dislocation step followed by proteasomal degradation might occur predominantly during the tetherin biosynthesis pathway , while a rerouting of tetherin towards lysosomes might be relatively more important during constitutive tetherin endocytosis and recycling from the plasma membrane [10] . Alternatively , ubiquitination of tetherin could first target it to the lysosome and , subsequently , the remaining cytosolic tail of tetherin could be degraded by the proteasome , as described for the erythropoietin receptor [39] . Finally , it is likely that the relative contribution of proteasomal versus lysosomal degradation varies depending on the cell type used . Indeed , while Vpu-induced lysosomal degradation of tetherin was clearly demonstrated in HeLa cells [24] , [31] , two other publications showed mostly proteasomal degradation in 293T cells [23] , [40] . In any case , these distinct trafficking pathways ultimately result in the absence of tetherin from the cell surface , thereby allowing for the unimpeded release of new viral particles . The mechanism underlying tetherin degradation had common characteristics with the cellular ER-associated degradation pathway ( ERAD ) , where ER-associated proteins are dislocated and subsequently degraded by the proteasome in the cytosol ( Fig . 9A ) . Indeed Vpu-mediated tetherin degradation required the action of the cellular p97 ATPase , which is a key component of the ERAD [27] . The involvement of an ERAD-like pathway in Vpu anti-tetherin functioning provides an explanation for our observation that a tetherin mutant devoid of cytosolic lysines is still degraded by Vpu as efficiently as wild type tetherin ( Fig . 9B ) . It is indeed extensively documented that ERAD substrates do not require cytosolic lysines for their proteasomal degradation [41]–[44] . Notably , this is also true for Vpu-induced ERAD-mediated CD4 degradation [21] . Two possibilities can explain this apparent paradox . Firstly , lumenal lysines are exposed to the cytosolic milieu during the dislocation step , therefore alleviating the requirement for cytosolic lysines for ubiquitination of the target protein . Secondly , ubiquitination of ERAD substrates can occur on non-lysine residues [45] , [46] . The precise timing of ubiquitination and dislocation during ERAD , as well as their functional relationship is not yet fully understood [27] . Nevertheless , we show that a putative β-TrCP-mediated tetherin ubiquitination on cytosolic lysines cannot be the trigger for its dislocation , since in that case the lysine mutant would be resistant to Vpu action . Our results are compatible with a model where Vpu induces the dislocation ( be it partial ) of tetherin from the membrane , thereby exposing additional lysines for ubiquitination by β-TrCP . Finally , we were unable to detect direct tetherin ubiquitination in the presence of Vpu ( data not shown ) . This is not surprising as several groups have been unable to detect Vpu-induced CD4 ubiquitination although it is generally accepted that Vpu also degrades CD4 through a proteasomal pathway [16] , [20] . This failure to detect a membrane protein ubiquitination is not limited to Vpu targets , since the same holds true for the ERAD-mediated MHC-1 degradation induced by the CMV protein US11 [47] , where the proteasomal degradation of MHC-I does not seem to be coupled to direct MHC-I ubiquitination , but possibly to the ubiquitination of another associated protein . Finally , overall , the mechanism of action employed by Vpu to counter tetherin restriction shares some similarities with the mechanisms used by Vpu to induce CD4 degradation [21] , [48] . This is maybe not surprising , since both these cellular proteins are membrane-associated proteins that impede efficient release of viral particles . Importantly , our data also suggest that the Vpu anti-tetherin activity is not fully explained by Vpu-mediated tetherin depletion . Indeed , this phenomenon accounted for a large part but not the integrality of the Vpu anti-tetherin functional effect . In particular , in conditions where degradation was completely abrogated , Vpu still had a residual ability to counteract tetherin antiviral action ( Fig . 3B , 4C and 6B ) . In addition , the extent of inhibition of tetherin antiviral activity by Vpu was higher than the decrease of tetherin levels it induced ( Fig . 2A & 2B ) . All these observations are fully consistent with reports indicating that a Vpu mutated in its cytosolic serine motif still possesses a residual ability to rescue viral release [3] , [49] , [50] . This β-TrCP-independent effect is probably mediated by the Vpu transmembrane domain , since this region by itself harbors some potential for the rescue of viral release [2] , [49] , [51] . In agreement , we showed that a Vpu mutant impaired for β-TrCP binding was still fully able to interact with tetherin ( Fig . 7 ) . It is therefore likely that the residual β-TrCP-independent anti-tetherin activity of Vpu is mediated by the interaction between Vpu and tetherin , which likely happens through their respective transmembrane domains . Accordingly , it was recently shown that modifying tetherin transmembrane region can render it resistant to Vpu counterstrike [15] , [40] . This binding might partially impair tetherin antiviral activity , possibly by steric hindrance , or by inducing its downregulation from the cell surface . Vpu would subsequently target tetherin for proteasomal and likely also lysosomal degradation , thereby deploying the integrality of its activity [23] , [24] , [31] , [40] . Of note , during the preparation of this manuscript , it was reported that Vpu could relieve the blockade of viral release even in certain cells lines where it failed to induce tetherin depletion [52] . It can be envisioned that , in these cell types , Vpu would counteract tetherin through its β-TrCP-independent activity . In agreement with this model , Vpu mediated its virion release enhancement , which appeared to be only modest , independently of its β-TrCP-interacting motif in these cells [52] . Hijacking of ubiquitin E3 ligases appears to be a common theme for HIV-1 accessory proteins to counteract host cell restriction factors . In addition to Vpu that serves as a bridge between the E3 β-TrCP substrate recognition module and the targeted restriction factor , HIV-1 Vif developed a similar but slightly different strategy , where it directly replaces the substrate recognition module to induce the degradation of the APOBEC3G antiviral protein [53] . More generally , it will be worth investigating the strategies used by other classes of viruses to counteract the broad antiviral action of tetherin . To conclude , we propose that the molecular interplays revealed here pave the way for the development of new therapeutic strategies targeting the Vpu-tetherin interaction in order to thwart HIV-1 replication . Expression plasmids for untagged tetherin of human and murine origin were obtained from Origene ( Rockville , MD ) . Tetherin was subsequently sub-cloned using standard molecular biology procedures into pCDNA3 . 1 ( + ) or pEF1 backbones ( both from Invitrogen ) , with either a Flag or HA tag added in frame at their N-terminus . The tetherin mutant harboring lysines to arginines changes in its two cytosolic lysines ( K18R and K21R , which we named KcytoR ) , was engineered with the help of the QuickChange mutagenesis system ( Stratagene ) . Of note , the N-terminal HA-tag appended to this construct does not itself encode for any lysine . The expression plasmid for Vpu , pCDNA-Vphu , encodes a well characterized codon-optimized version of Vpu ( made by K . Strebel and S . Bour , obtained through the NIH AIDS Research and Reference Reagent Program , Division of AIDS , NIAID , NIH ) [54] . Versions of this plasmid harboring the S52A or S52A/S56A ( which we named 2S/A in the core of the text ) were made with the help of the QuickChange mutagenesis system ( Stratagene ) . The Vpu-deficient or proficient HIV-1 expression vectors are kind gifts of Didier Trono and are based on the pR9 proviral construct [55] . Wild type β-TrCP1 was expressed from the pCR3-Flag-β-TrCP1 plasmid ( a kind gift of Sylvia Rothenberger ) [56] . β-TrCP1-ΔF-box was expressed from the pCMV2-FLAG-β-TrCP1-ΔF plasmid ( a kind gift or Yinon Ben Neriah ) [33] . Wild type β-TrCP1 was expressed from the pCDNA3-β-TrCP2-HA plasmid [57] . HA-tagged wild type and K48R mutant of ubiquitin were expressed from the pRK5 backbone and were obtained from Ted Dawson's lab through Addgene [58] . The K63R version of this ubiquitin construct was engineered with the help of the QuickChange mutagenesis system ( Stratagene ) . The GFP expression plasmid was pEGFP . N1 ( Clontech ) . Bafilomycin A1 ( Sigma ) was used at a concentration of 50 nM , and MG132 ( Sigma ) at a concentration of 10 uM . Recombinant human IFN-α was obtained from Sigma . 293T cells were cultured following usual procedures . The transfection of these cells was performed either following a standard calcium-phosphate-based technique or with the help of the Fugene 6 reagent ( Roche ) , according to manufacturer instructions . For experiments done in the absence of proviral constructs , the molar ratio of transfected Vpu and tetherin plasmids was 2∶1 , unless otherwise indicated . HIV-1 particles were produced by transient transfection of 293T cells with CaCl2 or Fugene ( Roche ) . Unless otherwise indicated , the supernatant of producer cells was collected 36 hours post-transfection . Virion release was scored by monitoring the reverse transcriptase enzymatic activity in the producer cells supernatant . In single-round infectivity assays , viral titer was determined by applying filtered supernatant from producer cells on HeLa-CD4-LTR-LacZ indicator cells [59] . When Vpu and tetherin were co-transfected with a proviral construct , the plasmid molar ratio was 2∶2∶1 , respectively , unless otherwise indicated . When required , statistical analysis of the results were performed with the InStat software ( GraphPad ) . Unless otherwise indicated , cells were lysed with RIPA buffer 36 hours post-transfection . Lysates were pre-cleared ( 13'000 rpm tabletop spin for 10 minutes ) , and subjected to standard SDS-PAGE , after protein quantification with the BCA kit ( Thermo ) . Overexpressed tetherin was detected with antibodies against the relevant tag added on its N-terminus . Namely , the HA and Flag tags were detected with the mouse monoclonal antibodies 3F10 ( Roche ) and M2 ( Sigma ) , respectively . The endogenous tetherin and the Vpu protein were detected with rabbit anti-tetherin and anti-Vpu antibodies , respectively , both made by K . Strebel [52] , [60] ( obtained through the AIDS Research and Reference Reagent Program , Division of AIDS , NIAID , NIH ) . All western blots of endogenous or tagged tetherin depict its glycosylated forms in the 28 to 37 kDa range , but not its immature 20 kDa form . Depending on the experiments , the relative intensity of individual tetherin bands in the 28–37 Kd range varies and we always depict the predominant species . PCNA ( Oncogene Research Products ) and GFP ( Miltenyi ) antibodies were of mouse origin , while anti-ezrin ( Cell Signaling Technology ) was raised in rabbits . RIG-I and ubiquitin were detected with the mouse monoclonal antibodies Alme-1 ( Alexis Biochemicals ) and FK-2 ( BioMol International ) , respectively . Gag p55 and p24 were detected with the mouse monoclonal antibody made by Bruce Chesebro and Kathy Wehrly [61] ( obtained through the AIDS Research and Reference Reagent Program , Division of AIDS , NIAID , NIH ) . Quantifications of tetherin protein levels were performed by densitometry using Photoshop ( Adobe ) , with normalization for loading input by the parallel quantification of a control cellular protein . When required , statistical analysis of the results were performed with the InStat software ( GraphPad ) . Lysates were prepared as described for the western blotting protein analysis . HA-tetherin was immunoprecipitated overnight in PBS , using anti-HA affinity matrix ( clone 3F10 , Roche Applied Science ) . The resulting immunoprecipitates were washed three times with RIPA buffer . They were then resuspended in Laemmli sample buffer , followed by western blot analysis . To achieve downregulation of the VCP ( p97 ) mRNA , 293T cells were transfected using HiPerFect ( Qiagen ) with 100 nM of either a siRNA pool specific for this RNA ( “siRNA ON-Target plus smart pool” , # L-008727-00 , from Dharmacon ) , or a non-targeting siRNA ( “Dharmacon siGenome Non-Targeting siRNA” ) . Twenty-four hours later , the cells were split into the adequate number of wells , and transfected with the plasmids indicated in the relevant figure . The pGIPZ lentiviral vectors expressing , under the control of a CMV promoter , the shRNAmirs specific for β-TrCP1 or β-TrCP2 were obtained from Open Biosystems . The targeted sequences were: β-TrCP1 shRNAmir #325 ( GGCACATAAACTCGTATCTTAA ) , β-TrCP2 shRNAmir #187 ( TGCCAATTATCTGTTTGAAATA ) , β-TrCP2 shRNAmir #190 ( GACATATTAACTCTTACCTGAA ) β-TrCP2 shRNAmir #192 ( GGCCTACGAGATAATTCTATTA ) . The production of the lentiviral vector particles serving for the delivery of these shRNAmirs were done according to the manufacturer instruction ( which is a standard procedure ) . The transduced cells were selected with puromycin to generate stable cell lines . Total RNA was extracted from cells with the help of the RNeasy mini kit ( Qiagen ) , including an on-column DNase treatment step . The integrity of the resulting RNAs was checked with a spectrophotometer . Then , they served as templates for the synthesis of cDNA by the Superscript II reverse transcriptase kit ( Invitrogen ) , using random primers . The cDNAs were quantified by SYBR-green-based real-time PCR using JumpStart SYBR green Taq ReadyMix ( Sigma ) , on a CFX96 cycler ( Bio-Rad ) , with the following primers: β-TrCP1 ( sense CCAACATGGGCACATAAACTCG , antisense GCAGCACATAGTGATTTGGCATCC ) , β-TrCP2 ( sense ACGAATGGTACGCACTGATCC , antisense ACTTCACCCGTGTTCACATCC ) , tetherin ( sense CTGCAACCACACTGTGATG , antisense ACGCGTCCTGAAGCTTATG ) , TBP ( sense GCCCGAAACGCCGAATATA , antisense: CGTGGCTCTCTTATCCTCATGA ) , p97 ( sense: TTGCTCCAGACACAGTGATCC , antisense: GCCACCAATGTCATCATACCC ) . The TBP quantification allowed normalization for the starting amount of RNA . The human and murine tetherin clones used in this study correspond to Swiss-Prot entries Q10589 and Q8R2Q8 , respectively .
To efficiently replicate in cells , HIV-1 needs to inactivate a number of intracellular host defenses . One such antiviral mechanism is provided by the newly identified tetherin protein . This factor blocks viral production by impeding the release of newly generated HIV-1 particles from the surface of cells . HIV-1 possesses the Vpu protein , which efficiently counteracts this blockade . Here we reveal that HIV-1 Vpu interacts with tetherin and leads to its depletion from cells , possibly through multiple mechanisms , including proteasomal degradation . In order to eliminate tetherin , Vpu hijacks a cellular component , named β-TrCP2 , which is normally used by human cells to induce degradation of certain proteins . Identification of tetherin binding to Vpu provides a potential novel target for the development of drugs aimed at inhibiting HIV-1 replication .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biochemistry", "virology/viral", "replication", "and", "gene", "regulation", "virology/virulence", "factors", "and", "mechanisms", "microbiology/immunity", "to", "infections", "virology/virion", "structure,", "assembly,", "and", "egress", "virology/immunodeficiency", "viruses", "cell", "biology", "microbiology/innate", "immunity", "immunology/innate", "immunity", "virology", "infectious", "diseases/hiv", "infection", "and", "aids", "infectious", "diseases/viral", "infections", "molecular", "biology", "immunology/immunity", "to", "infections", "virology/host", "antiviral", "responses" ]
2009
HIV-1 Vpu Neutralizes the Antiviral Factor Tetherin/BST-2 by Binding It and Directing Its Beta-TrCP2-Dependent Degradation
Mycobacterium ulcerans , the causative agent of Buruli ulcer , is an emerging environmental bacterium in Australia and West Africa . The primary risk factor associated with Buruli ulcer is proximity to slow moving water . Environmental constraints for disease are shown by the absence of infection in arid regions of infected countries . A particularly mysterious aspect of Buruli ulcer is the fact that endemic and non-endemic villages may be only a few kilometers apart within the same watershed . Recent studies suggest that aquatic invertebrate species may serve as reservoirs for M . ulcerans , although transmission pathways remain unknown . Systematic studies of the distribution of M . ulcerans in the environment using standard ecological methods have not been reported . Here we present results from the first study based on random sampling of endemic and non-endemic sites . In this study PCR-based methods , along with biofilm collections , have been used to map the presence of M . ulcerans within 26 aquatic sites in Ghana . Results suggest that M . ulcerans is present in both endemic and non-endemic sites and that variable number tandem repeat ( VNTR ) profiling can be used to follow chains of transmission from the environment to humans . Our results suggesting that the distribution of M . ulcerans is far broader than the distribution of human disease is characteristic of environmental pathogens . These findings imply that focal demography , along with patterns of human water contact , may play a major role in transmission of Buruli ulcer . Mycobacterium ulcerans is the cause of Buruli ulcer , a severe necrotizing skin infection ( Figure 1 ) . Although Buruli ulcer is globally distributed , it is an emerging infection primarily in Australia and West Africa [1] . The disease begins as a painless nodule or papule that , if left untreated , can lead to extensive ulceration that could cover 15% of the body [2] . Though the disease is not usually fatal , Buruli ulcer can lead to profound morbidity , especially within rural areas of West Africa where treatment options are limited . Though sex and age are not seemingly risk factors , women and children between the ages 5 and 15 are most often infected . Incidence of Buruli ulcer has increased over the last several years . For instance , in Ghana , the number of new cases reported has been 685 in 2003 , 1021 in 2004 , 1097 in 2005 , and 1010 in 2006 . True incidence data , however is difficult to determine due to poor surveillance measures and case confirmation . The major virulence determinant for M . ulcerans is a plasmid-encoded toxic macrolide , mycolactone [2] , [3] . Acquisition of the mycolactone plasmid is thought to have been a pivotal event in the evolution of M . ulcerans from an M . marinum-like ancestor [4] . Like M . marinum , M . ulcerans is an environmental pathogen . Although the exact mode of transmission for M . ulcerans remains unknown , person to person transmission is extremely rare and a large body of epidemiological data supports the hypothesis that infection results from exposure to aquatic environments [5] , [6] , [7] . Lack of direct person-to-person transmission is a characteristic M . ulcerans shares with other environmental pathogens such as Francisella tularensis and Borrelia burgdorferi . Environmental pathogens are maintained in the environment in the absence of humans . The distribution of such pathogens is far broader than the cases of human disease . For example the life cycle of Borrelia burgdorferi , the causative agent of Lyme disease involves several species of Ixodes ticks and a number of mammalian vectors . Human infections only occur through exposure to ticks; and humans are a dead end for infection . In some areas of the Western U . S . , Borrelia burgdorferi is vectored by an Ixodes species which feeds primarily on lizards and rarely bites humans . In these areas , despite the abundance of Borrelia burgdorferi in the environment , human Lyme disease is extremely rare [8] , [9] . A major advance in deciphering the ecology of M . ulcerans resulted from the identification of an insertion sequence , IS2404 , which is present in over two-hundred copies in M . ulcerans [10] , [11] . Early work showed that IS2404 was present in M . ulcerans , but absent in the closely related mycobacterial species M . marinum , and over 40 other mycobacterial species suggesting that the insertion sequence was specific for M . ulcerans [11] . In the past 15 years a large number of environmental samples collected from Buruli ulcer endemic regions in Australia and West Africa have been analyzed using IS2404 PCR . In Australia , IS2404 has been detected in water as well as from detritus collected from water bodies and , most recently , from trapped mosquitoes [12] , [13] , [14] . No acid-fast bacilli were reported and attempted cultures were negative . In 1999 , Portaels et al reported detection of IS2404 positive PCR from two groups of predaceous aquatic insects , Naucoridae and Belostomatidae [15] . IS2404 PCR positive results have also been obtained from Naucoridae and Belostomatidae collected in Ghana , Cote d'Ivoire and Benin [14] , [16] , [17] . In 2004 , Marsollier et al obtained IS2404 positive PCR results from 5/80 Naucoridae collected in Cote d'Ivoire and , more importantly , successfully cultured an IS2404 positive mycobacteria from two of these . Although one of these isolates produced an ulcer upon injection into mice , both isolates were lost before they could be fully characterized . More recently , an exciting discovery was the culture and complete characterization of M . ulcerans from a Gerridae , or water strider ( in press ) . Gerridae , like Naucoridae and Belostomatidae are predacious aquatic insects in the Order Hemiptera . Unlike Naucoridae and Belostomatidae , Gerridae are unable to bite humans . However , it is likely that Gerridae along with other invertebrates share a food web with M . ulcerans . M . ulcerans has also been shown to form biofilms on aquatic plants [18] . A culture of an IS2404 mycobacteria was obtained from an IS2404 PCR positive plant ( Family: Scrophulariaceae ) collected from the Lobo River in Cote d' Ivoire and it has been suggested that snails may be transiently infected by feeding on this vegetation [18] . Contamination of this sample with M . szulgai prevented isolation of M . ulcerans . IS2404 positive samples include detritus , snails , and fish [13] , [17] . Taken together these results suggest that the ecology of M . ulcerans is complex and includes participation in a food web comprised of many different taxa and feeding groups . Considerable speculation concerning the possibility of an insect vector for Buruli ulcer has followed from elegant studies in which laboratory infections of naucorids collected in France with M . ulcerans could be transmitted to mice from the bite of the infected insect [15] . However , these results have been interpreted with caution [19] . Most attempts to culture the organism from environmental sources have not been successful despite the fact that it is readily cultured from human tissues . None of the IS2404 PCR-positive insects identified in West Africa are blood feeders , making it unlikely that they could play a major role in transmission . Further , IS2404 has been found in several aquatic mycobacterial pathogens closely related to M . ulcerans such as M . liflandii [20] , M . pseudoshottsii [21] , and a newly discovered clade of M . marinum [22] isolated from frogs and fish . Finally , environmental sampling has not been conducted in a systematic way and results from samples collected in non-endemic regions have not been conducted with the exception of one study in which an unspecified number of unidentified plants were collected from Cote d' Ivoire [18] . A problem inherent in the identification of pathogens in the environment is the difficulty of distinguishing the target species within a complex and largely unknown population of background microbial flora . Although it is impossible to have complete confidence that any PCR primer set targeting a specific gene sequence is 100% specific in this context , the use of multiple PCR targets is likely to increase specificity . The completion of the M . marinum and M . ulcerans genome sequencing projects has led to the identification of variable number tandem repeat ( VNTR ) sequences which have been very useful in detecting heterogeneity among M . ulcerans [23] , [24] , [25] . Results from these studies suggested that it might be possible to trace transmission pathways by matching VNTR profiles from environmental samples with those from M . ulcerans cultures obtained from patients in the same geographic area . In this report we present data from a systematic collection of over 1400 environmental samples collected from both endemic and non-endemic regions of Ghana as part of a larger study aimed at defining the ecology of M . ulcerans . Using a tiered PCR based detection method we have mapped the distribution of M . ulcerans within 26 aquatic sites in Ghana . Samples analyzed include vertebrates , invertebrates , suspended solids from water filtrate , soil , and biofilms collected on glass slides . Preliminary evidence for M . ulcerans in environmental samples was obtained from PCR detection of the insertion sequence IS2404 [10] along with PCR detection of the enoyl reductase ( ER ) domain of the mycolactone toxin [26] . Variable number tandem repeat ( VNTR ) analysis of ER-PCR positive samples allowed the discrimination of M . ulcerans from other mycolactone producing mycobacteria and also made it possible to match VNTR profiles from environmental samples with VNTR profiles obtained from patient isolates from the same region . Although M . ulcerans has been detected in many Buruli ulcer endemic areas of West Africa using IS2404-PCR [17] , this is the first study in which both endemic and non-endemic sites have been randomly and systematically sampled . The major finding from this work is that M . ulcerans and other mycolactone producing mycobacteria ( MPM ) are widely distributed in water bodies in endemic and non-endemic villages within the Ashanti and Greater Accra regions of Ghana . This is entirely consistent with M . ulcerans's position as an environmental pathogen . Although the human host may play a role in the dispersion of an environmental pathogen , the pathogen does not depend on the human host for dispersion . Thus the distribution of an environmental pathogen is always much broader than the distribution of disease . Further , these studies suggest that the presence of M . ulcerans in the environment , while necessary , is not sufficient for Buruli ulcer . Strains used in this study are listed in Table 1 . M . ulcerans strains were grown at 32°C for 4–6 weeks on M7H10 agar media . M . liflandii was grown at 32°C in 5% CO2 for 6 weeks on Bordet-gengou media . M . pseudoshotsii , and M . marinum DL strains were grown at 25°C for 6 weeks on Bordet-gengou media . DNA was extracted using a protocol adapted from Lamour and Finley [27] . Small invertebrates collected in Ghana were sampled in pools of groups of 3–15 , whereas vertebrates and larger invertebrates were tested individually . Invertebrate samples were also collected from Tennessee . These samples were used as negative controls for PCR analysis . DNA was also extracted from M . ulcerans Agy99 , M . marinum 1218 , or water for use as positive and negative controls . Samples were vortexed in 400 µL lysis solution ( 100 mM Tris ( pH8 . 0 ) , 50 mM EDTA , 500 mM NaCl , 1 . 33% SDS and 0 . 2 mg/mL RNase A ) and one gram 1 . 0 mm glass beads ( Sigma-Aldrich ) , then centrifuged . One hundred-fifty microliters of 5 M potassium acetate was added , and each sample was incubated at −20°C overnight . Following centrifugation , supernatants were transferred to new tubes containing 0 . 66 M guanidine hydrochloride and 63 . 3% ethanol solution . The samples were then added to a MOBIO spin filter ( MOBIO ) in a 2 mL microcentrifuge tube ( MOBIO ) . The flow-through was discarded and the filter was washed with 500 µL wash solution ( 10 mM Tris [pH 8] , 1 mM EDTA , 50 mM NaCl , 67% ethanol ) , then further washed by the addition of 500 µL of 95% ethanol . The spin filter was dried by centrifugation , and then transferred to a new 2 . 0 mL microcentrifuge tube . Two-hundred microliters of elution solution ( 10 mM Tris [pH 8] ) were added to the spin filters which were allowed to incubate at room temperature for 15 minutes . Following this , the DNA was eluted . The DNA was stored at −20°C until further use . DNA was subjected to amplification of IS2404 , the enoyl reductase domain , and various variable number tandem repeat ( VNTR ) loci . Those yielding no amplification of the ER domain were diluted ten-fold twice for determination of inhibition of PCR . Dilutions were made of M . ulcerans Agy99 by first placing a loopful of cells into 1 mL of 1% SDS . Aggregates were broken by passing the suspension through a 25 gauge needle 10 times . One hundred microliters were then transferred into a new tube containing 900 µL 1% SDS , and 10-fold dilutions were made . Ten microliters of each suspension was plated in triplicate onto M7H10 plates and allowed to incubate at 32°C for 4–6 weeks at which time colony forming units were counted . In order to determine sensitivity of primer sets targeting ER and VNTR loci within environmental samples , belostomatids were spiked with serial dilutions of M . ulcerans DNA . Eight sacrificed belostomatid samples , each with a wet weight of 160 mg , were placed in separate vials . These vials were spiked with dilutions of M . ulcerans DNA ( prepared as above with the exception that M . ulcerans 1615 was used for this study ) with predicted concentrations ranging from 105 CFU to . 01 CFU . DNA was extracted as described . Primers used for this study are listed in Table 3 . A 719 basepair fragment of the enoyl reductase ( ER ) domain , found on one polyketide synthase gene partially responsible for toxin production , was amplified for samples as well as for M . ulcerans Agy99 and 1615 , M . marinum 1218 , and water ( as positive and negative controls ) using a 50 µL reaction mixture containing 1 µL each of forward and reverse primer ( 1 . 0 µM ) , 10 µL 5× Go Taq reaction buffer ( Promega ) , 1 µL 10 mM PCR nucleotide mix ( Promega ) , 31 . 7 µL ddH2O , 1 . 6 units of Go Taq polymerase enzyme ( Promega ) , and 5 µL DNA template . An average concentration of 10 ng/µL mycobacterial DNA was used for positive and negative controls . Cycling conditions began with an initial denaturation at 94°C for 5 minutes , 35 cycles of 94°C for 1 minute , 58°C for 45 seconds , 72°C for 1 minute , and a final extension of 72°C for 10 minutes . Primers and PCR conditions for amplification of VNTR MIRU 1 and 9 , and loci 4 , 5 , 6 , 8 , 14 , 15 , 18 , 19 , 33 , and ST1 as well as for IS2404 were as previously described [23] , [24] , [25] , [11] . The amplified DNA was subjected to gel electrophoresis using a 1 . 5–3 . 0% agarose gel and band sizes were compared using a 1 Kb DNA ladder ( Invitrogen ) . PCR products from all positive samples were cloned into the pCR2 . 1 Topo vector ( Invitrogen ) and sequenced using an ABI 3100 automated genetic analyzer ( Applied Biosystems ) . IS2404 PCR has been widely used for detection of M . ulcerans in the environment and patients because of the high copy number of the IS element ( 213 ) within the M . ulcerans genome [28] However , evidence from the M . ulcerans genome as well as results from restriction fragment length polymorphisms of IS2404 suggests considerable heterogeneity between copies , as well as the presence of incomplete copies which could lead to production of multiple products [29] . For this reason we developed a PCR method based on amplification of the ER domain of mlsA which encodes a polyketide synthase that produces the mycolactone core , and compared the sensitivity of ER PCR and IS2404 PCR using environmental samples , as well as M . ulcerans cultures . In this study 319 invertebrate and vertebrate samples were analyzed using IS2404 PCR and the PCR products were sequenced . A PCR product of appropriate size was obtained from eight invertebrate samples . However , DNA sequencing showed that only four of the samples contained IS2404 DNA . Although adjustment of PCR parameters improved specificity somewhat , many non-specific products were still amplified . ER PCR of the initial eight IS2404 positive samples yielded four ER positive samples . DNA sequence results confirmed that all four ER positive samples contained ER sequence . Further analysis of DNA from 71 ER positive samples showed that ER DNA was the product in every case . ER is present four times on the mycolactone plasmid . Although there is no evidence concerning plasmid copy number , most large plasmids are present in only 1 or 2 copies per cell making the copy number for the ER target 4–8 [3] . Because we initially assumed there was a clear correlation between copy number and PCR sensitivity , we were concerned that the lower copy number of the ER domain , with respect to IS2404 , might influence the sensitivity of the method . Thus the relative sensitivity of ER and IS2404 PCR was evaluated using 10-fold dilutions of M . ulcerans culture . As few as 10−1 CFU of M . ulcerans could be detected using either method ( Figure 2 ) . These results suggested that ER PCR was adequately sensitive for detection of M . ulcerans in environmental samples where few copies of M . ulcerans might be present . Sensitivity of the primer sets targeting VNTR loci and ER for environmental samples was also determined by spiking samples of belostomatids with serial dilutions of M . ulcerans DNA and performing ER and VNTR PCR . Results from this study show that ER and VNTR DNA could be detected at predicted concentrations as low as 0 . 1 CFU ( Figure S2 ) . During 2004–2006 1 , 068 invertebrate and vertebrate samples were collected from 14 endemic and 12 non-endemic sites with a focus on the Ashanti and Greater Accra regions of Ghana ( Figure 3 ) . Samples included material collected within 1 m2 quadrats ( N = 3 ) as well as those obtained by sweep sampling through vegetation . Identical sampling methods were used for all sites . Endemic sites yielded more samples than non-endemic sties . Of the 1 , 068 samples obtained , 572 ( 54% ) were obtained from endemic sites whereas 496 ( 46% ) were from non-endemic sampling sites . M . ulcerans DNA was detected in only 7% ( 78/1 , 068 ) of the total samples ( Table 4 ) using ER PCR . From the 78 ER positive samples , 42 ( 54% ) were from aquatic environments endemic for Buruli ulcer; whereas 36 ( 46% ) samples were from non-endemic sites . The largest number of ER positive invertebrate samples was collected from Afuaman where 18 invertebrate pooled or individual samples were found to be positive . Six sites yielded only one ER positive pooled or individual sample . These included three endemic sites ( Tontokrom , Bowkrom , and Amasaman ) and three non-endemic sites ( Bretsekrom , Dodowa , and Keedmos ) . Eight sites yielded zero ER positive invertebrate or vertebrate samples ( five endemic and three non-endemic ) . The remaining eleven sites ( six non-endemic and five endemic ) had a range of 2 to 10 PCR positive pooled or individual invertebrate samples . All ER PCR positive results were confirmed by DNA sequencing . ER positive DNA was detected in a broad spectrum of vertebrates and invertebrates representing 30 of the 89 taxa identified . Many taxa , such as Crambidae ( moth ) larvae and Araneae were found repeatedly positive at specific sites during the 2 year sampling period . Two pools of Crambidae larvae were found positive from Subin; one collected 2005 and the other collected 2006 . Araneae have been found positive from sampling of Amasaman 2004 , 2005 , and 2006 . Although some taxa , such as Belostomatidae and Naucoridae have been found IS2404 positive by others [12] , [13] , [14] most ER PCR positive taxa reported in this study have not previously been identified as potential sources of M . ulcerans . M . ulcerans positive taxa represented a wide variety of functional invertebrate feeding groups and life stages ( Table 2 ) [30] . Although most of the positive taxa represented predators , positive results were obtained from collector-gatherers such as those from the family Elmidae ( beetle ) and scrapers such as those from the family Baetidae ( mayfly ) . A complete description of the demography and identification of positive taxa per site are presented in a separate paper ( in preparation ) . Previous reporting of M . ulcerans in Belostomatidae and Naucoridae led us to selectively collect additional samples from these taxa . Seventy-one additional belostomatids and twenty additional naucorids were obtained through selective collection . Of those , 3/71 ( 4% ) belostomatids and 7/20 ( 35% ) naucorids were found to contain ER positive DNA . Although these results suggest that M . ulcerans DNA is widely distributed in invertebrates , the majority of taxa identified ( 59/89 ) were repeatedly negative for M . ulcerans DNA ( Table S1 ) . In some cases where a taxon was represented by a single sample , such as with Calonoida ( copepod ) , little can be said about the absence of M . ulcerans . In other cases such as with Coenagrinidae ( damselfly larvae ) and Pleidae ( backswimmer ) , over 100 individuals were sampled . The absence of ER PCR positive results from these taxa is more meaningful . Out of 260 samples of water filtrate tested ( 130 from non-endemic and 130 from endemic sampling sites ) , 97 ( 36% ) were ER PCR positive . Sixty of the 97 ER positive filtrate samples ( 61% ) were from areas non-endemic for Buruli ulcer , while 37 ( 38% ) of the ER positive filtrate samples were from endemic areas . PCR was also conducted on 100 soil samples; 50 of which were from endemic sites and 50 from non-endemic sites . M . ulcerans DNA was detected in 3% ( 3/100 ) of the soil samples ( Table 4 ) . Each of these three samples was collected from the floor of the water body . Two of the three ER PCR positive soil samples were from an area endemic for Buruli ulcer ( Nyame-Bekyere and Subin ) while the third was from an area non-endemic for Buruli Ulcer ( Abbeypanya ) . Although ER PCR is a reasonable preliminary test for the identification of M . ulcerans , the discovery of other mycolactone producing mycobacteria ( MPM ) in fish and frogs revealed that mycolactone genes are not M . ulcerans specific [26] , [31] . In order to distinguish between M . ulcerans and other MPM , a VNTR-based method was developed based on published VNTR sequence [23] , [24] , [25] . For this analysis , a panel of 6 Ghanaian M . ulcerans isolates obtained from patients in the same regions where the environmental samples were collected was compared to a panel of MPM species . Primers targeting VNTR loci 4 , 8 , 14 , 15 , 18 , and MIRU 9 did not distinguish between Ghanaian isolates of M . ulcerans and other MPM , although several of these loci had been previously used to discriminate between Beninese M . ulcerans and other MPM [24] , [25] . Although some studies have found only 1 biovar of M . ulcerans in West Africa suggesting very little heterogeneity among M . ulcerans isolates within Africa [24] , [25] one paper , which investigated a large group of M . ulcerans isolates from Ghana identified three different biovars [23] . In this paper , VNTR analysis of 6 M . ulcerans isolates from the Greater Accra , Central and Ashanti regions revealed three M . ulcerans VNTR profiles , A , B , and C based on MIRU 1 , locus 6 and STI ( Table 5 ) . Profile A strains contained one copy of MIRU 1 , one copy of locus 6 , and one copy of ST1 ( 1 , 1 , 1 ) . Profile B strains had three copies of MIRU 1 , one copy of locus 6 , and one copy of ST1 ( 3 , 1 , 1 ) and profile C consisted of a single isolate with three copies of MIRU 1 , one copy of locus 6 , and two copies of ST1 ( 3 , 1 , 2 ) . Two of these VNTR profiles , B and C , were previously identified by Hilty et al [23] whereas profile A , characterized by a single copy of MIRU 1 and one copy of ST1 represented a new profile . These VNTR loci also distinguished M . ulcerans from other MPM ( Table 5 ) . Finally , the addition of locus 19 made it possible to distinguished M . liflandii , a newly discovered frog pathogen , from mycolactone producing fish pathogens M . marinum and M . pseudoshottsii ( Table 5 ) . Two separate VNTR profiles were identified among mycolactone producing M . marinum isolates and these were associated with different habitats ( Table 5 ) . Whereas fish from salt water had profile D , those from freshwater had profile E ( Table 5 ) . Profile D included one copy of MIRU1 , four copies of locus 6 , two copies of ST1 , and two copies of locus 19 ( 1 , 4 , 2 , 2 ) , and profile E had one copy of MIRU1 , two copies of locus 6 , one copy of ST1 , and two copies of locus 19 ( 1 , 2 , 1 , 2 ) . Despite the great geographical distance between the Red and Mediterranean Seas and the Chesapeake Bay , MPM M . marinum isolated from sea bass ( Siganus nivulatus ) and M . pseudoshottsii isolated from striped bass ( Morone saxatilis ) shared identical 1 , 4 , 2 , 2 VNTR profiles . VNTR analysis revealed a single VNTR profile for M . liflandii ( 1 , 2 , 2 , 1 ) . These results showed that VNTR could be used to differentiate MPM found in environmental samples in Ghana . To discriminate between M . ulcerans and other MPM , 78 ER-PCR positive samples collected from standardized sampling and 10 ER positive belostomatids and naucorids ( 3 belostomatids and 7 naucorids ) that were selectively collected were tested for the presence and copy number of MIRU1 , locus 6 , ST1 , and , if applicable , locus 19 . Of these samples , VNTR profiles were obtained from 67 invertebrate/vertebrate samples ( Table 6 ) . The remaining 31 samples could not be VNTR typed presumably due to insufficient material . VNTR profiling showed that only 12 of these 67 samples ( 18% ) had a VNTR profile which matched M . ulcerans ( Table 6 ) . Seven of these were collected from aquatic environments endemic for Buruli ulcer , and five of these were from non-endemic water bodies . M . ulcerans Profile A was identified in 9 different invertebrate species , whereas M . ulcerans profile C , found in the genome sequence strain Agy99 was detected in specimens of a Nepidae ( Order Hemiptera ) , a Belostomatidae and an unidentified spider . VNTR MPM profile D was found in three samples , including a tadpole ( Anura ) and two predacious aquatic insects ( Coleoptera: Families Hydrophilidae and Dytiscidae , Table 4 ) . M . ulcerans VNTR profile A and MPM profile D was obtained from different samples of Dytiscidae , Anura and Hydrophilidae . Both Anura and Hydrophilidae samples were collected from the same endemic site . The Dytiscidae samples were collected from two different endemic sites . M . ulcerans profiles A and C were identified in two separate Belostomatidae samples collected from separate sites , one endemic and one non-endemic . These results suggest that M . ulcerans and other MPM occupy the same water body . VNTR analysis of 82 ER PCR positive water filtrates yielded 8 M . ulcerans positive samples . One of these was profile B whereas the other 7 typed as profile A . Four of these samples were from non-endemic areas , while the remaining four samples were from endemic areas . Four of the 82 ER PCR positive water filtrates yielded MPM profile E . Two of these were from endemic regions whereas two were from non-endemic sites . The identity of all VNTR products was confirmed by sequence analysis . Representative gels illustrating VNTR profiles from various sample types are given in Figure S1 . These data suggest that human endemicity data do not reliably predict the presence of M . ulcerans in Ghana . Ninety-six glass slides were submerged in water bodies associated with human use in the communities of Amasaman ( endemic ) and Adigon , ( non-endemic ) . From these , 47 slides were collected at 21 , 42 and 98 days . At 21 days , biofilm formation on slides collected from Adigon was sparse , but became progressively denser over the course of the experiment . In contrast , at Amasaman , the endemic site , biofilms were very dense by 21 days , but became less dense over the course of the study ( Figure 4 ) . Acid-fast bacilli were found on 45 of 47 slides ( Figure 4 ) . Microscopic analysis of the biofilm community showed the presence of diatoms and fungus as well as a mixed population of bacteria and considerable detritus . Acid-fast bacilli occurred in clusters or small groups , but were not associated with other flora present on the slide consistent with the ability of mycobacteria to adhere to glass [32] . Of the 47 biofilm slides analyzed , 37 were ER PCR positive ( Table 4 ) . VNTR profiles of 17 ( 46% ) of these matched M . ulcerans , while 8 matched VNTR profiles of other MPM . VNTR analysis of slides collected from Adigon at 21 days was not conducted because all samples were ER negative ( Figure 5 ) . Three of five ER positive slides ( 60% ) collected at 42 days from Adigon had M . ulcerans VNTR profile A , whereas one of the slides had a VNTR profile matching other MPM ( profile D ) . M . ulcerans VNTR profiles were not found at Adigon at 98 days although VNTR patterns matching MPM were found on two slides . One of these corresponded to M . liflandii ( profile F ) while the other matched that of MPM associated with fish ( profile E ) . Nine of the twelve ( 75% ) ER positive slides taken from Amasaman at 21 days had a M . ulcerans VNTR profile matching profile A , whereas a VNTR profile matching that of M . liflandii ( profile F ) was found on two slides . Five of six ( 83% ) ER positive slides taken at 42 days from Amasaman had M . ulcerans profiles . M . ulcerans was not detected on the slides taken from Amasaman at 98 days although three slides ( 60% ) produced VNTR signatures matching fish-associated MPMs ( D and E ) . These results show the evolution of biofilm communities through time . The absence of M . ulcerans at 98 days is particularly interesting and could be explained by spontaneous detachment of the biofilm , or by grazing by tadpoles or invertebrates . The analysis of VNTR data from environmental samples is complicated by many factors not present when analysis is performed on a pure bacterial colony . DNA extracted from insects , frogs , fish or filters contains DNA from a complex population of organisms . If VNTR profiling is a valid tool for detection of M . ulcerans in environmental samples , ER negative samples should also be negative for M . ulcerans by VNTR PCR . If however , specific VNTR sequences are present in a number of different organisms , or in bacteria which do not produce mycolactone , VNTR analysis of ER negative sites could yield a M . ulcerans or MPM profile . For example , if 1 repeat of MIRU1 , locus 6 and ST1 were present in each of three different bacteria within a single environmental sample , this sample would produce a VNTR profile consistent with M . ulcerans . If this were the case , VNTR analysis of environmental samples would have little value in the identification of M . ulcerans . To address this possibility , VNTR analysis was performed on two sets of ER negative samples . The first set consisted of ER negative DNA from 35 samples representing a broad spectrum of samples collected at many different sites . The second set of samples was a complete sample set of 34 samples from a single ER negative site . Invertebrate , vertebrate , water filtrate , and soil samples were represented in each set . Though some of these samples produced bands for an individual locus , none of these samples produced a M . ulcerans VNTR profile . Twenty-six sites were sampled from 2004–2006 ( Table 7 ) . Fourteen were endemic and twelve were non-endemic . These sites represented water bodies from south-central regions in Ghana with a focus on the Greater Accra and the Ashanti regions . All samples from seven sites were ER negative suggesting the absence of any MPM including M . ulcerans . Six sites had samples with DNA insufficient for VNTR analysis . VNTR profiling was performed on the remaining thirteen sites , seven endemic and six non-endemic sites . M . ulcerans profile A was found in 6 of the endemic sites . Three endemic sites had only one VNTR profile: Ampa Abena and Nyame-Bekyere had M . ulcerans profile A , and Subin had MPM profile E . Two or more VNTR profiles were found within the same water body at four of the endemic sites . Bonsaaso was found to contain M . ulcerans VNTR profiles A , B and C . Along with M . ulcerans profile A , Bowkrom and Afuaman also had MPM profiles E and D , respectively . Amasaman was found to contain two M . ulcerans VNTR profiles ( A and B ) , one of the MPM M . marinum VNTR profiles ( profile D ) , and the profile corresponding to M . liflandii ( profile F ) . Samples from six non-endemic sites produced VNTR profiles . However , there was less diversity of VNTR profiles from the non-endemic sites than endemic sites . Four of these sites were represented by one M . ulcerans profile ( either profile A or C ) , and one of the sites , Afienya , had only a MPM M . marinum VNTR profile ( profile E ) . Adigon was the only non-endemic site which yielded multiple VNTR profiles . VNTR profiles of M . ulcerans ( profile A ) , MPM M . marinum ( profiles D and E ) , and M . liflandii ( profile F ) were all obtained from biofilm samples collected in Adigon . VNTR profiles representing M . ulcerans and other MPMs were obtained from sites from both the Greater Accra and the Ashanti regions ( Figure 3 ) . M . ulcerans and MPM VNTR profiles were found within the same site more frequently in the Greater Accra region than in the Ashanti region . M . ulcerans VNTR profiles A , B and C ( 1 , 1 , 1 , 3 , 1 , 1 and 3 , 1 , 2 respectively ) were found in both the Greater Accra and the Ashanti regions . MPM M . marinum profile D was found only in the Greater Accra region , whereas profile E was found in both regions . Profile F ( M . liflandii ) was found in two sites of the Greater Accra region . In this paper we present results from a large scale study of M . ulcerans in the environment . Although a number of studies have reported the presence of M . ulcerans in environmental samples from endemic regions [13] , [16] , [17] , [33] , this is the first study where standardized ecological methods were used to reduce sampling bias , and the first to include longitudinal data from both Buruli ulcer endemic and non-endemic sties . One of the mysteries of Buruli ulcer is the close proximity of endemic and non-endemic villages . For example , whereas the disease is rarely reported from the Ga East district of the Greater Accra region in Ghana , it is endemic in the Ga West district despite the fact that endemic and non-endemic villages may be separated by only a few kilometers ( Figure 3 ) . Since the climate , rainfall , plant populations and ethnic groups in Ga East and Ga West are similar it has been difficult to understand the differential occurrence of Buruli ulcer within these regions . The most important finding from this study is that , whereas Buruli ulcer occurs within discrete geographic village foci within endemic regions , M . ulcerans is widely distributed in water bodies in both endemic and non-endemic villages in the Greater Accra and Ashanti regions . This is consistent with its position as an environmental pathogen . We have also been able to repeatedly detect the presence of M . ulcerans within some sites over a 27 month framework suggesting the long term survival and presence of M . ulcerans in specific locations . These results clearly show that the focal occurrence of Buruli ulcer within the Greater Accra and Ashanti regions cannot be explained by the presence or absence of M . ulcerans in the environment . Thus other factors such as demography and human behavior may be important in the epidemiology of Buruli ulcer in these regions . In contrast , there are large geographic areas in West Africa such as the Volta region of Ghana , or drier Northern parts of Ghana , Benin and Togo , where Buruli ulcer has never been reported . It has been assumed that the absence of Buruli ulcer from these regions is based on environmental constraints which restrict the growth of M . ulcerans or potential reservoir species . Results from an on-going project in the Volta region confirm this hypothesis in that we have failed to reveal a single M . ulcerans positive sample out of hundreds of invertebrate , water filtrate or macrophyte samples from 20 sites sampled . The absence of Buruli ulcer in Volta is explained by the absence of M . ulcerans ( work in progress ) . In a clinical setting the use of a single PCR target for detection of a pathogen is widely accepted . However , the use of a single PCR target for identification of bacteria in an environmental sample is rarely adequate . In Ghana , analysis of many IS2404 positive samples revealed the presence of mycolactone producing mycobacterial species ( MPMs ) other than M . ulcerans as had been predicted [29] . In contrast , in Australia IS2404 PCR appears to be specific for M . ulcerans because of the absence of other MPMs [33] . Here we provide the first evidence for the presence of MPMs in West Africa and show that MPMs and M . ulcerans share aquatic environments . The pathogenic potential of MPM for humans is unknown , although the lower growth temperature of some of these species makes them unlikely human pathogens [26] . The fact that the strain complexity of MPMs and M . ulcerans is greater in endemic areas and greatest within the Greater Accra region is an intriguing finding which needs further investigation . The use of geographic-specific VNTR profiles in following chains of transmission is extremely important since the heterogeneity of M . ulcerans isolates appears to differ within different West African countries [23] , [24] , [25] . For example , data based primarily on patient isolates from Benin led to the conclusion that there was a single West African M . ulcerans clone . However , several biovars have been identified in Ghana [23] . Our results agree with those of Hilty et al [23] in showing the presence of that at least 3 different VNTR profiles in Ghana . Thus it is important when discriminating between M . ulcerans and other MPM that a geographically representative set of patient isolates is used . Our initial concerns regarding the effect of low target copy number on the sensitivity of PCR methods reflected our naiveté regarding PCR theory . We had not considered that the efficiency of the PCR reaction depends on many factors including the efficiency of primer binding , the length of the product and local DNA conformation or that because the reaction is exponential , the first few targets bound may rapidly become the major products . Experimental results confirm this theory since others have found no difference between the use of IS2404 PCR and that of 16sRNA PCR for detection of M . ulcerans in human samples despite the enormous difference in copy number [34] and results from VNTR analysis of clinical isolates show gel bands with an intensity never reported for IS2404 PCR [23] . It is possible that the fact that VNTR sequences are non-coding segments of DNA may make them more accessible to primer binding . Our studies confirm the presence of M . ulcerans in predacious aquatic insects including Belostomatidae and Naucoridae families reported by Portaels et al [15] and extend these findings by showing that VNTR profiles from these insects match those of human isolates of M . ulcerans . Belostomatids were common in many sites sampled throughout the year . However , even where large numbers of Belostomatidae were collected the rate of M . ulcerans infection was very low . In Ghana , despite repeated seasonal sampling the numbers of naucorids found were very low ( paper in preparation ) . Evidence for the role of naucorids as potential M . ulcerans vectors comes from studies in Cote d'Ivoire [16] . Insect population studies are needed to confirm whether naucorids are more abundant in Cote d'Ivoire than in Ghana . Our results show that M . ulcerans is widely distributed within invertebrate communities in aquatic environments . However , none of the M . ulcerans-positive , predacious invertebrates are hematophagous; thus the frequency with which humans are bitten would be expected to be quite low [35] . Although potential trophic relationships exist between several taxa studied ( belostomatids , for example , feed on many other invertebrates and vertebrates and also cannibalize each other ) , it will take considerably more work to elucidate chains of transmission within the environment . Results presented here are based on determining the presence or absence of M . ulcerans in an environmental sample . Further studies need to be conducted using quantitative PCR methods to determine which species are most heavily infected and thus are more likely to serve as vectors . Although it has been reported that snails and fish may harbor M . ulcerans [17] our results suggest the possibility that many of the IS2404 positive mycobacteria detected are MPM other than M . ulcerans . In our studies M . ulcerans was never detected in fish or snails , although other MPM were identified in later studies . The most consistently M . ulcerans-positive samples detected were filtered water and biofilms on glass slides . This suggests that exposure of open lesions to infected water cannot be ruled out as a potential source of infection . A general problem regarding detection of M . ulcerans in environmental samples is that evidence has come almost solely from detection of M . ulcerans DNA and under-estimation of M . ulcerans could result due to the presence of PCR inhibitors . Our results suggest that current methods are effective in eliminating PCR inhibitors since dilution of samples did not result in the detection of many additional ER positive samples and none of those detected through dilution could be confirmed by sequencing . Despite the broad spectrum of samples we did not find evidence for inhibitors in any particular taxa or sample type tested . Nonetheless , the possibility exists that the number of positive M . ulcerans positive samples may be underestimated . The use of slide biofilms for trapping mycobacteria in the environment has proven particularly useful since it provides preliminary physical evidence for the presence of mycobacteria ( AFB staining ) along with molecular evidence , and facilitates longitudinal studies . The numbers of slides used and placement of PVC pipes are crucial because of the inevitable loss of slides through changes in water level , or disturbance by animals or humans . There was a decrease of DNA samples from slides giving a VNTR profile matching M . ulcerans between 42 and 98 days in the two water bodies ( Figure 5 ) . There was , however , an increase in DNA samples from slides producing a VNTR profile matching other MPM s . These data suggest bacterial community dynamics between M . ulcerans and other MPMs . In summary , we have developed new methods for mapping the distribution of M . ulcerans in aquatic environments and applied these in the Greater Accra and Ashanti regions of Ghana . This work is part of a much larger five year project in which data from water chemistry , LandSat satellite imaging of land cover , and macrophyte and aquatic invertebrate population structure will be used to define the broad ecology of M . ulcerans . The presence of M . ulcerans in both endemic and non-endemic villages within endemic regions suggests that studies of human ecology will be necessary to unravel the mysteries surrounding the transmission of M . ulcerans to humans . Our goal in this work is to define the M . ulcerans environment in order to develop programs for preventing human exposure . The findings presented here show the possibility of tracing transmission of M . ulcerans from the environment to humans . This work represents a small step towards solving the mysteries surrounding human infection .
Buruli ulcer is an ulcerative skin disease caused by Mycobacterium ulcerans . Though usually not fatal , ulceration can cover up to 15% of the body , with treatment being costly and sometimes painful . Primary risk for Buruli ulcer in Africa is exposure to stagnant water , but the route of transmission is unknown . Detection of M . ulcerans in aquatic insects in endemic sites suggests the presence of aquatic reservoirs . This article reports results from the first investigation into the ecology of M . ulcerans based on random sampling of both endemic and non-endemic aquatic sites . Development of a method for discriminating M . ulcerans from closely related mycobacterial pathogens made it possible to determine the distribution of M . ulcerans in aquatic environments . This article demonstrates the presence of M . ulcerans DNA in both endemic and non-endemic sites within aquatic insects , water filtrate , and glass-slide biofilm communities . This article provides data suggesting that M . ulcerans is more broadly distributed than the human disease it causes . This study provides an initial step for future work on whether certain M . ulcerans strains are particularly successful human pathogens and suggests that research on specific human water contact factors may provide insight into the transmission of M . ulcerans .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[ "microbiology/environmental", "microbiology" ]
2008
Distribution of Mycobacterium ulcerans in Buruli Ulcer Endemic and Non-Endemic Aquatic Sites in Ghana
Interleukin ( IL ) -21 is an attractive antitumor agent with potent immunomodulatory functions . Yet thus far , the cytokine has yielded only partial responses in solid cancer patients , and conditions for beneficial IL-21 immunotherapy remain elusive . The current work aims to identify clinically-relevant IL-21 regimens with enhanced efficacy , based on mathematical modeling of long-term antitumor responses . For this purpose , pharmacokinetic ( PK ) and pharmacodynamic ( PD ) data were acquired from a preclinical study applying systemic IL-21 therapy in murine solid cancers . We developed an integrated disease/PK/PD model for the IL-21 anticancer response , and calibrated it using selected “training” data . The accuracy of the model was verified retrospectively under diverse IL-21 treatment settings , by comparing its predictions to independent “validation” data in melanoma and renal cell carcinoma-challenged mice ( R2>0 . 90 ) . Simulations of the verified model surfaced important therapeutic insights: ( 1 ) Fractionating the standard daily regimen ( 50 µg/dose ) into a twice daily schedule ( 25 µg/dose ) is advantageous , yielding a significantly lower tumor mass ( 45% decrease ) ; ( 2 ) A low-dose ( 12 µg/day ) regimen exerts a response similar to that obtained under the 50 µg/day treatment , suggestive of an equally efficacious dose with potentially reduced toxicity . Subsequent experiments in melanoma-bearing mice corroborated both of these predictions with high precision ( R2>0 . 89 ) , thus validating the model also prospectively in vivo . Thus , the confirmed PK/PD model rationalizes IL-21 therapy , and pinpoints improved clinically-feasible treatment schedules . Our analysis demonstrates the value of employing mathematical modeling and in silico-guided design of solid tumor immunotherapy in the clinic . Cancer is a multi-faceted disease , involving complex interactions between neoplastic cells and the surrounding microenvironment [1] . The prospect of immunotherapy , i . e . stimulating endogenous immune responses by various molecular and cellular factors , is emerging as a promising approach against this disease [1] , [2] , [3] . One of the latest candidates for solid cancer immunotherapy is Interleukin ( IL ) -21 , a γc-signaling protein of the IL-2 cytokine family with versatile immune-modulating properties [4] , [5] , . IL-21 has demonstrated substantial antitumor responses in several independent preclinical studies , in which mice inoculated with diverse transplantable syngeneic tumor lines were treated with the drug via cytokine-gene transfection , plasmid delivery , or injection of the recombinant protein [9] . In Phase I and IIa clinical trials , IL-21 was well tolerated and triggered moderate antitumor activity in some renal cell carcinoma ( RCC ) and metastatic melanoma ( MM ) patients [10] , [11] , [12] , [13] , [14] . More recently , clinical trials of IL-21 in combination with the tyrosine kinase inhibitor sorafinib for the treatment of RCC , and Rituximab for the treatment of non-Hodgkin's lymphoma , have also been investigated with encouraging results [15] . Yet , the intricate biology of IL-21 may set hurdles for its clinical development . Produced mainly by activated CD4+ T cells , IL-21 induces anticancer immunity predominantly by stimulation of natural killer cells ( NKs ) and/or cytotoxic T lymphocytes ( CTLs ) [4] , [5] , [6] , [7] . The cytokine regulates various cellular and humoral pathways of immunity , and exerts conflicting stimulatory and inhibitory effects on several cell types [9] , [16] , [17] . Recent evidence for anti-angiogenic effects of IL-21 [18] further complicates its dynamical influence on the tumor microenvironment . Considering this biological complexity , traditional “trial-and-error” methodologies for clinical IL-21 therapy design are likely inefficient , and ought to be replaced by new guided approaches to maximize drug efficacy . Rational and systematic planning of anticancer therapy may be directed by mathematical modeling and computer-aided analysis , which provides a better understanding of the involved dynamics . Over the past 25 years , mathematical modeling strategies have been applied in oncology-focused studies investigating tumor progression , angiogenesis and interactions with the immune system [19] , [20] , [21] , [22] , [23] , [24] . Models for cytotoxic , cytostatic and cytokine-based direct and supportive cancer drugs have been introduced , with some being subsequently validated in preclinical and clinical settings [23] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] . These strategies have highlighted the importance of adequate selection of therapeutic regimens to achieve desired outcomes , by carrying out in-depth analysis of optimal times , dosages , and durations of treatment . Pharmacokinetic ( PK ) and pharmacodynamic ( PD ) modeling of anticancer agents can be particularly useful for clinical design of treatment [37] , [38] . We have previously developed a mathematical model for the local dynamic effects of IL-21 on solid cancers . The model focused on interactions of IL-21 with NKs/CTLs , effector cytotoxicity against target cells , and immune memory , providing initial understanding of the optimal conditions for IL-21 gene therapy [39] , [40] . Here , we have designed a new comprehensive PK/PD/disease model to predict clinically relevant scenarios of IL-21 treatment following intravenous ( IV ) subcutaneous ( SC ) or intraperitoneal ( IP ) administration in different cancer indications . The model forecasts long-term effects of the drug by integrating newly described PK/PD processes together with a disease model , based on our initial in situ model [39] , [40] . This new combined model was retrospectively and prospectively validated by in vivo experiments in IL-21-treated mice bearing melanoma ( B16 ) or renal cell carcinoma ( RenCa ) . Model predictions provide substantial insights concerning adequate planning of systemic IL-21 therapy in solid cancers . All experiments were conducted according to Novo Nordisk principles for animal studies , as approved by the Danish National Ethics Committee on Experimental Animals , and in accordance with National Institute of Health guidelines for the care and use of laboratory animals . Data were collected from a published preclinical study in which mice bearing B16 and RenCa tumors were treated with IL-21 by various strategies [41] . Briefly , tumors were induced at day 0 , and a daily ( B16 ) or 3×/week ( RenCa ) IL-21 regimen ( 50 µg/dose ) was applied SC or IP either at an “early” stage ( day 3 in B16; day 7 in RenCa ) , or at a “late” stage ( day 8 in B16; day 12 in RenCa ) of tumor development . The tumor was measured several times until experiment termination . Data were available from additional unpublished dose-titration experiments in RenCa: IL-21 was given SC , 1× or 3×/week , and groups of mice ( n = 6 ) were assigned a dose between 1-50 µg . The complete database was a priori divided into “training datasets” for model parameter estimation , and “validation datasets” for model verification . In new prospective experiments designed to test model-suggested regimens , 7-8-week-old wild type C57BL/6 mice ( Taconic Europe A/S , Denmark ) were inoculated SC in the right flank with 1×105 B16F0 melanoma cells ( American Type Culture Collection ( ATCC ) , CRL-6322 ) on day 0 . Recombinant murine IL-21 ( Novo Nordisk A/S , Denmark ) or PBS was injected SC from day 3 , when tumors were visible . IL-21 was given at 12 µg/day , 50 µg/day , or 25 µg twice a day , each group including n = 10 mice . Tumor volumes were calculated by the formula based on the two perpendicular diameters d1 and d2 measured approximately 3×/week with digital callipers . All experiments were carried out blindly , without the investigator's knowledge of model predictions . Animals were randomized and ear-tagged prior to treatment onset and euthanized when individual tumor volumes reached 1000 mm3 . The new comprehensive systemic model for IL-21 immunotherapy contains PK/PD effects merged with disease interactions , as schemed in Fig . 1 . The system is described hereafter , and the coupled ordinary differential equations ( ODEs ) are fully detailed in the Text S1 ( sections A-B ) . The model ( Fig . 1 ) was implemented in C ( Microsoft Visual Studio . NET ) and MATLAB ( The MathWorks , Natick , MA ) programming platforms . The system was solved by fourth-order Runge Kutta integration . Model parameters were evaluated by a customized numerical method based on Hooke and Jeeves optimization [48] combining global and local search heuristics and least-squares curve-fitting . Parameter sets achieving maximal model agreement with experimental training data were selected ( see Text S1 , Tables S1-S2 ) . The model was simulated under numerous IL-21 regimens , differing in onset , duration , dose , inter-dosing interval , route , etc . All simulations were repeated several times to ensure output consistency . Retrospective verification of the model was accomplished by checking its prediction accuracy , via statistical comparison of its output with prior independent validation datasets ( see Experimental data and [41] ) : Model simulations were conducted under the specific tumor settings and treatment conditions of each prior experiment . For prospective model validation , selected model-identified regimens were tested experimentally , and results were statistically compared to model predictions at the data sampling times . The goodness-of-fit between the model output and experimental data was determined by calculating the coefficient of variation ( R2 ) . To compare between experimental datasets , Student's t-test ( two-tailed , assuming equal variance ) was applied . A P< . 05 value was considered statistically significant . First , we examined the sensitivity of the model to small variations in the value of the plasma-tissue correlation factor s , being that this pivotal parameter simplifies rather complex PK processes . Simulations of the experimental early-onset IL-21 regimen ( 50 µg/day applied SC/IP ) in the B16-challenged setting were carried out under diverse s values , in the vicinity of those obtained through curve-fitting ( see Materials and methods and Fig . 2 ) . After increasing or decreasing s values by two-fold , model predictions still accurately retrieved the murine data ( R2>0 . 90; Fig . 2 ) , and were comparable to the original fits ( Fig . 2 , “Model fit” ) . Interestingly , model predictions remained precise even when modifying the values of the effector-tumor interaction coefficients k1 and k2 ( see Text S1 , section C , and also Fig . S3 ) . These results indicate that model predictions are robust even when s , k1 and k2 values slightly diverge , meaning that different numeric combinations of these parameters , i . e . , multiple NK:CTL ratios , can accomplish the same therapeutic effect . This implies a potentially wide window of IL-21 doses within which effects may be comparable . Our primary goal was to validate the model's predictive accuracy . We therefore compared its output to the experimental B16 progression following a late ( day 8 ) onset regimen of IL-21 , given at 50 µg/day SC/IP for 3 weeks [41] . All late treatment simulations were strongly in line with the independent validation data ( R2>0 . 90; Fig . 3A ) , thus verifying the model . Notably , the model was able to recapitulate the biological behavior even under the aforementioned modifications in s , k1 and k2 parameter values ( data not shown ) . Next we assessed the model's generality by investigating whether it can predict IL-21 therapy outcomes in other solid cancer indications , such as RenCa . Tumor growth and selected immune system parameters were set for RenCa , using training data in untreated mice and previously calibrated parameter values for moderately-immunogenic cancers ( see Materials and methods and [39] ) . Other parameter values were set exactly as in the B16 case . Simulations of the experimentally-applied IL-21 treatment of 50 µg at 3×/week , given for 3 weeks [41] , showed model predictions to be strongly akin to the observed dynamics under late ( day 12 ) therapy administered SC , as well as in early ( day 7 ) and late IP regimens ( R2>0 . 90; Fig . 3B ) . Under the early SC regimen , predicted responses were slightly weaker than observed , yet still remained within the measurement's standard deviation ( R2>0 . 73; Fig . 3B , upper panel ) . To further validate the model for RenCa , we simulated it to predict the effects another experiment that applied lower IL-21 doses ( between 1–20 µg , SC 3×/week for 3 weeks ) . Predictions were in agreement with the validation set readouts in most doses ( R2>0 . 94; Fig . 3C ) , collectively demonstrating a moderate dose-dependent decrease in IL-21-mediated tumor eradication . The 10 µg ( 3×/week ) simulation experiment gave a good , but slightly lower , model-data correlation ( R2>0 . 83; Fig . 3C ) . The model also successfully retrieved a retrospective experiment testing a 30 µg ( 1×/week ) IL-21 treatment schedule ( R2>0 . 90; Fig . 3C ) . Having validated the model , we used it to gain insights into better IL-21 therapy in the B16 setting . In particular , we searched for regimens that would be superior to the standard daily SC 50 µg treatment applied previously [41] . First , we tested whether the treatment initiation time is a critical factor in determining IL-21 effects , by simulating different onsets of the standard daily regimen . The model predicted that earlier therapy initiation results in stronger anticancer responses , as expected ( Fig . 4A ) . The simulated tumor mass at the end of therapy ( day 20 ) was lowest under the earliest regimen , which began one day after B16 challenge: This final tumor load was roughly 15% lower than that obtained in the standard treatment initiated at day 3 . In contrast to this early regimen , the tumor load resulting from a delayed regimen , initiated at day 10 , was doubled ( Fig . 4A ) . Further delayed regimens ( with onsets as high as day 17 ) were even less favorable ( data not shown ) . These results collectively emphasize the importance of early-onset therapies . Notably , however , not even the earliest treatment onset was able to fully eradicate the tumor . Simulations were performed also to see whether the anticancer response could be improved by fractionating the IL-21 regimen into a more intensive high-dosing protocol , as suggested for other drugs [34] , [49] . To design alternative schedules , the daily IL-21 regimen ( 16 SC injections , 50 µg each , given from day 3; [41] ) was taken as a reference point: the same total dose ( 800 µg ) was distributed differently across the treatment window , using various doses and inter-dosing intervals , creating a collection of regimens to be tested . Intriguingly , the model predicted that a more intensive schedule , applying two 25 µg doses per day at a 12-hour inter-dosing interval , would lead to a 45% lower tumor mass than that obtained under the standard daily 50 µg regimen ( Fig . 4B ) . Fractionation into even smaller doses given every few hours produced slightly lower tumor sizes , yet these responses were not significantly better than the 25 µg regimen outcomes ( Fig . 4B ) . In fact , not even the most fractionated schedule could arrive at full eradication of the tumor . At the other end , less fractionated regimens comprising large IL-21 doses given every few days had significantly weaker efficacy ( Fig . 4B ) . In order to verify our prediction that the fractionated 25 µg/12 hour regimen would be superior to the standard 50 µg/24 hour schedule , the two were experimentally applied in B16-challenged mice . Even though both schedules effectively attenuated tumor progression as compared to control PBS-treated mice ( *p< . 001; Fig . 4C ) , the 25 µg/12 hour regimen was considerably more successful than the standard 50 µg daily regimen ( **p< . 05; Fig 4C ) , as mathematically predicted . The observed tumor dynamics under the 25 µg regimen had an excellent fit with the prior model predictions ( R2>0 . 90; Fig . 4C ) , providing strong and quantitative prospective validation of the model's precision . We considered that the fractionated regimen may not be clinically practical , since it could involve increased costs of therapy , and , at least in IV delivery , would possibly require hospitalizing patients . Therefore , the search for better treatment was limited to simple , widely-acceptable daily administration schedules . Regimens of one IL-21 dose per day ( e . g . 16 SC injections given between days 3–20 following B16 inoculation ) were simulated under different dose intensities: A dose-dependent increase in the response , reflected by lowered tumor masses , was predicted for very low ( <5 µg ) or very high ( >50 µg ) levels ( Fig . 5A ) . Yet interestingly , similar outcomes were predicted for the 5–50 µg dose range ( Fig . 5A ) . This might be explained by the conflicting roles of IL-21 , enhancing CTL activation while drastically reducing NK numbers at the same time [39]; It is likely that in this dosing range , IL-21-increased CTL responses fail to promote further tumor shrinkage due to the IL-21-inhibition of NK availability . A prospective experiment in B16-induced mice examined whether a low dosing regimen in the plateau range ( i . e . 12 µg/day ) could indeed be as effective as the standard 50 µg/day treatment . Beginning on day 3 following tumor challenge , the two doses were applied SC , and the tumor mass was measured until day 17 . Both the 12 µg and 50 µg doses induced sufficient antitumor responses in the mice ( *p< . 05 and **p< . 001 compared with PBS-treated mice; Fig . 5B ) . Although the 12 µg dose appeared slightly less potent , its effect was not significantly different from the 50 µg schedule ( ns , p> . 05; Fig . 5B ) , as anticipated by the model . Indeed , the model prediction ( Fig . 5A ) fit the 12 µg/day outcome to a good degree ( R2 = 0 . 89 , Fig . 5B ) . These findings further validate the model , and are the first indication of an IL-21 dosing range executing equally potent effects . Immune-targeted therapy is increasingly apparent in the battle against cancer . Several reagents are in development within this scope , some already approved for use in certain indications [1] , [9] , [50] . In this study , we have devised and validated a clinically-relevant mathematical model integrating the PK/PD effects on immune and disease interactions of IL-21 , one of the recent immunotherapeutic drugs under focus in solid cancers [9] . Following its verification , our model was used for suggesting beneficial IL-21 treatment policies . Previous attempts to model cytokine-based immune modulation of solid malignancies have been mainly theoretical , helping to elucidate certain characteristics of the tumor-immune system cross-talk and providing important insights into treatment success ( see for example [23] , [31] , [33] ) . Our former model focused on the heart of the IL-21 response , retrieving the effects of cytokine gene therapy to a good extent . Yet , its predictions could not be extrapolated to the clinical realm . The current work is thus among the first biomathematical studies accounting for practical treatment aspects of cytokine immunotherapy in general , and IL-21 treatment in particular . Our current model deals with realistic PK and PD effects on disease progression , clinically-feasible scheduling , patient compliance , etc . Moreover , in contrast to the customary stand-alone PK/PD modeling approach , we have integrated IL-21 PK/PD with specific effects on the involved biological processes , to give a mechanistic , yet minimal , model . Particularly , our PD/disease model accounts for real entities of the IL-21 biological processes ( effector cells , etc . ) , which enabled us to use measurable data and make testable quantitative predictions . At the same time , we kept our model concise thanks to condensation of other overly complex biological entities ( cytotoxic proteins , etc . ) which are less cardinal and often not measured experimentally . Overall , our approach provides a robust model that can forecast the long-term anticancer effects of a specific immunotherapeutic cytokine , via a clinically-oriented prism . Our integrated PK/PD model was constructed by an advanced “multiple-modeling” approach , which we found most suitable for the IL-21 scenario . The selection of a favorable model out of many analyzed structures and complexities , and the use of non-linear kinetics , enabled us to explore significantly more functional possibilities , and allowed for flexibility in the design . Moreover , rather than forming a model per scenario , we were able to create a generalized model by describing processes that are mutual to different therapeutic settings ( administration routes , etc . ) and tumor types . This enhanced the robustness of the model , since it structure was subject to testing under diverse conditions . Indeed , the model encompasses IL-21-induced outcomes in a wide range of treatment conditions , under different times and administration routes . Despite its simplicity , the model accurately predicted IL-21-relayed effects in B16- and RenCa-challenged mice , both prospectively and retrospectively . Moreover , the model demonstrated robust behavior , and predictions were largely insensitive to modulation of key parameters . With this combined generality and accuracy , the model can potentially accommodate other clinical settings and solid cancers where similar immune processes apply and where IL-21 has been useful ( i . e . adenocarcinoma , glioma , neuroblastoma ) [7] , [8] . A systematic design of clinically applicable IL-21 immunotherapy strategies has long been called for . Considering the modest responses of MM and RCC patients to IL-21 therapy [10] , [11] , [12] , [13] , [14] , it is worthwhile to examine whether the drug can be more powerful under different treatment approaches . Previous trial regimens of IL-21 were determined based on the US Food and Drug Administration guidelines for high-dose IL-2 therapy in MM patients [13] , as the two cytokines share homology and certain effector-inducing functions . Yet , recent findings demonstrate that IL-2 and IL-21 do not entirely align in their actions [17] , [51] , [52] , inferring that the optimal administration strategies ( administration routes , dose intensities , inter-dosing intervals , etc . ) likely vary between the two agents . Local IL-21 delivery or expression have been proposed , by us and others , to be potentially effective and safe approaches [17] , [39] , [53] , yet such therapeutic methods are not yet available for clinical use . Our systemic model analysis therefore represents a new effort to identify improved , clinically-appropriate IL-21 therapies , using the preclinical tumor models B16 and RenCa as case studies . Simulations of differently dosed IL-21 schedules gave rise to central new insights . According to the model , comparable antitumor responses are induced by daily IL-21 doses within the 5–50 µg range . This was prospectively confirmed in B16-challenged mice , in which a substantially lower IL-21 dose ( roughly 12 µg/day ) was as effective as the standard 50 µg/day treatment . An insensitive range of IL-21 doses with similar efficacy is not unreasonable , considering that the drug respectively inhibits or induces NKs and CTLs , two cells which complement one another in the process of cancer targeting . This model-aided identification of smaller doses with similar therapeutic efficacy could have immense clinical value , possibly reducing putative IL-21-associated toxicities . Adverse events have indeed been reported in IL-21-treated patients [10] , [11] , [12] , [13] , [14] . IL-2 and interferon-α , other cytokine drugs , are associated with severe hematological and neuropsychiatric side effects complicating their use [2] . Recent PK/PD models of toxic IL-21 effects on body temperature and red blood cell regulation [46] , [47] present a possible framework in which our improved regimens can be confirmed for clinical safety . Another interesting concept surfacing from our simulations addresses IL-21 fractionation . The model predicted improved antitumor responses by simple partitioning of the experimental regimen ( a single 50 µg dose/day ) into an equally intense regimen of 25 µg doses given twice daily . This was prospectively validated by experiments in which the fractionation-treated mice ended therapy with ca . half of the tumor load observed after the standard treatment . Model-predicted halving of a daily dose was sufficient to significantly enhance IL-21 efficacy , and further division of the doses was not imperative . Indeed , fractionation of cancer therapeutics was recommended in the past by mathematical modeling [29] , and its beneficial effects have been validated preclinically for a chemotherapy supportive drug [34] . This strategy has mostly been applied in the context of radiation therapy and chemotherapy [54] , yet our results , which clearly indicate the benefit of fractionated IL-21 dosing , propose its relevance also to immune-modulating drugs . Notwithstanding , fractionation may be impractical , reducing patient compliance and requiring hospitalization in certain cases . Moreover , embarking on new clinical studies to test fractionation therapy is a large and expensive task , and further adjustment of the mathematical model to humans is needed before engaging in such endeavors . Our findings also raise the question whether IL-21 ought to be administered by available “slow and continuous release” drug delivery methods , which can be viewed as regimens of maximal partitioning . Past cytokine-gene therapy experiments in mice showed complete eradication of IL-21-secreting tumors in which the drug was released in low continuous levels directly in the target tissue [7] , [9] , supporting the possible advantage of fractionated regimens . Future implementation of such routes of drug delivery within our model can allow to specifically analyze the benefit of such strategies for IL-21 therapy . Our present results set the stage for constructing a humanized IL-21 model , to serve as a tool for streamlining development of the drug , and in the future , hopefully , also for personalizing cytokine immunotherapy . The model , up-scaled to the clinical arena , can entertain diverse cancer indications , patient-specific characteristics , and different modes of therapy . Newly-discovered IL-21 properties of relevance to the anticancer response , such as modulation of T regulatory cell functions [17] and anti-angiogenic properties [18] , may be introduced in the evolving IL-21 model . Finally , considering the growing interest in combination therapies for solid cancers , and the promising preclinical and clinical responses observed when applying IL-21 with monoclonal antibodies or signaling inhibitors [9] , [50] , a future model will also study IL-21 therapy in combination with additional therapeutic reagents .
Among the many potential drugs explored within the scope of cancer immunotherapy are selected cytokines which possess promising immune-boosting properties . Yet , the natural involvement of these proteins in multiple , often contradicting biological processes can complicate their use in the clinic . The cytokine interleukin ( IL ) -21 is no exception: while its strength as an anticancer agent has been established in several animal studies , response rates in melanoma and renal cell carcinoma patients remain low . To help guide the design of effective IL-21 therapy , we have developed a mathematical model that bridges between the complex biology of IL-21 and its optimal clinical use . Our model integrates data from preclinical studies under diverse IL-21 treatment settings , and was validated by extensive experiments in tumor-bearing mice . Model simulations predicted that beneficial , clinically practical IL-21 therapy should be composed of low-dose schedules , and/or schedules in which several partial doses are administered rather than a single complete dose . These findings were subsequently confirmed in mice with melanoma . Thus , future testing of these strategies in solid cancer patients can be a promising starting point for improving IL-21 therapy . Our model can thus provide a computational platform for rationalizing IL-21 regimens and streamlining its clinical development .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[ "medicine", "immune", "physiology", "immune", "cells", "cytokines", "clinical", "research", "design", "immune", "activation", "animal", "models", "of", "disease", "immunology", "anatomy", "and", "physiology", "preclinical", "models", "adaptive", "immunity", "genetics", "and", "genomics", "immunoregulation", "immunomodulation", "immunotherapy", "t", "cells", "biology", "immune", "response", "immune", "system", "systems", "biology", "clinical", "immunology", "nk", "cells", "immunity", "physiology", "computational", "biology", "modeling" ]
2011
An Integrated Disease/Pharmacokinetic/Pharmacodynamic Model Suggests Improved Interleukin-21 Regimens Validated Prospectively for Mouse Solid Cancers
Leishmaniasis is one of the most important zoonotic diseases spread in Latin America . Since many species are involved in dog infection with different clinical manifestations , the development of specific diagnostic tests is mandatory for more accurate disease control and vaccine strategies . Seventy-five 15-mer peptides covering the sequence of recombinant Leishmania donovani virulence factor A2 ( recLdVFA2 ) protein were prepared by Spot synthesis . Membrane-bound peptides immunoreactivity with sera from dogs immunized with recLdVFA2 and with a specific anti-recLdVFA2 monoclonal antibody allowed mapping of continuous B-cell epitopes . Five epitopes corresponding to the N-terminal region of recLdVFA2 ( MKIRSVRPLVVLLVC , RSVRPLVVLLVCVAA , RPLVVLLVCVAAVLA , VVLLVCVAAVLALSA and LVCVAAVLALSASAE , region 1–28 ) and one located within the repetitive units ( PLSVGPQAVGLSVG , regions 67–81 and 122–135 ) were identified . A 34-mer recLdVFA2-derived bi-epitope containing the sequence MKIRSVRPLVVLLVC linked to PLSVGPQAVGLSVG by a Gly-Gly spacer was chemically synthesized in its soluble form . The synthetic bi-epitope was used as antigen to coat ELISA plates and assayed with dog sera for in vitro diagnosis of canine visceral leishmaniasis ( CVL ) . The assay proved to be highly sensitive ( 98% ) and specific ( 99% ) . Our work suggests that synthetic peptide-based ELISA strategy may be useful for the development of a sensitive and highly specific serodiagnosis for CVL or other parasitic diseases . Visceral leishmaniasis ( VL ) is an infection caused by various species of Leishmania , an intracellular protozoan parasite . Currently , VL is among the six endemic prioritized diseases in the world [1] . In humans , infection with Leishmania can cause a broad spectrum of symptoms ranging from a clinically silent infection to a fatal visceral disease [2] . In an urban environment , dogs are the main reservoir of the disease , but many stay asymptomatic , showing no clinical signs [3 , 4 , 5] . A2 is a stress response protein from L . donovani and it is expressed in amastigote and in promastigote cultures . It corresponds to the specific virulence factor ( LdVFA2 ) and has been shown to be required for L . donovani amastigote survival in visceral organs of mice [6 , 7 , 8] . A2 proteins are composed mostly of a variable number of 10-amino-acid repeats and their molecular weight varies from 45 to 100 kDa [9] . LdVFA2 antigens , administered as recombinant protein ( recLdVFA2 ) or DNA , are protective against L . donovani , L . amazonensis and L . chagasi infections in mice [10 , 11 , 12] , dogs [13] and macaques [14] . Anti- LdVFA2 antibodies have been detected in sera samples from human patients with active visceral leishmaniasis , confirming that LdVFA2 proteins are expressed during infection [10 , 15] . These findings suggest that studies of LdVFA2 proteins antigenic properties might have great potential for the development of vaccines , therapeutics and diagnostics for leishmaniasis . In this work , we report the mapping of B-cell continuous epitopes of recLdVFA2 , production by chemical synthesis of a recLdVFA2-derived synthetic epitope and its use as antigen for canine visceral leishmaniasis ( CVL ) diagnosis . Epitope mapping was achieved by peptide-scanning of the recLdVFA2 sequence using the Spot-synthesis technique [16] . This method is an easy and very flexible technique for simultaneous parallel peptides chemical synthesis on membrane supports . Furthermore , it allows a rapid and low-cost access to a large number of peptides for systematic epitope analysis [17] . Sixty-five overlapping peptides ( 15-mer frameshifted by 3 residues ) covering the complete amino acid sequence of recLdVFA2 were synthesized on cellulose membranes . Five continuous epitopes corresponding to the non-repetitive N-ter region of recLdVFA2 ( MKIRSVRPLVVLLVC , RSVRPLVVLLVCVAA , RPLVVLLVCVAAVLA , VVLLVCVAAVLALSA and LVCVAAVLALSASAE , region 1–28 ) were mapped using anti- recLdVFA2 dog sera and one epitope was located within the repetitive units ( PLSVGPQAVGLSVG , region 67–81 and 122–135 ) using an anti-recLdVFA2 mAb . An epitope from N-ter ( MKIRSVRPLVVLLVC ) and another from the C-ter part ( PLSVGPQAVGLSVG ) were selected and chemically assembled in tandem , to yield a soluble bi-epitope peptide . The bi-epitope used as coating antigen in ELISA accurately distinguish ( high sensitivity and specificity ) sera of CVL dogs from sera of non-infected dogs . Approval to use the sera samples was obtained from the Committee on Ethics of Animal Experimentation ( CETEA , national guidelines Lei 11 . 794 , de 8 de outubro de 2008 ) from this UFMG ( CETEA–protocol 44/2012 ) . L . infantum ( MHOM/BR/1975/BH46 ) was grown at 24°C in Schneider´s medium ( Sigma , St . Louis , MO , USA ) supplemented with 20% heat-inactivated fetal bovine serum ( FBS; Sigma ) , 200 U/mL penicillin and 100 μg/mL streptomycin , at pH 7 . 2 . Total soluble antigens of L . infantum ( LiA ) was prepared from stationary phase promastigotes , submitted to 7 cycles of freezing ( liquid nitrogen ) and thawing ( 42°C ) , followed by ultrasonication ( Ultrasonic processor , GEX600 ) , with cycles of 10 sec for 2 min at 35 MHz . Extracts were then submitted to centrifugation at 8000 × g for 20 min at 4°C . The supernatant was collected and stored at −70°C . recLdVFA2 , a recombinant form of A2 , was expressed and purified as previously described [15] . For epitope mapping , sera from seventy-three dogs immunized with recLdVFA2 were obtained from the laboratory HERTAPE-KALIER Health Animal S . A . For diagnostic test , serum of dogs from a CVL non-endemic area and giving negative results for L . infantum in immunofluorescence antibody test ( IFAT ) and confirmed by parasitological test and microscopic analysis of bone marrow aspirates were considered to be non-infected and used as the control group ( NI , n = 101 ) . Leishmania-infected dog sera ( I , n = 101 ) were obtained from an endemic area for CVL in the Minas Gerais State of Brazil . Infection status was determined by parasitological test , the positivity was confirmed by microscopic analysis of bone marrow aspirates . The positive and negative status was further confirmed by real time PCR . Samples from dogs experimentally infected with Trypanosoma cruzi ( TC , n = 10 ) , but parasitologically negative for Leishmania , were included in this study to evaluate possible cross-reactivity . All sera used for diagnostic test were obtained from sera bank already existing of Laboratory of Immunology and Genomics of Parasites , Federal University of Minas Gerais ( UFMG/BR ) . The anti- L . donovani virulence factor A2 murine monoclonal antibody ( mAb-anti recLdVFA2 ) was kindly provided by Dr . Greg Matlashewski , McGill University , Quebec , Canada . One hundred and one sera from infected dogs were used ( I ) , as well as 101 sera from dogs without a history of Leishmania infections ( NI ) and 10 sera from dogs experimentally infected by T . cruzi ( TC ) , to verify if the bi-epitope recLdVFA2 derived is a good candidate to be antigen in CVL diagnostic test . Maxisorb flexible microtitration plates were coated overnight at 5°C with 100 μL of synthetic peptide solution ( 10 μg/mL ) in 0 . 02 M sodium bicarbonate buffer , pH 9 . 6 . Assays were performed as previously described [22] . Sera were diluted 1:100 and absorbance values were determined at 492 nm with a Titertek Multiscan spectrophotometer . All measurements were made in triplicate . Standard EIE-LCV kit for the leishmaniasis diagnosis was used for comparison . This test is the most used in the clinical and serologic testing ELISA for LCV is a good test for use in the field epidemiological serum screening due to its convenience and low cost . All data comparisons were tested for significance by using unpaired Student’s t test or Kruskal–Walls test . Differences were considered statistically significant when P values were < 0 . 05 . The lower limit of positivity ( cut-off ) for bi-epitope and EIE-LCV was established for optimal sensitivity and specificity using the Receiver Operator Curve ( ROC curve ) . The cut-off was chosen based on the point that provides the maximum of the sum of the sensibility and specificity [23] . The performance of each test was evaluated according to the sensitivity ( Se ) , specificity ( Sp ) , positive predictive value ( PPV ) , negative predictive value ( NPV ) , area under the curve ( AUC ) and accuracy ( ACC ) . Statistical analyses were performed using GraphPad Prism ( version 5 . 0 ) and R package for Windows ( www . r-project . org ) ( version 3 . 1 . 0 ) . A 34-mer recVFA2-derived synthetic peptide containing the sequence MKIRSVRPLVVLLVC linked by a Gly-Gly to the sequence PLSVGPQAVGPLSVG was chemically synthesized . Two amino acids were added , a Lys to the N-ter and a Cys to the C-ter regions , respectively . This synthetic peptide ( bi-epitope ) was used as antigen to coat ELISA plates , for an immune diagnosis of CVL . ELISA parameters ( eg . antigen concentration , incubation times , serum dilution ) were previously defined . A ready to use commercial EIE-LVC kit was included for performance comparison ( Fig 3 ) . In the conditions previously defined , the bi-epitope showed better diagnostic performance ( AUC = 0 . 9987 , 95% CI 0 . 9967 to 1 . 001; ACC = 0 . 9851 ) when compared to EIE-LVC kit ( AUC = 0 . 9601 , 95% CI 0 . 9351 to 0 . 9850; ACC = 0 . 9001 ) ( Table 3 ) . recLdVFA2 showed sensitivity ( 98 . 02%; 95% CI 93 . 03 to 99 . 76% ) and specificity ( 99 . 01%; 95% CI 94 , 61 to 99 . 97% ) values for detection CVL higher than those obtained with EIE-LVC kit ( Se and Sp = 90 . 01%; 95% CI 82 . 54 to 95 . 15% ) . Bi-epitope ELISA was also able to discriminate Leishmania-infected animals from animals infected with T . cruzi , however EIE-LVC kit show cross-reactivity with T . cruzi-infected sera ( Fig 3A and 3B ) . LdVFA2 protein was identified as an important candidate for vaccine development against visceral leishmaniasis [11 , 13 , 25] . B-cell epitope in LdVFA2 was previously located within the repetitive units using sera from recLdVFA2-vaccinated mice and with the LdVFA2-specific monoclonal antibody [10] . A recent study has demonstrated that humoral response to recLdVFA2 in dogs is associated , presumably , with protective immunity against Leishmania spp . parasites [26] , however , B-cell epitope analysis with antibodies elicited in dogs were not conducted . Thus , researches for diagnosis or vaccines applied to dogs could be eventually improved by the identification of B-cell epitope mapping of LdVFA2 , using homologous antibodies . In this way , the present study , provided mapping of continuous B-cell epitopes , using sera from recLdVFA2 immunized dogs and a mouse monoclonal antibody ( anti-recLdVFA2 mAb ) , by performing a systematic 15 mer peptide-scan along the complete recLdVFA2 sequence . Anti-recLdVFA2 dog sera recognize peptides derived from the non-repetitive N-term region of recLdVFA2 . Immunoreactivity of peptides bound to membranes reveals five sequences containing epitopes close to this region ( peptides 1–15 , 4–18 , 7–21 , 10–24 and 13–27 ) . B-cell epitopes within the repetitive C-term region were not identified . On the other hand using an anti-LdVFA2 mAb , B-cell epitopes in recLdVFA2 were located solely within the repetitive units , which is consistent with a previous report [27] . The two most reactive peptides have two repetitions of the sequence PLSVG ( spots 23 and 48: region 67–81 and 122–135 ) . This sequence PLSVGPQAVGPLSVG is repeated four times in the complete sequence of the LdVFA2 protein . Spots 13 and 38 are also very reactive and have only one substitution in its sequence ( alanine for serine ) , when compared to the spots 23 e 48 . Thus , residues PLSVG- ( X ) 5 –PLSVG are key contributors to the antigenic recognition of the peptide by specific mAb . However , spots 27 and 75 have only one sequence PLSVG and are also very reactive . We do not have a clear explanation for this observation . A recLdVFA2 derived chimeric peptide based on mapped continuous B-cell epitopes MKIRSVRPLVVLLVC and PLSVGPQAVGPLSVG was synthesized and used in ELISA experiments for serum diagnosis of CVL . In fact , we prepared 34-mer recLdVFA2-derived peptides containing a sequence of 15 residues from one part of recLdVFA2 linked by a Gly-Gly dipeptide to a pentadeca sequence from another part of the protein , in order to bring together regions that are apart from each other in the linear sequence of the recombinant peptide . Glycine spacers’ separating the peptides increases their recognition by antibodies by providing a better exposition of chains for interaction [28] . N-ter and C-ter extremities were capped respectively by a Lysine and a Cysteine residue to allow further specific coupling to protein carriers ( not used in this work ) . The 34-mer bi-epitope peptide was used as coating antigen in an ELISA format . Accurate diagnosis of canine leishmaniasis is essential towards a more efficient control of this zoonosis , but is no yet achieved due to the high incidence of serological cross-reactions , mainly with other tripanosomatids antigens in canine serum samples [29] . The use of synthetic peptides [30 , 31] as antigens in diagnosis of canine leishmaniasis may limit cross reactivity . It would also circumvent reliance on parasite extracts , which are not easy to reproducibly produce , and thus may help assay standardization . In the present work , encouraging results were obtained using the synthetic bi-epitope as coating antigen . Bi-epitope ELISA diagnostic test showed better sensitivity and specificity than the EIE-LVC kit , which is considered the gold standard for CVL diagnosis and high degree of agreement with parasitological techniques for the leishmaniasis diagnosis . These results using peptides selected by a peptide scanning method showed a better performance than others studies with synthetic peptides for CVL immunodiagnosis tests [32 , 33 , 30 , 34] . In conclusion , data presented in the current study suggest that it is feasible to map B-cell epitopes from an overlapping peptide library covering the full length of recLdVFA2 and to further use the selected peptides in combination to diagnose canine visceral leishmaniasis . Further studies using sera of dogs from endemic areas ( with high and low CVL prevalence ) are obviously required to determine the use of these antigens for field control of CVL . Bi-epitope is derived from A2 protein and Leish-Tec vaccine is produced from this protein , so if it used in a diagnostic test of CVL , it may not be able to discriminate infected animals from those vaccinated . This antigen can be used in regions where this vaccine is not used and can also be combined with other antigenic epitopes that can minimize this fact . Finally , our work suggests that synthetic peptide-based ELISA strategy may be useful for the development of a sensitive and highly specific serodiagnosis for CVL or other parasitic diseases .
Leishmaniasis is a neglected tropical disease being among the six endemic prioritized diseases in the world . Visceral leishmaniasis ( VL ) is caused by Leishmania infantum and represents a serious public health problem in Brazil . Dogs are the main source of infection in the urban area and , in Brazil , the main strategies of the Visceral Leishmaniasis Control Program are directed to control the canine reservoir ( serological survey and euthanasia of dogs which present reactive serum ) . In general , diagnosis of canine visceral leishmaniasis ( CVL ) has been presented as a problem for Brazilian public health services . The issue should be attributed mainly to the following factors: 1- range of similar clinical signs observed in other infectious diseases that affect dogs; 2- large percentage of asymptomatic or oligosymptomatic dogs; 3- nonspecific histopathological changes; 4- nonexistence of a diagnostic test 100% specific and sensitive . In this work , we developed a synthetic bi-epitope peptide as an antigen for immunodiagnostic ELISA to detect CVL . The biepitope used for ELISA assay accurately distinguish ( 98% sensitivity and 99% specificity ) CVL dogs sera from non-infected dogs sera .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "blood", "cells", "medicine", "and", "health", "sciences", "enzyme-linked", "immunoassays", "immune", "physiology", "immune", "cells", "epitope", "mapping", "immunology", "tropical", "diseases", "vertebrates", "parasitic", "diseases", "dogs", "animals", "mammals", "neglected", "tropical", "diseases", "molecular", "biology", "techniques", "antibodies", "immunologic", "techniques", "chemical", "synthesis", "research", "and", "analysis", "methods", "peptide", "synthesis", "immune", "system", "proteins", "infectious", "diseases", "white", "blood", "cells", "zoonoses", "gene", "mapping", "animal", "cells", "proteins", "peptide", "mapping", "immunoassays", "proteomics", "protozoan", "infections", "molecular", "biology", "biosynthetic", "techniques", "biochemistry", "antibody-producing", "cells", "cell", "biology", "b", "cells", "physiology", "leishmaniasis", "biology", "and", "life", "sciences", "cellular", "types", "amniotes", "organisms" ]
2017
Epitope mapping of recombinant Leishmania donovani virulence factor A2 (recLdVFA2) and canine leishmaniasis diagnosis using a derived synthetic bi-epitope
In many low-income settings , despite improvements in sanitation and hygiene , groundwater sources used for drinking may be contaminated with enteric pathogens such as Cryptosporidium and Giardia , which remain important causes of childhood morbidity . In this study , we examined the contribution of diarrhea caused by Cryptosporidium and Giardia found in groundwater sources used for drinking to the total burden of diarrheal disease among children < 5 in rural India . We studied a population of 3 , 385 children < 5 years of age in 100 communities of Puri District , Odisha , India . We developed a coupled quantitative microbial risk assessment ( QMRA ) and susceptible-infected-recovered ( SIR ) population model based on observed levels of Cryptosporidium and Giardia in improved groundwater sources used for drinking and compared the QMRA-SIR estimates with independently measured all-cause ( i . e . , all fecal-oral enteric pathogens and exposure pathways ) child diarrhea prevalence rates observed in the study population during two monsoon seasons ( 2012 and 2013 ) . We used site specific and regional studies to inform assumptions about the human pathogenicity of the Cryptosporidium and Giardia species present in local groundwater . In all three human pathogenicity scenarios evaluated , the mean daily risk of Cryptosporidium or Giardia infection ( 0 . 06–1 . 53% ) , far exceeded the tolerable daily risk of infection from drinking water in the US ( < 0 . 0001% ) . Depending on which protozoa species were present , median estimates of daily child diarrhea prevalence due to either Cryptosporidium or Giardia infection from drinking water was as high as 6 . 5% or as low as < 1% and accounted for at least 2 . 9% and as much as 65 . 8% of the all-cause diarrhea disease burden measured in children < 5 during the study period . Cryptosporidium tended to account for a greater share of estimated waterborne protozoa infections causing diarrhea than did Giardia . Diarrhea prevalence estimates for waterborne Cryptosporidium infection appeared to be most sensitive to assumptions about the probability of infection from ingesting a single parasite ( i . e . the rate parameter in dose-response model ) , while Giardia infection was most sensitive to assumptions about the viability of parasites detected in groundwater samples . Protozoa in groundwater drinking sources in rural India , even at low concentrations , especially for Cryptosporidium , may account for a significant portion of child diarrhea morbidity in settings were tubewells are used for drinking water and should be more systematically monitored . Preventing diarrheal disease burdens in Puri District and similar settings will benefit from ensuring water is microbiologically safe for consumption and consistent and effective household water treatment is practiced . Untreated groundwater is the primary source of drinking water for nearly a quarter of the world’s population and in low-income settings groundwater tubewells are widely used for drinking [1] . Although tubewells have been classified as an improved source of drinking water , they are susceptible to fecal contamination [2] , making them a potential transmission pathway for diarrheal pathogens unless water is properly treated before ingestion . Globally , nearly 1 . 5 million deaths are estimated to occur each year from diarrheal diseases , with the majority of these deaths occurring in low-income settings and in children < 5 years old [3] . In low-income settings , however , fewer than half the population is reported to treat their drinking water at home to remove pathogens , and poorer households are the least likely to do so [4] . In rural India roughly 77% of people rely for drinking water on non-piped improved water sources ( e . g . tubewells ) [1] , which raises concerns about exposure to waterborne pathogens caused by fecal contamination . Etiology of childhood diarrhea is complex , but where surveillance occurs protozoal pathogens are recognized as important contributors to waterborne disease [5] . Cryptosporidium and Giardia are two fecal protozoal pathogens which cause diarrhea and both have zoonotic potential . The primary zoonotic species of Cryptosporidium and Giardia known to infect humans are Cryptosporidium parvum and Giardia lamblia ( syn . Giardia duodenalis and Giardia intestinalis ) assemblages A and B , respectively [6] . Additionally , Cryptosporidium hominis is a human-specific species [7] . These pathogens can be transmitted via contaminated drinking water as well as contaminated recreational or bathing water , food , soil , and hands , and are responsible for substantial disease burdens worldwide [8] . In developing countries Cryptosporidium and Giardia are frequently detected in stools of children in hospital- and community-based studies [9–11] . Additionally , Cryptosporidium is a leading cause of moderate to severe diarrhea in children < 2 years old in India [10] and both cryptosporidiosis and giardiasis have been associated with stunting , malnutrition , and wasting when diagnosed as a chronic disease [12–14] . When measured with methods able to detect relatively low concentrations , Cryptosporidium and Giardia have been frequently detected in water sources in India [15] , pointing to potentially large but unknown risks . Risk and simulation modeling are mathematical approaches used to estimate exposure risks and levels of disease burden attributed to environmental exposures , including infectious diseases . Quantitative microbial risk assessment ( QMRA ) is a method typically used to quantify risk of infection for target pathogens in drinking water and food [16] . Susceptible-infected-recovered ( SIR ) modeling is a population level simulation approach . In QMRA , the probability of an infection is modeled on an individual basis and determined by exposure conditions for a given exposure scenario , such as ingested volume of water and concentration of disease-causing pathogens in the ingested volume . With SIR models , an exposed individual is categorized as susceptible , infected , or recovered from an infection and their health status and exposure levels simulated over time . Rarely are data on both pathogen exposure and disease outcomes available in the same population at the same time to develop accurate models of exposure risks and compare model estimates to observed values . Most often modeling studies have information on disease burdens without pathogen exposure data [17 , 18] or exposure data without levels of disease [19 , 20] . This is a common weakness of many published modeling studies and results in an inability to compare modeling assumptions , risk results , or disease burden estimates to actual levels of disease . The objective of this study was to better understand the public health significance of Cryptosporidium and Giardia contamination detected in groundwater sources used for drinking in a low-income population in rural Puri District , Odisha , India . To do so , we estimated the infection risk and associated child diarrhea disease burden from drinking groundwater and compared estimates to independently measured child diarrhea prevalence rates observed in the same population over the same period when contamination was observed . Specifically , we had three research questions: 1 ) what is the daily protozoal infection risk for children drinking from contaminated tubewells , 2 ) what is the associated child diarrhea disease burden in the study population , and 3 ) how does the estimated child diarrhea disease burden attributable to protozoa in drinking water compare to actual levels of all-pathogen/all-pathway child diarrhea observed in the study population , or stated alternatively , how much child diarrhea morbidity could be explained by consumption of protozoa-contaminated drinking water . To address these research questions , the prevalence of diarrhea in children < 5 years old from ingestion of Cryptosporidium and/or Giardia in contaminated tubewell drinking water was estimated using a QMRA approach coupled with a SIR population model and child diarrhea prevalence estimates compared to measured rates during the monsoon season in 2012 and 2013 . The main inputs to the QMRA and SIR models were taken from previously published research in the study population as a part of a large sanitation intervention trial , including measured protozoal concentrations in tubewells [15] , caretaker-reported 7-day recall diarrhea period prevalence [21] , and site-specific population characteristics and data [22] . Sensitivity analysis was used to identify model inputs which were associated with the greatest uncertainty in the Cryptosporidium and Giardia attributable waterborne child diarrhea prevalence estimates . Study villages were part of a large-scale cluster randomized control trial ( the Odisha Sanitation Trial ) evaluating the health impacts of a Total Sanitation Campaign program in 2011 [21] . Baseline data indicate the majority of households ( 82% ) got their drinking water from tubewells , with 39% using deep public tubewells installed by local government and 43% using privately owned shallow tubewells installed by the private sector . Additional details of the study villages can be found elsewhere [22] . In the Sanitation Trial , a total of 3 , 835 children < 5 years old in 100 villages were enrolled in diarrhea surveillance monitoring in which caretakers reported 7-day recall period prevalence for child diarrhea measured once every three months on a rolling basis for a period of almost two years starting in 2012 . Reported diarrhea episodes may have been caused by any number of pathogens circulating in the population since stool samples were not collected for pathogen screening . To estimate the probability of a symptomatic case of cryptosporidiosis or giardiasis from drinking water in children < 5 years old , and to estimate prevalence of diarrhea over time in the study population of 3 , 835 children in study communities exposed to contaminated tubewell drinking water , we used a quantitative microbial risk assessment ( QMRA ) approach [23] ( Fig 1 ) coupled with a susceptible-infected-recovered ( SIR ) model ( Fig 2 ) . QMRA is composed of four main steps: ( 1 ) hazard identification , ( 2 ) dose-response , ( 3 ) exposure assessment , and ( 4 ) risk characterization . During hazard identification , information is gathered describing how a particular pathogen affects the population of interest . Typical information can include the population size and typical pathogen shedding rates from an infected host . During dose-response , a mathematical model is developed or selected to estimate the probability that an individual will become infected with a pathogen given a certain number of organisms ingested and characteristics of the pathogen . The goal of exposure assessment is to characterize the different processes that contribute to the number of organisms an individual is exposed to through an activity , such as volume of water intentionally ingested for hydration ( i . e . , daily drinking ) purposes . Risk characterization is the stage where information from the three previous steps is synthesized to estimate infection and/or illness risk for an individual or a population . In our QMRA , we used information about the hazard ( i . e . contaminated drinking water ) , the exposure ( i . e . amount drunk , amount treated , etc . ) , the target pathogen ( i . e . Cryptosporidium and Giardia ) and the host ( i . e . children < 5 ) , described by statistical distributions or point estimates , to estimate the probability that exposure resulted in ingestion of a target pathogen , and that the estimated amount ingested resulted in an infection for the host . To reflect the variability inherent in modeling disease transmission and infection from a drinking water source , given uncertain and variable concentrations of viable and infectious pathogens in the drinking water in space and time , we used Monte Carlo simulation to repeatedly and randomly sample the statistical distributions that characterize the amount of ingested target pathogen . All simulations were programmed and run using the R modeling environment [24] . The main parameters of the QMRA model , their values and distributions , and sources of data are summarized in Table 1 . Each QMRA modeling step is described in detail next . For children drinking protozoa-contaminated tubewell water in our study population , we estimated the risk of infection for an individual child over the course of a single day ( individual risk ) , accounting for boiling and other factors , and compared the expected risk for different households ( i . e . , deep vs . shallow tubewell users ) , years ( i . e . 2012–2013 ) and protozoa ( i . e . Cryptosporidium vs . Giardia ) , to the tolerable level of microbial risk from drinking water for a day ( 1 in 1 , 000 , 000 ) in the United States [57] . To estimate individual risk of infection for an average child from drinking tubewell water , under the local probability of water treatment via boiling , we produced risk plots for each pathogen and tubewell type and each year using the output from the QMRA model ( i . e . probability of infection from drinking tubewell water for one day , see Fig 1 ) . Plots for each scenario were generated from 10 , 000 Monte Carlo simulations of a single day of exposure to tubewell water for an individual . To estimate the waterborne child diarrhea disease burden in the study population attributable to Cryptosporidium and Giardia protozoal contamination of tubewell drinking water , we used an SIR model coupled with the QMRA model , above , to longitudinally track the daily infection status of each individual child in our study population over time ( Fig 2 ) , assigning each to a tubewell type ( TW ) and to boiling ( B ) before drinking as a function of the household fractions for each practice in the population ( see TW and B in Table 1 ) . SIR models track the daily infectious status of individuals in three states; susceptible to acquiring an infection when exposed ( S ) , infected from an exposure event ( I ) , and recovered from an infection event with some degree of immunity ( R ) . In our SIR model , S means a child is susceptible to infection from Cryptosporidium or Giardia , I means a child is infected from Cryptosporidium or Giardia and has developed diarrheic symptoms ( children who are infected , but do not develop diarrheic symptoms remain in their current state ) , and R is a child who has recovered from a diarrheic infection from Cryptosporidium or Giardia and is immune to infection for the moment . To align with the three-month monsoon period when tubewells were sampled in 2012 and 2013 , the SIR model was run on a daily time step for 98 days each year ( allowing for eight days of model warm-up to establish baseline distributions of SIR states ) , such that for a given day , each child was in one of the three states , with each child’s state being independent of other children . To determine if a susceptible child transitioned into the infected state on a given day , first the QMRA model was used to assign a probability of infection , P ( i ) , modeled as a Bernoulli variable ( 1 = infection , 0 = no infection ) , to each child . If P ( i ) = 1 , the probability that the infection resulted in a diarrheic symptom ( P ( s ) ) was modeled based on published studies of the diarrhea morbidity ratio for children diagnosed with Cryptosporidium [45 , 47] or Giardia [9 , 46] in developing countries . These included two large scale , multi-country , case-control studies designed to identify primary pathogens responsible for causing diarrhea in children in developing countries ( the GEMS and MAL-ED ) and two smaller scale regional studies conducted in settings with inadequate access to clean water and sanitation . Variability in the morbidity ratio across studies was modeled as a Bernoulli process with parameter p represented by a uniform distribution between of 0 . 28–0 . 68 and 0 . 49–0 . 59 for Cryptosporidium and Giardia respectively ( see P ( s ) in Table 1 ) . Our estimates did not account for co-infections of pathogens and assumed no other pathogen besides Cryptosporidium or Giardia were responsible for causing a diarrhea episode . Not all cases of symptomatic Cryptosporidium and Giardia infection persist for the same duration of time . To model this variability , we used a duration of illness parameter ( D ) ( see Table 1 ) fit from published sources . For Cryptosporidium , we identified four studies [48–51] of children with data on duration of illness ( i . e . active shedding of parasites ) that allowed fitting this data to a statistical distribution ( Fig D in Supporting Information ) . However , we were unable to find similar information for Giardia and therefore used previously published values [17] based on outbreak data to estimate duration of infection for Giardia . From these studies , the mean duration of cryptosporidiosis and giardiasis is 10 ( IQR 3–14 ) and 11 ( IQR 6–14 ) days respectively . Once the illness event ended a child was assumed to transition into the recovered state and be temporarily immune to reinfection for a duration of seven days post-infection [17] . Only children in the susceptible state could transition into the infected state and only if their infection resulted in diarrheic symptoms ( i . e . both P ( i ) and P ( s ) equal to 1 in the model ) ; susceptible children who were infected without symptoms ( P ( i ) = 1 but P ( s ) = 0 ) remained in the susceptible state , while children in the infected and recovered states were protected from infection in the model . The main parameters of the SIR model , their values and distributions , and sources of data are summarized in Table 1 . Using results from the SIR model , we estimated the diarrheal disease burden associated with drinking tubewell water during each monsoon season ( mid-June to mid-September 2012 and 2013 ) for the population of < 5 children in the Sanitation Trial ( population burden ) and compared modeling estimates to observed levels of child diarrhea measured in the Sanitation Trial over the same periods . All-cause child diarrhea prevalence in the Odisha Sanitation Trial was measured quarterly as the 7-day recall diarrhea period prevalence reported at a single quarterly surveillance visit for each child in the study population . Thus , to properly compare our QMRA-SIR modeled daily average prevalence over the monsoon period simulation ( mid-June to mid-September ) to the Trial’s observed 7-day recall period prevalence on a single day during each monsoon season , we sampled the simulated child population and their daily diarrhea prevalence time series over the 90-day monsoon period as they were sampled in the Trial’s surveillance . The tubewell contamination data used in the simulation modeling was collected over the same 3-month period in which each of the 3 , 385 enrolled Trial children were monitored for diarrhea once , on a random day , using caregiver self-report and recall . To account for caregiver recall bias when sampling the modeled results , we used a reduced symptom recall correction variable ( Re in Table 1 ) to derive each child’s 7-day diarrhea period prevalence status . As there was no study specific information on caregiver recall bias , we used results from a study in neighboring Bangladesh in which children < 5 were followed for three years on a weekly basis and accuracy of caregiver recall of diarrhea assessed [52] . In the Bangladesh study , recall varied between 12% and 52% three to six days after onset of diarrhea . Therefore , we modeled recall as a Bernoulli process , in which recall was 100% on the first two recall days ( i . e . p = 1 ) , and between 12% and 52% for each day of the remaining five recall days ( i . e . p was a random uniform variable with values between 0 . 12 and 0 . 52 ) . To account for surveillance visits occurring on a random day , a total of 1 , 000 data sampling simulations were run for each year . Further details are provided in Appendix C in Supporting Information . To estimate how sensitive the model estimated 7-day recall predicted child diarrhea prevalence was to assumptions in the QMRA and SIR models , we ran a global sensitivity analysis with parameters considered in the HUM scenario . Specifically , we employed a density based approach previously described [58] . Briefly , the sensitivity analysis used the cumulative distribution function ( CDF ) of the QMRA-SIR model output as the primary input and compared an unconditional CDF to a conditional CDF for a given parameter . The unconditional CDF was approximated by evaluating the output of the QMRA-SIR models over the entire parameter space by varying all inputs simultaneously ( i . e . output is not conditional on a particular parameter value ) . The conditional CDF was approximated by holding the parameter of interest constant while varying all other parameters ( i . e . output is conditional on the fixed parameter value ) . Using the Kolmogorov-Smirnov two-sample statistic , a sensitivity index was calculated ranging from 0–1 , where an index closer to one indicated the QMRA-SIR model output was more sensitive to that parameter ( i . e . the conditional CDF diverged further from the unconditional CDF ) . To set the bounds of parameter space in the sensitivity analysis , minimum and maximum values were used for QMRA-SIR parameters represented by a distribution of values , while model sensitivity to parameters represented deterministically ( i . e . with a single value as with immunity of seven days ) was assessed by halving and doubling the parameter value . Uncertainty around the sensitivity index was assessed with bootstrapping [58] . Separate sensitivity analyses were conducted for Cryptosporidium and Giardia for each sample year ( 2012 and 2013 ) and each tubewell type ( DTW and STW ) , resulting in eight sensitivity analyses . To summarize the overall effect for each parasite , we averaged the upper , median , and lower sensitivity indices from the bootstrapping analysis for each parasite across years and tubewell types . Boxplots of daily risk are shown in Fig 3 in log10 scale and reveal the mean risk of waterborne protozoal infection per day , accounting for boiling rates , varied between 0 . 06% and 1 . 5% ( between about 1/1000 and 15/1000 children infected daily ) ( see Fig F for risk profiles in S1 Supporting Information ) . Comparing deep and shallow groundwater sources , years , pathogens , and human pathogenicity scenarios ( HUM , ENV , MST ) , ingesting Cryptosporidium from deep tubewells in 2012 carried the highest level of daily infection risk ( 1 . 5% , 0 . 7% , 1 . 2% under the HUM , ENV , and MST scenarios , respectively ) . The lowest estimated levels of risk were from ingesting Giardia in deep and shallow tubewells during 2013 under the ENV scenario ( 0 . 063% ) . A Kolmogorov-Smirnov two-sample test for risk profiles shown in Fig F in Supporting Information indicated a trend that the HUM scenarios were significantly different from the ENV scenario for a given year , tubewell type , and pathogen ( see Tables F & G for Kolmogorov-Smirnov two-sample test statistics in S1 Supporting Information ) Estimated child diarrhea daily point prevalence is shown in Fig 4 and reveals a wide range of prevalence , from a median as high as 6 . 5% to as low as < 1% at the population level considering estimated levels of water treatment by boiling . Across all tubewell types and years , assuming all parasites were shed from humans ( HUM ) increased diarrhea prevalence estimates by two-fold or more , compared to using fractions based on environmental parasite loading estimates ( ENV ) for Puri District ( see Table H in S1 Supporting Information ) . Comparing years , 2012 had a much higher estimated prevalence of diarrhea compared to 2013 under all scenarios . In 2012 , deep tubewell users were estimated to have higher diarrhea prevalence than shallow tubewell users , with Cryptosporidium often causing more symptomatic infections than Giardia across human pathogenicity scenarios . In 2013 , deep and shallow tubewell users were estimated to have similar diarrhea prevalence , with considerably more symptomatic Cryptosporidium than Giardia infections . The simulated 7-day recall diarrhea period prevalence from waterborne infections are compared to the all-cause observed levels reported in the Odisha Sanitation Trial during the monsoon season ( ~12% in 2012 and ~ 9% in 2013 ) [21] in Table 4 . The fraction of the observed all-cause diarrhea during each monsoon season that can be explained by the estimated tubewell drinking water protozoa infections under each human pathogenicity scenario ( HUM , MST , ENV ) is presented . The results indicate that as much as 65 . 8% or as little as 2 . 9% of the all-cause diarrhea burden in < 5 children can be attributed to waterborne infections from Cryptosporidium and Giardia in tubewell water . Depending on the scenario examined ( HUM , MST , ENV ) , we see a wide range of estimated attributable fractions , but a clear trend that a far greater fraction of diarrhea can be attributed to Cryptosporidium and Giardia contamination in drinking water during the monsoon season in 2012 , when child diarrhea prevalence rates were higher ( ~12% 7-day recall period ) compared to 2013 ( ~9% 7-day recall period ) . See Table I in S1 Supporting Information for further details . Results from the sensitivity analysis for the HUM scenario combined by sample year and tubewell type are shown in Fig 5 . Of the parameters examined , Cryptosporidium 7-day recall diarrhea period prevalence estimates were most sensitive to the rate parameter used in the dose-response model , the fraction of detected parasites assumed to be viable , and the method recovery of parasites from tubewell samples . For Giardia , diarrhea estimates were most sensitive to model parameters representing viability , method recovery , and the concentration of Giardia observed in tubewell samples . For both parasites , diarrhea estimates were least sensitive to the volume of water ingested , the fraction of the population that treated water by boiling , the morbidity ratio , and recall bias as these parameters had sensitivity indices generally below 0 . 2 . We coupled QMRA and SIR models to estimate waterborne infection risk and child diarrhea disease burdens attributable to observed Cryptosporidium and Giardia contamination of tubewell drinking water sources in rural Puri District , Odisha , India and compared model estimated levels to all-cause ( all pathogens and pathways ) child diarrhea rates measured in the study population . Daily child diarrhea prevalence attributed to infection from Cryptosporidium and/or Giardia in drinking water was estimated to be between 6 . 5% and < 1% , depending upon year , tubewell type , and fraction of parasites assumed to be infectious-to-humans . Model-based estimated levels of child diarrhea due to protozoal infections from drinking contaminated tubewell water accounted for as much as 65 . 8% of the Odisha Sanitation Trial all-cause child diarrhea disease burden measured in the study population ( 12% and 9% 7-day recall period prevalence , respectively , in 2012 and 2013 monsoon season ) . While the human pathogenicity scenarios tested in this study demonstrated there was considerable uncertainly around the attributable fraction of observed diarrhea in the Trial from drinking water contaminated with Cryptosporidium and Giardia , it is likely that the portion of parasites infectious-to-humans lies between the HUM and MST scenarios . Our research shows the usefulness of coupling QMRA-SIR models with field data to estimate the contribution of different pathogens and transmission pathways to diarrheal disease burdens and health impacts associated with targeted water , sanitation , and hygiene interventions . Our QMRA estimates are the first to estimate waterborne Cryptosporidium and Giardia infection risk from drinking tubewell water in India and show the microbiological quality of water investigated in this study is unsafe for drinking . Across tubewell types , years , and scenarios , the lowest daily estimated additive risk for Cryptosporidium and Giardia , occurring under the ENV scenario for shallow tubewells in 2013 ( 0 . 3% or 3 new infections in 1 , 000 children per day ) , exceeded the acceptable limits for annual infection risk from daily exposure via drinking water set by the US EPA ( 0 . 01% or 1 in 10 , 000 people ) [59] . By comparison , the estimated mean daily risk of infection from Cryptosporidium or Giardia in this analysis ( 0 . 06% - 1 . 5% ) is within the drinking water daily infection risk range reported for Cryptosporidium and Giardia in groundwater wells in Mexico ( 0 . 5–8 . 4% and 1 . 9–17% respectively ) [19] , but below the infection risk reported for Giardia in tubewell water used for drinking in Nepal ( 17% ) [60] , and for Giardia in children in Brazil drinking from tubewells ( 9 . 1–29% ) [20] . Nevertheless , a mean daily risk as high as 1 . 5% and as low as 0 . 06% represents a significant public health threat for children < 5 years old using tubewells with similar levels of protozoal contamination for drinking without proper disinfection or treatment prior to consumption . Aside from the expectation that risk differs geographically , temporally , and between age groups , comparison of estimated risks between QMRA studies is problematic due to different model assumptions and sources of data . However , our QMRA model included important assumptions , such as adjusting for the viability of parasites and accounting for the fraction protozoa species infectious-to-humans , not typically included in QMRA models of Cryptosporidium or Giardia . We estimated that of the observed child diarrheal disease burden in the Odisha Sanitation Trial study population , somewhere between 65 . 8% and 31 . 5% in 2012 , and between 13 . 9% and 4 . 7% in 2013 , was caused by Cryptosporidium and Giardia contaminated drinking water , based on the HUM and MST scenarios ( Table 4 ) . While the ENV scenario suggested much less and as little as 2 . 9% , this scenario is unlikely as additional research in the study region found a strong relationship between the level of Cryptosporidium and Giardia contamination in tubewells and spatial proximity to household latrines , indicating a greater likelihood that parasites originated from humans [61] . Assuming these ranges are correct , we could expect consistent and effective household water treatment ( HWT ) [62] to reduce diarrheal burdens by up to these fractions and likely more as other waterborne child diarrheal pathogens , including pathogenic Escherichia coli , rotavirus , adenovirus , and Vibrio cholera were also detected in the tubewell drinking water source samples in the Sanitation Trial [55] in addition to Cryptosporidium and Giardia . Previous work evaluating the effect of HWT on diarrhea prevalence has had mixed results , with some studies finding as much as 40% reduction in diarrhea and others finding no effect [63 , 64] . A randomized control trial evaluating the effectiveness of chlorine for HWT in Puri District recently reported diarrhea prevalence in children < 5 years dropped by roughly 30% ( 1 . 23 vs . 1 . 78% ) in households verified to use chlorination compared to those who did not [65] , further indicating waterborne transmission of diarrheal disease is an important pathway in Puri District . Therefore , until tubewells in Puri District and similar low-income settings can be assured to be microbiologically safe , consistent and effective HWT ( chlorination may not destroy all Cryptosporidium and Giardia parasites under typical concentrations and exposure times ) may play an important role in reducing child diarrhea . Both our model-based estimate of diarrheal disease and the observed levels of all-cause diarrhea in the Trial were higher during the 2012 monsoon season compared to 2013 . For our model-based estimates , the differences between years is purely a function of the difference in observed concentration , with 2012 having higher concentration of parasites compared to 2013 , as all other parameter distributions/values in the model were consistent across years . Previous analysis of observed levels of all-cause diarrhea in the Trial also attributed differences in diarrhea prevalence between years to levels of tubewell contamination , but also noted a rainfall effect and found an association between lower all-cause diarrhea in 2013 and increased rainfall in one region of the Trial [55] . As mechanisms at work to distribute pathogens in the environment and result in exposure for a host across different years are likely site specific and interacting , a surveillance program would ultimately be needed to gather data and better characterize how changing environmental and host-pathogen demographics interact with each other over annual and other time scales . Our study has shown that the fraction of parasites in drinking water that are from humans vs . non-human animal hosts and that are species infectious-to-humans have important implications for infection risk and diarrhea disease burden estimates . Determining whether Cryptosporidium and Giardia detected in water samples are infectious-to-humans , however , is difficult . Molecular characterization , such as PCR , may only amplify one species in a sample of mixed species [66] , while visual identification at the species levels is not considered valid [67] . To navigate these limitations , it has been suggested that studies of zoonotic diarrheal pathogens might use additional information of the environmental pathways that contaminate tubewell water , such as hydraulic connections from surface to groundwater , combined with information on the spatial distribution of human and animal feces around tubewells to help clarify the relative likelihood of human vs . non-human water contamination [61] . Another limitation of our study , specific to the MST and ENV scenarios examining prevalence of zoonotic Cryptosporidium and Giardia in livestock and domestic animals , was a lack of region specific data . Using studies from India , when available , combined with data from literature reviews to estimate the zoonotic fraction term in our QMRA-SIR models may not have adequately represented the cultural , geographic , and socioeconomic factors that relate to levels of zoonotic parasites in Puri District . However , as numerous factors interact to produce levels of zoonotic pathogens in a population , and as these factors may be spatially and temporally dynamic , a regional surveillance program would ultimately be needed to estimate the fraction of livestock and domestic animals shedding zoonotic parasites . In the meantime , using a range of values , preferably generated from local data sources , for human vs . non-human parasites is recommended to realize upper and lower limits of risk . While we had site-specific pathogen concentrations in source water and method recovery data for our QMRA modeling , we lacked specific information on the viability of the detected Cryptosporidium and Giardia parasites . Currently , common methods used to detect Cryptosporidium and Giardia in water do not assess if parasites are able to cause infection [68] , and doing so requires additional time , expense , and expertise [67] . Those studies that have investigated viability of parasites in water tend to use viable dye assays or morphology [26 , 69] , but little information is available for field studies using animal infectivity or culture-based assays ( a gold standard ) [67] , with no data from low-income settings found in our searches . Our assumption taken from a study in North America that infectivity was typically less than 50% for Cryptosporidium and less than 25% for Giardia reduced our risk estimates by more than half and may have biased our estimates of risk downwards and not fully represented the processes occurring in our study region that increase or inhibit parasite viability . Results from the sensitivity analysis indicate that assumptions about viability are an important factor contributing to variability in our QMRA-SIR model estimates of diarrhea ( especially for Giardia ) . Additional information on the viability of parasites detected in drinking water , especially in low-income settings , would help to improve the understanding of risks associated with drinking water contaminated with Cryptosporidium and Giardia . The novelty of our research was to couple QMRA estimates of waterborne pathogen infection risk with SIR modeling to estimate the contribution of waterborne infections to childhood diarrhea disease burdens in a low-income setting . Often diarrheal disease risk is shared among multiple transmission pathways , each requiring a different intervention strategy , and among multiple pathogens , often requiring further design considerations for a given WASH intervention . Additionally , the magnitude of impacts on health for a given intervention is likely to differ across settings depending on the major transmission pathways and pathogens of concern in each setting . The modeling methods developed here provide a new approach to assist in more effective selection and targeting of interventions to maximize health impacts on diarrheal disease at the local level . However , using model results without field observations makes the approach less useful . Having data on exposure ( drinking water quality ) and outcomes ( child diarrhea rates ) for the same population over the same time period , allowed us to both construct the QMRA-SIR modeling and compare the results against observed outcomes . More field , monitoring , and evaluation studies for diarrheal disease should aim to do this . While waterborne transmission is clearly a contributor of diarrheal disease burdens and while outbreak data suggest Cryptosporidium and Giardia are important etiological agents of waterborne disease worldwide [5] , there are other important diarrheal transmission pathways and pathogens to consider . In our setting , analyses of water samples from Puri District during 2012 and 2013 detected four other diarrheal pathogens ( pathogenic Escherichia coli , rotavirus , adenovirus , and Vibrio cholera ) in these same tubewells at similar detection rates to Cryptosporidium and Giardia [55] . Additionally , improved sanitation and hygiene is also lacking in Puri District and animal contact is frequent . These conditions make transmission from direct contact with human and non-human feces a likely additional cause of diarrhea . While we demonstrated that tubewells contaminated with Cryptosporidium and Giardia had a high potential of being a source of diarrhea in Puri District , coupling waterborne , foodborne , handborne , and other disease transmission models that incorporate environmental pathogen transport processes , such as transport mediated by rainfall , and consider multiple pathogens would be an important step to more fully understand diarrheal disease etiology , pathways of transmission , and risk factors in low-income settings . Additionally , the use of sensitive diagnostic methods able to detect the relativity low , but public health relevant concentrations of Cryptosporidium and Giardia used in this study should be a goal for water quality research programs going forward to better characterize the risks associated with drinking water contamination . In the meantime , diarrheal disease burdens in Puri District and other similar settings may persist despite improvements in sanitation and hygiene , unless drinking water is made safe and reliable at the source or through effective household water treatment .
Water , sanitation , and hygiene ( WASH ) interventions aimed at reducing exposure to enteric pathogens have produced mixed health impacts , with some interventions finding no significant difference in health outcomes between intervention and control groups . While there are many explanations why individual WASH interventions may not achieve improved health outcomes , one reason is an incomplete understanding of the conditions that favor perpetuation and transmission of enteric pathogens in a given population and region . In this study , we developed a set of diarrhea-causing disease transmission models using measurements of drinking water contamination and child diarrhea over the same time period in the same study population . Using the disease transmission models , we examined how much of the observed diarrhea in children was due to waterborne transmission of enteric pathogens in a program in rural India that improved household sanitation but failed to produce improvements in child health . We focused on the role of two enteric protozoal pathogens , Cryptosporidium and Giardia , and diarrhea rates among children < 5 years of age in these communities . We found that Cryptosporidium and Giardia infections from drinking water contaminated with these enteric protozoa may have together caused as much as 65 . 8% ( IQR 63 . 4–68 . 2% ) or as little as 2 . 9% ( IQR 2 . 3–3 . 4% ) of the observed diarrhea in children depending on modeling assumptions about which protozoa species were present . These findings suggest implementing a single barrier , such as only sanitation , to disrupt the multiple pathways of fecal-oral transmission of enteric pathogens , rather than multiple barriers , such as sanitation and safe drinking water , may lead some interventions to fall short of achieving measurable health improvements . Finally , our research suggests that Cryptosporidium and Giardia may cause significant amounts of child diarrhea morbidity even at low levels of concentration when present in improved drinking water sources and their measurement should be including in community drinking water quality monitoring programs .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "medicine", "and", "health", "sciences", "ecology", "and", "environmental", "sciences", "water", "resources", "pathology", "and", "laboratory", "medicine", "giardia", "pathogens", "cryptosporidium", "parasitic", "diseases", "parasitic", "protozoans", "diarrhea", "protozoans", "signs", "and", "symptoms", "gastroenterology", "and", "hepatology", "public", "and", "occupational", "health", "natural", "resources", "protozoan", "infections", "eukaryota", "diagnostic", "medicine", "biology", "and", "life", "sciences", "organisms" ]
2018
Estimating Cryptosporidium and Giardia disease burdens for children drinking untreated groundwater in a rural population in India
Triclabendazole is reported to be highly effective in treatment of human fascioliasis . We present 7 of 19 selected cases of human fascioliasis referred to our center in the Cusco region of Peru that failed to respond to triclabendazole . These were mostly symptomatic adults of both sexes that continued passing Fasciola eggs in the stool despite multiple treatments with 2 doses of triclabendazole at 10 mg/kg per dose . We documented the presence of eggs by rapid sedimentation and Kato Katz tests after each treatment course . We found that repeated triclabendazole courses were not effective against fascioliasis in this group of people . These findings suggest that resistance to triclabendazole may be an emerging problem in the Andes . Fascioliasis is a worldwide zoonotic infection caused by the trematode parasite Fasciola hepatica . Livestock infection causes large economic losses in developed and developing countries . [1] Even in some wealthy countries , up to 50% of the dairy and meat herds may be infected; but data from resource-poor countries are limited . [2–4] Heavily infected cattle have significantly decreased milk ( ≥ 1 . 5 L daily ) and meat ( ≥ 3 kg ) production . [5 , 6] Human infection has been reported in more than 70 countries , but the highest burden occurs in the Andes and parts of the Middle East . [7] School-age children have the highest prevalence of fascioliasis and bear most of its severe consequences . Lopez et al . described a threefold increase in anemia risk among children with fascioliasis compared with children without infection . [8] Significant weight loss during the acute and chronic infections has been described in other studies . [9 , 10] Thus , the long term effects of fascioliasis complications have motivated significant efforts to tackle livestock and human infection . Triclabendazole is the most effective drug for fascioliasis based on safety and cure rates reported in small mostly uncontrolled studies . [11] Mass treatment with triclabendazole has been proposed as a strategy to control fascioliasis in livestock and humans . In developed countries cattle and sheep herds are treated with triclabendazole under professional supervision . However , in resource-poor countries , mass livestock treatment is often inconsistent . [12] Mass treatment and inconsistent dosing of triclabendazole may select resistant parasites . [13] The emergence of triclabendazole resistance has been described among sheep and cattle herds in Scotland , Northern Ireland , and Australia and has been associated with decreased beef and dairy production . [12 , 14] Increasing resistance has also been reported in Cajamarca , Peru , where only 31% of cattle treated with 12 mg/kg of triclabendazole were cured after 14 days . [15] Triclabendazole resistance in humans has only rarely been noted . [16 , 17] Reports of resistance are of concern given that triclabendazole is the only highly effective treatment available . In this report , we describe 7 patients with fascioliasis with persistent infection despite multiple treatment courses with triclabendazole . Between January 2014 and April 2015 , 7 out of 19 patients with Fasciola hepatica infection referred to our center for evaluation and treatment failed to respond to multiple courses of triclabendazole ( Egaten 250 mg tablets , Novartis Pharma AG , Basel , Switzerland , expiration date December 2015 ) 2 doses at 10 mg/d every 12 h with a fatty meal . Three of these were males , 2 were younger than 18 years old , and all but one were born in Cusco City . Four patients had acute presentations with delayed diagnosis , severe symptoms requiring prolonged hospital admissions for hypereosinophilia . All patients had a history of eating fresh watercress and other green leafy vegetables and self-medicated at least once with triclabendazole for veterinary use without response . In an attempt to improve their clinical response , all were prescribed triclabendazole and nitazoxanide ( Colufase , Roemmers SA , Lima , Peru ) 500mg PO every 12 hours for 7 days in combination after failing courses of treatment with triclabendazole monotherapy . Only one patient had consecutive negative stool tests and was deemed cured . The characteristics of the patients are shown in Table 1 . The cases and their clinical course are briefly described below . Fig 1 shows the egg counts 1 to 3 months after each treatment course with triclabendazole . Case 1 was a 51 years old female farmer with 16 kg weight loss , right upper quadrant abdominal pain , night sweats , anorexia , malaise , fever , and hypereosinophilia . She was first treated with a single dose of 10 mg/kg triclabendazole with improvement of symptoms . However , after 8 months her symptoms returned and she was again noted to be shedding Fasciola eggs . The patient was treated 2 additional times with triclabendazole ( each with 2 doses of 10 mg/kg every 12 hours ) and then with 2 doses of triclabendazole 10 mg/kg every 12 hours followed by nitaxozanide 500 mg every 12 hours for 7 days with improvement of symptoms . However , continued to pass Fasciola eggs on stool tests . Case 2 was a 36 years old female with right upper quadrant abdominal pain , jaundice , severe joint pain , fatigue , 8 kg weight loss , and hypereosinophilia . Her stool tests and Fas-2 ELISA were positive for Fasciola . After failing a treatment course with triclabendazole ( 2 doses of 10 mg/kg every 12 hours ) , she was referred to our center . Over 10 months she received 1 additional course of triclabendazole treatment ( 2 doses of 10 mg/kg every 12 hours ) , a course of 3 doses of triclabendazole 10 mg/kg every 12 hours , and a course of 2 doses of triclabendazole 10 mg/kg every 12 hours followed by nitazoxanide ( 500 mg every 12 hours for 7 days ) with marked improvement of symptoms but persistence of Fasciola eggs in the stools . Case 3 was a 43 years old female who was asymptomatic . She was tested for Fasciola hepatica ova after her husband ( case 4 ) was diagnosed with the infection . Both Fas2 ELISA and stool tests were positive for Fasciola infection . She failed a course of triclabendazole ( 2 doses of 10 mg/kg every 12 hours ) and was prescribed 2 doses of triclabendazole 10 mg/kg every 12 hours followed by nitaxozanide 500 mg every 12 hours for 7 days after which she developed intrahepatic bile obstruction with removal of 3 adult Fasciola by endoscopic retrograde cholangiopancreatography . Also a migratory subcutaneous nodule due to Fasciola developed despite self-medication with a veterinary formulation of triclabendazole in 2 occasions . She was prescribed triclabendazole ( 2 doses of 10 mg/kg every 12 hours ) with negative stool tests for Fasciola at 5–6 weeks follow up . Case 4 is a 42 years old male born in the jungle of Cusco state married with case 3 . He was admitted to the hospital with fever , diffuse abdominal pain , cough , severe fatigue , 5 kg weight loss , rash in the lower extremities and buttocks , and hypereosinophilia ( eosinophil count > 30 , 000/dL ) . Lumbreras rapid sedimentation and Fas2 ELISA tests were positive for Fasciola hepatica infection . A few days after receiving triclabendazole treatment ( 2 doses of 10 mg/kg every 12 hours ) his symptoms disappeared , but continue passing Fasciola ova . He was prescribed 2 additional treatment courses with triclabendazole ( 2 doses of 10 mg/kg every 12 hours ) followed by a course of 2 doses of triclabendazole 10 mg/kg every 12 hours combined with nitaxozanide 500 mg every 12 hours for 7 days and 2 courses of triclabendazole veterinary formulation turning his Kato Katz tests negative . However , the Lumbreras rapid sedimentation test has remained positive . Case 5 was a 15 years old male who presented with epigastric pain , fever , shortness of breath , chest pain , 5 kg weight loss , hypereosinophilia , ascites , and pleural effusion . The stool tests for Fasciola were initially negative , but the Fas2 ELISA was positive . He was treated with a single dose of veterinary formulation triclabendazole with partial improvement of symptoms . His follow up stool tests were positive and remained positive since then despite 3 courses of triclabendazole ( 2 doses of 10 mg/kg every 12 hours each ) , and a course of 2 doses of triclabendazole 10 mg/kg every 12 hours in combination with nitaxozanide 500 mg every 12 hours for 7 days . Case 6 was a 12 years old male brother of case 5 diagnosed with asymptomatic F . hepatica infection . He failed the initial treatment with a single dose of triclabendazole . He was prescribed and failed 2 additional triclabendazole courses ( 2 doses of 10 mg/kg every 12 hours ) . He was subsequently treated with 2 doses of triclabendazole 10 mg/kg every 12 hours followed by nitaxozanide 500 mg every 12 hours for 7 days but his stool tests have remained positive for Fasciola eggs . Case 7 was a 36 years old woman mother of case 5 diagnosed with chronic F . hepatica infection . She received 3 courses of triclabendazole ( 2 doses of 10 mg/kg every 12 hours ) followed by a course of 2 doses of triclabendazole 10 mg/kg every 12 hours combined with nitaxozanide 500 mg every 12 hours for 7 days with persistently positive stool tests . The study was reviewed by the Institutional Ethics Committee from Universidad Peruana Cayetano Heredia in Lima , Peru . Written informed consent was obtained from the subjects . Although triclabendazole resistance in veterinary medicine is well known , resistant human infections have only rarely been reported . In this manuscript , we report 7 cases of Fasciola hepatica infection that failed to respond to multiple treatment courses with recommended doses of triclabendazole . Two other case reports of failure of triclabendazole treatment for fascioliasis have been published . In 2012 , Winkelhagen et al . from the Netherlands reported a single case of multiple treatment failures with triclabendazole and nitazoxanide . [16] In 2014 , Gil et al . reported 4 cases of triclabendazole failure in Chile . [17] However , in 3 of those cases the timeline between symptoms , treatment , and evaluation of response suggest reinfection rather than treatment failures . Of note , none of the reported cases had quantitative tests to evaluate the response of egg burden to treatment . Most of our patients had low egg burdens and the egg counts did not showed significant reductions after treatment . The microscopic detection of Fasciola eggs in human stool after the ingestion of metacercaria takes approximately 12 weeks . Our cases were followed up and tested for cure between 1 and 3 months after treatment with triclabendazole . This approach to monitoring was chosen to distinguish the treatment response from reinfection . Failure of anthelmintic treatment may be due to a number of factors . Quality control of the medications is essential . In these cases , all treatment failures received Egaten 250 mg tablets ( Novartis Pharma AG , Basel , Switzerland ) stored according to the manufacturer recommendations with an expiration date in December 2015 ( well after treatment ) . Treatment failure may also result from inadequate drug absorption . Food has significant effects on the absorption of triclabendazole . It is recommended that patients with fascioliasis ingest a fatty meal before each triclabendazole dose to increase medication absorption in the intestine , as was done in all of our cases . The impact in cure rates of not following this recommendation has not been studied . However , uncontrolled clinical trials with single dose triclabendazole report efficacies around 90% despite absence of fat ingestion before treatment . [11] Reduced triclabendazole conversion to triclabendazole sulfoxide and triclabendazole sulfone in the presence of severe liver impairment have been proposed as a cause of treatment failure . [20] All our cases had relatively low Fasciola egg counts suggesting mild infections and probably minimal liver damage . Of note , most of our patients presented with symptoms of acute Fasciola infection . Whether this was associated with the initial treatment failure cannot be ascertained . In early stages of infection with Schistosoma sp . the parasite has reduced susceptibility to praziquantel as demonstrated in vitro and in vivo . [20 , 21] Some in vitro studies with Fasciola hepatica infection suggest reduced triclabendazole susceptibility among juvenile parasites compared to adults . [22] This has not been rigorously documented in case series of patients with acute infections . [23 , 24] Marcos et al . reported the resolution of eosinophilia after a single dose of triclabendazole in 10 patients with acute Fasciola infection . However , the authors failed to report the absence of eggs in the stools during the follow up . [25] Thus , the clinical evidence gathered suggests the presence of triclabendazole resistant Fasciola hepatica infection in our cases . The mechanisms by which the fluke can become resistant to triclabendazole remain to be elucidated . The β-tubulin gene mutations that cause benzimidazole resistance in nematode parasites does not seem to explain triclabendazole resistance in Fasciola hepatica . [26] Changes in drug uptake and parasite drug metabolism seem to play a bigger role . The uptake of the drug by the fluke is influenced by a P-glycoprotein linked efflux pump . Experiments have shown that inhibition of this pump leads to potentiation of triclabendazole activity . [27] In addition , triclabendazole resistant flukes have been shown to metabolize triclabendazole sulfoxide to sulfone to a greater extent than susceptible flukes . [28] . Thus , the combined effect of reduced drug uptake and more active drug metabolism could reduce the effective concentrations of triclabendazole . Triclabendazole has been used in livestock to treat Fasciola for many years . Inconsistent dosing and schedules have led to widespread resistance in cattle rearing areas in the last decade . Human infections with triclabendazole resistant Fasciola in areas with zoonotic transmission is a potential problem . In contrast to veterinary medicine in which other treatment options for Fasciola exist , in humans triclabendazole is the only first line medication with reported high efficacy . Thus , the emergence of triclabendazole resistance in fascioliasis among humans is an important clinical and public health concern as no alternative drugs are available to treat the infection . In our case series , subjects were treated with nitaxozanide ( 500 mg twice daily for 7 days ) after 2 doses of triclabendazole . This approach was based on a double blind placebo controlled trial of nitazoxanide for the treatment of fascioliasis . Although the trials showed limited efficacy in children ( 40% ) , the efficacy was slightly higher in adults ( 60% ) . [29 , 30] The development of biliary colic in some of the cases could have suggested response to the medication , but none were cured by combination treatment . This study has some limitations that made difficult the assessment of resistance . Most of the information was collected retrospectively and the number of cases was small . We were not able to recover live flukes from the subjects after treatment or generate metacercariae from the eggs collected for susceptibility testing in vitro . Nevertheless , our clinical observations suggest the presence of triclabendazole resistant Fasciola infections in a selected group of patients from Cusco . Resistant infection in livestock has already been reported in the northern highlands of Peru . Although , this report does not reflect in any way the community prevalence of triclabendazole resistance among humans in Cusco , triclabendazole resistance appears to be an emerging problem deserving attention in Peru and probably other highly endemic areas . Research on new drugs and methods to evaluate drug resistance is urgently needed to control Fasciola .
Fascioliasis is a zoonotic food borne trematode infection with a wide distribution . The complex epidemiology of this infection makes control efforts difficult . The paucity of drugs available for treatment may further hinder their success . Triclabendazole , the only first line drug for Fasciola , has been used for many years in the livestock industry . Resistant livestock Fasciola infections have emerged in developing and developed countries . However , most human trials report triclabendazole efficacies close to 100% after a few doses . Only a few cases of triclabendazole treatment failure have been published . We document 7 patients infected with Fasciola hepatica in Cusco–Peru that failed several treatment courses with triclabendazole . This raises concerns regarding preparedness to address resistant parasite infections and calls for more research to find new medications and tools to evaluate resistance .
[ "Abstract", "Introduction", "Methods", "Results/Discussion" ]
[ "invertebrates", "livestock", "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "tropical", "diseases", "geographical", "locations", "fascioliasis", "parasitic", "diseases", "animals", "peru", "trematodes", "signs", "and", "symptoms", "pharmaceutics", "neglected", "tropical", "diseases", "veterinary", "science", "veterinary", "medicine", "south", "america", "livestock", "care", "flatworms", "fasciola", "pain", "agriculture", "people", "and", "places", "helminth", "infections", "fevers", "biology", "and", "life", "sciences", "drug", "therapy", "organisms", "abdominal", "pain" ]
2016
Treatment Failure after Multiple Courses of Triclabendazole among Patients with Fascioliasis in Cusco, Peru: A Case Series
To assess the operational effectiveness of long-lasting insecticide treated materials ( ITMs ) , when used at household level , for the control of Aedes aegypti in moderately infested urban and suburban areas . In an intervention study , ITMs consisting of curtains and water jar-covers ( made from PermaNet ) were distributed under routine field conditions in 10 clusters ( 5 urban and 5 suburban ) , with over 4000 houses , in Trujillo , Venezuela . Impact of the interventions were determined by comparing pre-and post-intervention measures of the Breteau index ( BI , number of positive containers/100 houses ) and pupae per person index ( PPI ) , and by comparison with indices from untreated areas of the same municipalities . The effect of ITM coverage was modeled . At distribution , the proportion of households with ≥1 ITM curtain was 79 . 7% in urban and 75 . 2% in suburban clusters , but decreased to 32 . 3% and 39 . 0% , respectively , after 18 months . The corresponding figures for the proportion of jars using ITM covers were 34 . 0% and 50 . 8% at distribution and 17 . 0% and 21 . 0% after 18 months , respectively . Prior to intervention , the BI was 8 . 5 in urban clusters and 42 . 4 in suburban clusters , and the PPI was 0 . 2 and 0 . 9 , respectively . In both urban and suburban clusters , the BI showed a sustained 55% decrease , while no discernable pattern was observed at the municipal level . After controlling for confounding factors , the percentage ITM curtain coverage , but not ITM jar-cover coverage , was significantly associated with both entomological indices ( Incidence Rate Ratio = 0 . 98; 95%CI 0 . 97–0 . 99 ) . The IRR implied that ITM curtain coverage of at least 50% was necessary to reduce A . aegypti infestation levels by 50% . Deployment of insecticide treated window curtains in households can result in significant reductions in A . aegypti levels when dengue vector infestations are moderate , but the magnitude of the effect depends on the coverage attained , which itself can decline rapidly over time . An estimated forty percent of the world's population lives at risk of contracting dengue , which currently is the most important mosquito-borne viral disease worldwide , responsible for 24 , 000 deaths , 250 , 000–500 , 000 hemorrhagic fever cases and up to 50 million dengue infections annually [1] , [2] . The public health importance of dengue has grown rapidly in recent years , with a 30-fold increase in incidence since the 1960s . This has coincided with the expansion of the geographical range of its main vector , the mosquito Aedes aegypti [2] , [3] , and co-circulation of multiple dengue serotypes , which elevates the risk of sequential infections and severe disease [4] . No curative treatment is available and the prevention of a fatal outcome in severe dengue cases hinges on early case detection and appropriate supportive treatment . To decrease the burden of disease , prevention of transmission is crucial . As there is no vaccine yet , this is possible only by vector control . Existing A . aegypti control tools can reduce vector infestation levels , but very few have succeeded in sustaining reductions for a prolonged period [5] , [6] or in impacting on dengue transmission [7] , [8] . The national routine dengue vector control programmes in endemic countries are facing variable and often disappointing results , which are among others due to inadequate implementation processes , lack of community participation or poor user acceptance of chemical-based vector control methods [9] , [10] . Programs integrating chemical or biological based strategies with community involvement are having better results , but rarely eliminate the vector [11]–[14] , though there have been notable successes in recent years [8] . Insecticide treated materials ( ITMs ) have recently shown promise in reducing household level dengue vector infestations [15]–[17] . Unlike most dengue vector control strategies , ITMs target the adult mosquito , which is epidemiologically the most important vector stage . It is postulated that the likelihood of adult vectors contacting an ITM during host seeking reduces their life expectancy , effectively altering the age structure of the vector population , such that fewer mosquitoes live long enough to become infective with dengue [9] . Furthermore , ITMs made from long-lasting insecticide treated fabrics retain their efficacy for at least 1 year [18] , which is longer than any other applied Aedes control tool . In previous trials , ITMs were shown to have an impact on vector populations and to have high acceptance levels by householders up to a few months after distribution [15] , [17] , though the key question of whether or not this will result in reduced dengue transmission remains to be proven before ITMs can be recommended as dengue vector control tools on a large scale . Achieving and sustaining high levels of ITM uptake and use under routine programme conditions rather than in an experimental situation also are fundamental prerequisites to success and this too requires investigation . We report here on an intervention study in urban and suburban areas of Trujillo State , Venezuela , where insecticide treated window curtains and water jar covers were distributed by local health committees and by the existing routine vector control programme . Over a period of 18 months , we assessed the uptake and use of these tools by local householders and their effectiveness in controlling the vector population , comparing the Breteau and the pupae per person indices at several time points before and after intervention; and also comparing them with indices from untreated areas of the same municipalities . This study received clearance from the ethical committee that oversees research of the Institute of Tropical Medicine , Antwerp and from the bio-ethics committee of the Jose Witremundo Torrealba Research Institute , Trujillo . Community representatives from each participating cluster approved the intervention and written informed consent was obtained from each individual household included in the study . The ITMs were made from material that is approved by the World Health Organization Pesticide Evaluation Scheme ( WHOPES ) for bed net use . The trial was registered at ClinicalTrials . gov ( number NCT 00883441 ) . The study was conducted in the municipalities of Valera ( 9°19′N 70°36′W; altitude 541 m ) and San Rafael de Carvajal ( 9°20′N 70°35′W; altitude 556 m; referred to as Carvajal ) in Trujillo State in north west Venezuela . The climate is tropical with two rainy seasons ( March/April and September/November ) , an average annual rainfall of 750 mm and temperatures ranging from 16–37°C . The city of Valera is the economic capital of the state , with 128 , 556 inhabitants and a population density of 534 inhabitants/km2 . Carvajal is a suburban municipality located 4 km from Valera , with 44 , 213 inhabitants and a population density of 493 inhabitants/km2 . Dengue is endemic in Trujillo State . Between 2006 and 2008 , dengue case reports ranged between 203 and 396 cases/100 , 000 inhabitants/year , of which 1 . 1 to 4 . 9% were hemorrhagic cases ( Regional direction of epidemiology and statistics , Trujillo state health ministry ) . In Trujillo , dengue affects children and young adults ( up to 24 years old ) primarily , with cases peaking between August and December . All routine A . aegypti vector control activities are carried out by a team of 24 persons from the department of environmental health of the Trujillo state health ministry . Activities comprise adulticiding ( indoor spraying with malathion 94% ULV ) and larviciding ( Abate ) within a 200 meter radius of a reported dengue case . When the number of clinical cases exceeds the epidemic alert level of the endemic channel , space spraying with vehicle-mounted equipment is added ( Department of environmental health of the Trujillo state Health Ministry ) . The study had been designed as a cluster randomized trial for comparing the efficiency of 2 ITM distribution models in terms of uptake and continued use that would at the same time permit a non-randomized before - after comparison to evaluate the effectiveness of the ITMs . Uptake rates attained at distribution and the subsequent reductions in coverage over time were equivalent in both models and are not analyzed in depth in this manuscript . In March 2006 10 clusters ( defined as distinct neighbourhoods of 300–600 houses ) were recruited for an intervention study and were stratified based on location in urban or suburban areas , which differ in Aedes infestation levels and population characteristics . The 10 clusters were selected from 18 districts that had dengue notification rates of at least 40/10 , 000 inhabitants ( 2003–2005 ) . The inclusion criteria at cluster level were: middle or low socio-economic status ( the number of high socio-economic level clusters was small and they were not representative of the overall area ) with fewer than 50% of the population residing in apartment blocks ( for operational reasons ) . Rural areas , where principal land use was for agricultural activities and where dengue was not a major health problem , were excluded . The sample size ( number of clusters ) was determined using calculations proposed by Hayes and Bennett [19] , and had a power of 80% to detect a 5-fold decrease in the Breteau index at an alpha error level of 0 . 05 ( assuming a between-cluster coefficient of variation of 0 . 50 ) . After collecting baseline data for 1 year , insecticide treated ( IT ) curtains and IT jar covers were distributed to all households in the 10 intervention clusters that had given their informed consent and agreed to use them . This was done between July and September 2007 either by the routine vector control programme or by local health committees . The ITcurtains and ITcovers were made from the same PermaNet ( Vestergaard-Frandsen ) polyester netting treated with a long-lasting formulation of deltamethrin ( 55 mg/m2 ) , coated with an unknown protectant ( not disclosed by the manufacturer ) to prevent degradation of the insecticide when exposed to UV light . The manufacturer stated that this material does not require re-treatment and its insecticidal effect is expected to last for up to 2 years or 6 “standard” washes ( http://www . vestergaard-frandsen . com/permanet-curtain-e-brochure . pdf , accessed 22/05/2008 ) . The number of ITcurtains and ITcovers distributed per house depended on the number of windows in the main living area and bedrooms ( up to a maximum of 5 curtains/house ) and on the numbers of 150–200 liter water storage jars present in the house ( no maximum of covers per house ) . During distribution , at least one person in every household received information on the use and maintenance of the ITMs through person-to-person communication . A total of 1120 houses were selected through systematic random sampling ( 560 houses across all urban clusters , corresponding to every 3rd house; and 560 across all suburban clusters , corresponding to every 4th house ) for periodic entomological monitoring . Five independent entomological surveys were conducted by a survey team ( trained and supervised by an experienced entomologist , author MO ) at roughly six-month intervals: two pre-intervention surveys ( October 2006 , March/April 2007 ) and three post-distribution surveys ( November/December 2007 , April 2008 , January 2009 ) . In all houses , containers were inspected for the presence of larvae and pupae . If pupae were found they were counted , collected , transported to the laboratory and allowed to emerge for species identification . As external control data , in line with Kroeger et al . [15] , we used the entomological data collected in the municipalities of Valera and Carvajal as part of the routine surveillance activities . The intervened clusters represented 7% of the total number of houses in the municipalities and the populations of vectors in the municipalities were considered beyond the influence of the ITMs used in the study clusters , and expected to fluctuate naturally as influenced by seasonal parameters only . The routine entomological surveillance data were collected by the department of environmental health of the Trujillo state health ministry: Houses in a radius of 200 m around a confirmed dengue case are visited and infestation of water holding containers with immature vector stages is recorded . We report the routine data for the months when entomological surveys were conducted in the intervention clusters and correct for the differences in data collection methods in the analyses ( see subsection on data analysis ) . Rainfall and temperature data were obtained from the weather station at the Valera airport ( located in between the two study sites , that are , themselves , 4 km apart ) ( http://www . wunderground . com/history/station/80426 ) . The averaged rainfall data from the month of each entomological survey plus data from the preceding month were used in our analyses . Data on routine A . aegypti control activities that took place in the intervention clusters during the month of each entomological survey and the preceding month were retrieved from the reports of the vector control programme . For each cluster , an intensity score was calculated based on the number of houses treated per cluster ( adulticiding and/or larviciding ) : 0 = no activities , 1 = less than 10% of houses covered , 2 = between 11 and 20% of houses covered , 3 = between 21 and 50% houses covered , 4 = more than 51% of houses covered , 5 = intensive and repeated spraying and larviciding in all houses . A baseline socio-economic survey was conducted during June–July 2006 in a systematic random sampling of 955 households ( 465 urban and 490 suburban ) . The survey encompassed both general and dengue related household characteristics . We used the Graffar Method , adapted to the Venezuelan context by Méndez-Castellano [20] to classify the households according to socio-economic stratum based on the profession of the head of household , education level of the mother , main source of family income and housing conditions . It classifies households from stratum I ( upper class ) to stratum V ( critical poverty ) . A random sub-sample of households that participated in the baseline sociological survey was revisited in September 2007 , February 2008 and January 2009 to observe the presence and use of the ITMs . On the same occasions , we inquired about any adverse effects attributed to the use of the ITMs . We developed 2 indicators for assessing ITcurtain coverage per cluster: the percentage of houses with at least 1 curtain and the median number of curtains per house . For ITcovers , the 2 indicators were the percentage of houses using at least 1 ITcover and the percentage of eligible water storage jars covered . We used the chi square test and the Mann-Whitney test to compare urban and suburban coverage proportions and medians respectively , and calculated 95% confidence intervals for their differences . A . aegypti infestation levels were the outcome measures . We calculated the Breteau index ( BI , number of containers positive with immature A . aegypti/100 inspected houses ) per cluster , per setting ( urban/suburban ) and per survey round . We compared trends over time for the BI in the urban and suburban study clusters . The trend of the BI in the corresponding municipalities was used to control for the natural seasonal fluctuations in vector populations . We calculated the % difference between the values at each survey time point and the October 2006 pre-intervention values . This permitted to represent the trends and to allow , at the same time , for the different methodology used to measure BI in intervention clusters and the municipality . For the intervention clusters , the pupae per person index ( PPI , number of A . aegypti pupae/inhabitant ) - considered a more accurate proxy for adult mosquito abundance [21] - was also calculated per cluster , per setting and per survey round . 95% confidence intervals around each estimate at each time point were calculated with a negative binomial regression model taking into account the cluster design . To estimate the independent effect of ITM coverage on A . aegypti infestation at the cluster level , we constructed two generalized linear random effect regression models with a negative binomial link function , taking into account the repeated measurements . Both outcome measures , BI and PPI , were the dependent variables . Each of the 10 clusters contributed 1 data point at each of the 5 entomological survey rounds . The models included the % ITcurtain and ITcover coverage , the setting ( urban or suburban ) , intensity of routine vector control activities in each cluster , municipal level data on A . aegypti infestation , rainfall and temperature . Interaction between variables was assessed . Based on the corresponding model regression-coefficient , the independent effect of ITcurtains coverage on BI was graphically represented over the empirically observed coverage range . Data were analyzed with Stata 10 . 0 ( StataCorp , Texas , USA ) and SPSS 17 . 0 ( SPSS Inc . , Chicago , IL , USA ) . In less than 1% of cases some essential data were missing , and these households were subsequently withdrawn from the database . The 5 urban and the 5 suburban clusters contained 1742 and 2359 houses , respectively . All clusters completed the study protocol through January 2009 and all were included in the analysis . Households in urban clusters had a significantly higher socio-economic status ( p<0 . 05 ) ( Table 1 ) . Permanent water supply was more common in urban than suburban intervention clusters ( 65 . 8% and 44 . 9% respectively; p<0 . 001 ) , while houses in suburban clusters had more water storage jars than urban houses ( averages of 1 . 2 and 0 . 5 water storage jars/house respectively; p<0 . 05 ) . All 510 pupae collected in the October 2006 survey belonged to subgenus Stegomyia and 89% were A . aegypti . Also , in November 2007 , after ITM distribution , 89% of the collected pupae were identified as A . aegypti . Since the vast majority of immature stages were A . aegypti at both time moments , all immature stages observed in entomological surveys were assumed to be of this species , in line with Arredondo-Jimenez and Valdez-Delgado [22] . Immediately after ITM distribution , in September 2007 , coverage with ITcurtains was similarly high ( >75% ) in both settings ( Table 2 ) . ITcover coverage levels differed significantly between settings , with lower coverage in urban ( 12 . 9% of houses ) compared to suburban ( 31 . 1% ) clusters ( p<0 . 001 ) . This was not surprising since , at baseline , 73 . 1% of jars in urban clusters were found to be fitted with a locally purchased cover as compared to 35 . 9% in suburban clusters ( regardless of condition or use ) ( p<0 . 05 ) . Minor allergic reactions ( temporary [less than 48 hrs] itching of palms ) after handling the ITMs were reported in 5 . 4% of houses . As the trial progressed , ITM coverage declined such that by the end of the 18-month follow-up period ( January 2009 ) , fewer than 40% of houses were using ITcurtains and fewer than 20% were using ITcovers ( Figure 1 ) . There were no significant differences between the settings ( urban or suburban ) in the rates of decline in coverage of ITcurtains ( p>0 . 05 ) or ITcovers ( p>0 . 05 ) . It was observed that the ITcovers deteriorated as the study progressed , particularly the elasticated rim , resulting in poorly sealed jars . Prior to intervention , the BI was 42 . 4 in suburban intervention clusters , which was significantly higher than the BI of 8 . 5 in the urban clusters; the PPI was 0 . 9 and 0 . 2 , respectively ( Figure 2 ) . Both settings experienced significant declines in the BI ( IRR = 0 . 30 , 95% CI 0 . 22–0 . 49 ) and PPI ( IRR = 0 . 23 , 95%CI 0 . 14–0 . 37 ) in the months following the distribution of the ITMs ( Figure 2 ) . In November 2007 , the BI fell to 15 . 8 in urban and 3 . 8 in suburban intervention settings , and the PPI decreased to 0 . 2 and 0 . 03 , respectively . While the PPI gradually increased again in the suburban ( but not in the urban ) clusters , the BI remained consistently at 55% or more below pre intervention levels in both settings throughout the 18-month follow up period . In contrast , BI levels in urban and suburban municipalities ( 59 . 0 and 82 . 6 respectively in October 2006 ) fluctuated considerably and did not show the same patterns as the study areas ( Figure 3 ) . The differences in average BI between the pre- and post-intervention period was −63% for urban and −67% for suburban intervention clusters . For the corresponding municipal areas these differences were −35% and −26% respectively . In the random effects negative binomial regression models ( Table 3 ) , the setting ( urban or suburban ) and the amount of rainfall were significantly correlated with the BI and PPI in the intervention clusters . Overall infestation levels at the municipality level and temperature had no significant effect , and it was interesting to note that the intensity of routine A . aegypti control activities in the clusters also had no effect . Temperature was not included in the final model because it did not confound the relationship between BI or PPI and ITcurtain coverage . ITcurtain coverage was highly significantly correlated with both entomological indicators , but ITcover coverage was not . Each 1% coverage increase with ITcurtains reduced the BI and PPI by 2% . Plotting this effect ( Figure 4 ) , reveals that 50% coverage or more was needed to halve the BI , and that the reduction , in absolute terms , depended on the initial BI . The presence of insecticide treated window curtains in an environment where A . aegypti infestation levels are moderate ( BI ranging between 10 and 50 ) can lead to substantial reductions in the Breteau index and the pupae per person index . The scale of the effect depends on the household coverage attained , and without any further intervention , curtain usage may rapidly decline over time . The demonstration of an effect on the PPI , in addition to the BI , is important , as PPI is considered a more accurate measure of local adult vector abundance , and therefore more directly related to dengue transmission risk [21] . We were unable to directly monitor adult A . aegypti populations ( due to operational reasons and resource constraints ) let be to measure dengue transmission . This study was also limited by the fact that it is a before and after evaluation and that we did not include randomized control clusters in the design , but used routine entomological surveillance data from the whole municipality as ‘control’ data . However , it is not likely that temporal trends in vector density should selectively affect the intervention clusters only and bias , if any , could not explain the differences that we observed . Importantly , the effects we attribute to the actual coverage with ITcurtains and ITcovers are independent of the comparison with the control data at specific time points , and of possible confounding factors such as rainfall , temperature , routine vector control activities and temporal trends that were controlled for in the analysis . Additionally , it has been demonstrated that the insecticide in the PermaNet curtains , when used by households , remains effective for at least 1 year [18] . Furthermore , the local mosquito population remained susceptible to deltamethrin , as shown in bioassays on A . aegypti collected in neighbouring municipalities where the same ITcurtains were concurrently deployed in the frame of another study ( A . Lenhart , personal communication ) . Major strengths of this study , from a public health perspective , are the length of the pre- and post intervention data collection periods and the fact that the ITMs were introduced into the community by the routine vector control programme and the local health committees , which mimics the reality of routine operational conditions . Both these elements markedly distinguish our approach from the one used in the only previous study on ITcurtain deployment for dengue control [15] . In that study , Kroeger et al . [15] reported no differences in entomological indices between intervention and control arms . This lack of a difference was attributed to a “spill-over” of the effect of the IT curtains in the intervention clusters into the adjacent control clusters . The authors performed therefore a before and after evaluation of Stegomyia indices , using routine surveillance data collected in nearby communities , and concluded that the changes in Stegomyia indices in the control and intervention study areas combined , could not be explained by natural fluctuations in the vector population due to seasonal parameters . The coverage attained at ITcurtain distribution in our study is lower , but still comparable to the 87% coverage attained in the Venezuelan site of the above efficacy trial [15] , in which delivery was controlled by the research team , and we achieved reductions in vector density of the same order of magnitude . However , our follow up period was much longer and our results on sustained use differ markedly . While coverage remained stable up to the final observation at month 5 in Kroeger et al . [15] , we observed a 20% decline in use 6 months after distribution and over 50% at 18 months . The determinants of uptake and continued use of the ITM have been assessed [23] and it was found that uptake was linked to pre-use behaviour and contextual factors , but continued use was mainly determined by the perceived effectiveness of the tool . Furthermore , our results demonstrate that the level of coverage attained has profound implications for the effectiveness of ITcurtain interventions . We did not find a significant effect of ITcovers on entomological indices . Kroeger et al . [15] reported on the combined efficacy of ITcurtains and ITcovers , but did not study ITcover efficacy independently . They also remarked that the covers were not durable and were easily torn and that use decreased by over 30% in the initial 5 months , which concurs with our own observations . In contrast , a trial of ITcovers in Cambodia [17] reported a much higher coverage of 3 . 1 ITcovers per house and a 58% reduction in PPI at 13 weeks in the intervention area as compared to the control area ( dropping to 13% at 22 weeks post-intervention ) . Inherent differences between the studies , in A . aegypti oviposition behavior and/or variations in ITcover coverage or the quality of the materials used might explain the differences in results between studies , but further research is needed to clarify exactly how ITcovers impact on dengue vector populations . Comparisons of our results with those obtained in controlled trials of other dengue vector control tools are difficult , certainly at quantitative level , as there are variations in study design , follow-up periods and/or outcomes measured . Although direct comparisons cannot be made , a number of issues are noteworthy . First , apart from the promising results observed with insecticide treated materials [15]–[17] , and small field-laboratory studies of lethal ovitraps , ( e . g . in Brazil; [24] ) , all published controlled intervention studies to date have targeted immature dengue vector stages . Secondly , substantial and sometimes sustainable effects have been reported with approaches combining chemical and biological control [25] , chemical control and community based environmental management [13] , [14] , [26] , and biological control and environmental management [27] . Hence , strategies integrating multiple control measures appear to be more effective [28] . Thirdly , only very few of the control strategies managed to completely eliminate the vector [8] . Against this backdrop , we cautiously state that ITcurtains constitute a potentially effective novel tool for controlling A . aegypti , with efficacy likely to be optimized when deployed in combination with other vector control tools , and particularly when their use is embedded in a strategy that also mobilizes the community . However , before calling for the launch of large scale integrated effectiveness trials with ITcurtains , important questions remain regarding the efficacy , cost and implementation of ITM strategies: Does long lasting material remain effective beyond one year [18] when heavily exposed to sunlight and dust ? How efficacious are ITMs at low or very high A . aegypti infestation levels and , ultimately , what is their impact on dengue transmission ? What is their incremental cost-effectiveness at 0 . 93 USD per m2 of fabric plus approximately 0 . 5 USD for distribution [29] ? And , obviously , finally , how can the high level of coverage required for effectiveness be attained and maintained under routine conditions ?
An estimated 40% of the world's population lives at risk of contracting dengue , and it inflicts a significant health , economic and social burden on the populations of endemic areas . In the absence of a vaccine , vector control is the only available strategy to prevent transmission . Some control methods against Aedes aegypti ( the main dengue vector ) have been successful in reducing vector infestation levels , but rarely sustained the reductions for a prolonged period . We report here on the first effectiveness trial of insecticide treated curtains and jar covers against A . aegypti implemented under ‘real-life’ conditions . The coverage of tools was high at distribution , but declined quickly over the 18 months of follow up . The vector infestation levels showed a sustained 55% decrease in the intervention clusters , while no discernable pattern was observed at the municipal level . At least 50% curtain coverage was needed to reduce A . aegypti infestation levels by 50% . We concluded that deployment of insecticide treated window curtains in households can result in significant reductions in dengue vector levels , which are related to dengue transmission risk . The magnitude of the effect depends on the curtain coverage attained , which itself can decline rapidly over time .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[ "infectious", "diseases/neglected", "tropical", "diseases", "public", "health", "and", "epidemiology/preventive", "medicine", "public", "health", "and", "epidemiology/infectious", "diseases", "infectious", "diseases/epidemiology", "and", "control", "of", "infectious", "diseases" ]
2011
Evaluation of the Effectiveness of Insecticide Treated Materials for Household Level Dengue Vector Control
DNA strand-breaks ( SBs ) with non-ligatable ends are generated by ionizing radiation , oxidative stress , various chemotherapeutic agents , and also as base excision repair ( BER ) intermediates . Several neurological diseases have already been identified as being due to a deficiency in DNA end-processing activities . Two common dirty ends , 3’-P and 5’-OH , are processed by mammalian polynucleotide kinase 3’-phosphatase ( PNKP ) , a bifunctional enzyme with 3’-phosphatase and 5’-kinase activities . We have made the unexpected observation that PNKP stably associates with Ataxin-3 ( ATXN3 ) , a polyglutamine repeat-containing protein mutated in spinocerebellar ataxia type 3 ( SCA3 ) , also known as Machado-Joseph Disease ( MJD ) . This disease is one of the most common dominantly inherited ataxias worldwide; the defect in SCA3 is due to CAG repeat expansion ( from the normal 14–41 to 55–82 repeats ) in the ATXN3 coding region . However , how the expanded form gains its toxic function is still not clearly understood . Here we report that purified wild-type ( WT ) ATXN3 stimulates , and by contrast the mutant form specifically inhibits , PNKP’s 3’ phosphatase activity in vitro . ATXN3-deficient cells also show decreased PNKP activity . Furthermore , transgenic mice conditionally expressing the pathological form of human ATXN3 also showed decreased 3’-phosphatase activity of PNKP , mostly in the deep cerebellar nuclei , one of the most affected regions in MJD patients’ brain . Finally , long amplicon quantitative PCR analysis of human MJD patients’ brain samples showed a significant accumulation of DNA strand breaks . Our results thus indicate that the accumulation of DNA strand breaks due to functional deficiency of PNKP is etiologically linked to the pathogenesis of SCA3/MJD . DNA strand breaks ( SBs ) , both single-stranded ( SSBs ) and double-stranded ( DSBs ) , with various “dirty” DNA ends are among the most toxic and mutagenic lesions in mammalian genomes , because such ends block the action of DNA polymerases and DNA ligases; the conventional 3’-OH ( hydroxyl ) and 5’-P ( phosphate ) ends must be restored for gap-filling and DNA ligation to occur during repair for maintaining genomic integrity . The end-processing steps have now become a major focus because of the observation that two of the proteins involved in this process ( Aprataxin and TDP1 ) are mutated in hereditary neurodegenerative diseases [1–4] . Human polynucleotide kinase 3’-phosphatase ( PNKP ) is another DNA end-processing enzyme; it removes the 3’-P group [5–7] and catalyzes the phosphorylation of 5’-OH termini [ ( generated by some nucleases , and as intermediates of topoisomerase cleavage [5 , 8] , and thus is involved in the repair of both SSBs via the SSB repair ( SSBR ) pathway and DSBs via non-homologous end joining . It has recently been reported that mutation in PNKP or its reduced level causes an autosomal recessive disease ( termed MCSZ ) ; characterized by microcephaly , intractable seizures , and developmental delay [9] . Another very recent report showed cerebellar atrophy and polyneuropathy in humans due to PNKP mutation [10] . Unrepaired SBs can impact cell fate in several ways . The most likely effect in proliferating cells is the blockage or collapse of DNA replication forks during the S phase . However , replicating cells have the ability to repair such DSBs in the nuclear genome via homologous recombination [11 , 12] . In non-proliferating cells , such as postmitotic neurons , SBs might cause stalling of RNA polymerase II during transcription , particularly at the 3’-P ends , and induce cell death via p53-mediated activation of apoptotic pathways [13] . Hence , SBs pose a significant threat to maintaining genomic integrity and neuronal cell survival [14] . While screening for PNKP-associated proteins , we identified Ataxin-3 ( ATXN3 ) in the PNKP immunopull-down complex . Eukaryotic ATXN3 is ubiquitously expressed in various tissues and also found both in the cytoplasm and nucleus of neuronal cells [15–18]; its normal biological function , despite many serious efforts , is not yet fully understood . It has been suggested that ATXN3 is a multifunctional protein that plays a role in transcriptional regulation , ubiquitination and protein homeostasis maintenance via its deubiquitinating activity [19–22] . ATXN3 is a polyglutamine ( polyQ ) -containing protein that carries 14–41 polyQ repeats in the normal population; when the polyQ length expands beyond 60 , it causes Spinocerebellar ataxia type 3 ( SCA3; OMIM:109150 ) , also known as Machado-Joseph Disease ( MJD ) , a hereditary neurodegenerative disorder characterized by gait ataxia , dysarthria and ophthalmoplegia , variably associated with spasticity , dystonia or amyotrophy and peripheral neuropathy [23] . Although it is a rare disease , genetic testing of large cohorts of ataxia patients identified MJD as one of the most commonly inherited ataxias worldwide [24 , 25] . It has been widely assumed that protein misfolding and aggregation is a major mechanism of SCA3 pathogenesis , but a clear consensus regarding the molecular mechanism of the toxic gain of function of the pathological form of ATXN3 has still not been reached . Here we report that WT ATXN3 stimulates , and by contrast mutant ATXN3 blocks the DNA 3’-end-processing activity of PNKP , and the resulting accumulation of DNA SBs may contribute significantly to SCA3 pathogenesis via modulating the DNA damage-response pathway . We and several other groups have reconstituted PNKP-mediated DNA strand-break repair in vitro , and also characterized the individual steps in the multistep repair process [26 , 27] . However , the in vivo repair process is far more complicated; for efficient DNA damage processing and repair , most , if not all of the components involved in a particular repair pathway , form complex ( es ) in a dynamic fashion within a “repair factory” [28] . To delineate the different steps and molecular mechanisms of the PNKP-mediated repair process , we screened for PNKP’s interacting partners via 2D-gel electrophoresis and subsequent mass spectroscopic ( MALDI-TOF-TOF MS ) analysis of a large-scale affinity pull-down of the PNKP immunocomplex . In the 500 mM ( most tightly bound ) salt eluate from the PNKP complex , we identified ATXN3 ( Figs . 1 and S1 ) , a poly-glutamine-containing protein with no known role in DNA repair , except for its association with HHR23 proteins , which are involved in nucleotide excision repair [29] . Characterization of other pulled down proteins and their role in PNKP-mediated DNA strand-break repair are currently under investigation . To examine ATXN3’s association with PNKP , we immunoprecipitated ( IP’d ) PNKP and ATXN3 separately from the nuclear extract ( NE , benzonase treated to remove DNA and RNA to avoid DNA-mediated co-immunoprecipitation ) of human HEK-293 ( human embryonic kidney cell line ) ( Figs . 2A and B ) and SH-SY5Y ( a human neuroblastoma cell line ) cells ( S2A and S2B Figs . ) using the respective anti-protein ( PNKP or ATXN3 ) antibody ( Ab ) . The experiment was conducted in two cell lines to test the global nature of ATXN3’s interaction with PNKP and related repair proteins , and thus to confirm its general role in DNA SB repair . We confirmed the presence of ATXN3 in the PNKP IP , along with Polβ and Lig IIIα , the known PNKP-associated proteins ( Figs . 2A and S2A ) [30] . Moreover , the reverse IP with an anti-ATXN3 Ab showed the presence of PNKP , Polβ and Lig IIIα ( Figs . 2B and S2B ) , suggesting that ATXN3 is indeed a part of the complex and plays a role in PNKP-mediated DNA SB repair . To test the specificity of the association between PNKP and ATXN3 , we depleted PNKP ( S3 Fig . ) and ATXN3 ( S4 Fig . ) individually , using siRNAs . Immunoblot analysis of the whole gel shows a single band of PNKP ( S3 Fig . , ln 6 ) or ATXN3 ( S4 Fig . , ln 5 ) in the NE from control siRNA-treated cells that runs with the corresponding purified recombinant protein ( used as marker ) . Significant depletion ( ∼85% ) of the corresponding band ( S3 Fig . , ln 7 and S4 Fig . , ln 6 ) was noted in the depleted extract . Importantly , IPs using the corresponding Ab ( Fig . 2A and 2B , ln 3 ) clearly shows that depletion of PNKP or ATXN3 strongly decreases the levels of their partners in the complex ( compare lane 5 ) , indicating the specificities of both the Abs and the association of the proteins in the complex . To further confirm the in-cell association of PNKP with ATXN3 , we performed an in situ proximity ligation assay ( PLA ) , in which the close physical association of two proteins is visualized by a fluorescent signal [31–33] . To assess the specificity of their interaction , cells were treated with control or ATXN3 siRNA; forty-eight hours after siRNA transfection , the cells were fixed , co-immunostained with PNKP ( anti-mouse ) and ATXN3 ( anti-rabbit ) Abs and performed PLA per the manufacturer’s protocol ( Olink Bioscience ) . We randomly selected 50 cells and manually counted the numbers of PLA foci . It was found that control siRNA-treated cells had 10–12 PLA signals/cell whereas ATXN3 siRNA-treated cells had only 1–2 foci ( Fig 2C ) . In addition , to assess the background levels of non-specific staining , cells were processed in the absence of antibodies; no fluorescence signals were detected , as was the case when control Abs were used in place of specific primary Abs ( Fig 2C , right panel ) , further indicating specificities of PNKP’s association with ATXN3 . As a follow-up to our initial observation of ATXN3’s association with PNKP , we performed a GST pulldown using purified proteins to test the binary interaction of ATXN3-Q29 ( WT with 29 polyQ repeats ) and -Q72 ( the pathological form with 72 polyQ repeats ) with GST-PNKP . Binary interactions are often driven by the interaction of specific regions in the constituent proteins . PNKP has 3 domains: forkhead-associated domain ( FHA; residues 1–119 ) , phosphatase domain ( P; residues 120–339 ) and kinase domain ( K; residues 340–521 ) . We thus separately expressed and purified GST-tagged full-length PNKP and all 3 of its domains from E . coli; equimolar solutions of each were then incubated separately with WT or mutant ATXN3 at 4°C for 4 h . Beads containing the interacting proteins were repeatedly washed with 200 mM salt-containing buffer . Fig . 2D shows that both forms of ATXN3 interacted directly with full-length as well as the kinase domain of PNKP . Importantly , the phosphatase domain interacted only with WT , but not with mutant ATXN3 . We also performed far-Western analysis to detect binary interaction between full-length PNKP vs . WT or mutant ATXN3 . S5 Fig . ( top panel , lns 1& 2 ) shows that both forms of ATXN3 do interact with PNKP , but not with bovine serum albumin ( BSA; ln 3 , used as a control ) . All these data are also consistent with the findings in the accompanying manuscript by Gao et al . ( Figs . 1 , 2 and Figs . S1 , S3 & S4 ) where it is shown , using various techniques , that both WT and mutant ATXN3 associate with PNKP in-cell , and in mouse and human brain tissues ( control and SCA3 ) . Given the stable interaction of PNKP with both forms of ATXN3 , we tested the functional implications of these interactions by analyzing PNKP’s 3’-phosphatase activity . Fig . 3A shows that WT ATXN3 stimulated PNKP’s 3’-phosphatase activity ( ln 2 vs . lns 3–7 ) ∼4-fold; in contrast , ATXN3-Q72 reproducibly and significantly abrogated PNKP’s activity ( ∼3 . 5-fold , Fig . 3B , ln 2 vs . ln 6; n = 3 ) . Notably , neither the WT nor the mutant form of ATXN3 affected the activities of Polβ ( S6A Fig . , ln 1 vs . 2–3 and 4–5 ) or Lig IIIα ( S6B Fig . ) , both of which associate with PNKP in a multiprotein complex that conducts SSBR [30] . These data indicate that the pathological form of ATXN3 specifically blocks PNKP’s 3’-phosphatase activity . To further examine the in-cell effects of ATXN3 on PNKP , we first examined the phosphatase activity in the nuclear extract of control vs . PNKP siRNA-treated cells . We found that PNKP depletion almost completely abrogated phosphate release , indicating that PNKP is the major , if not the only , 3’-phosphatase in mammalian cells ( S7 Fig . , ln 1 vs . ln 2 ) . We then measured the phosphatase activity in the NE prepared from ATXN3-depleted ( by ∼80% , Fig . 4A ) vs . control shRNA-expressing cells . Fig . 4B shows a significant decrease in the phosphatase activity in ATXN3-depleted compared to control shRNA-expressing cells ( by ∼70% , Fig . 4B , ln 3 vs . ln 4 ) . Furthermore , addition of purified WT ATXN3 to the NE of ATXN3shRNA-depleted ( Fig . 4B , lns 5–8 ) but not to PNKP-depleted ( S7 Fig . , ln 3 ) cells led to the recovery of phosphatase activity , thus confirming that the stimulation of phosphatase activity by ATXN3 in NE is PNKP-mediated . These results also confirmed ATXN3’s role in PNKP-mediated DNA SB repair . To examine whether the decreased repair activity of the ATXN3-depleted cells affected the accumulation of DNA strand breaks , genomic DNA was isolated from control and ATXN3-siRNA-treated cells , and the levels of SBs in the HPRT and POLB genes were compared using long amplicon quantitative PCR ( LA-QPCR ) as described previously [33] . DNA strand breaks were measured for both the genes using a Poisson distribution , and the results were expressed as lesion /10 kb genome [34] . Studies were conducted in both HEK-293 ( Fig . 5A ) as well as in neuronal SH-SY5Y cells ( S8 Fig . ) to examine the effect of ATXN3 depletion on DNA SB repair in general . A decreased level of the long amplicon PCR product ( ∼10–12 kb ) would reflect a higher level of DNA SBs , and amplification of a smaller fragment for each gene should be similar for the samples , because of a lower probability of SB formation in a shorter fragment . We indeed observed a higher level of DNA lesion frequency per 10 Kb ( 0 . 81 vs 0 . 34 for HPRT , 0 . 6 vs 0 . 24 for POLB in HEK 293 cells; 0 . 45 vs 0 . 1 for HPRT , 0 . 38 vs 0 . 14 for POLB in SH-SY5Y cells ) in the genomic DNA of ATXN3-depleted cells than in the DNA of control shRNA/siRNA-expressing cells ( Fig . 5A ) , indicating a role of ATXN3 in DNA SB repair . To further confirm the effect of pathological ATXN3 on PNKP’s activity , we measured 3’-phosphatase activity in the nuclear extracts of cells ( CSM14 . 1 , a rat cell line ) conditionally expressing vector control , WT ( Q23 ) and mutant ( Q70 ) ATXN3[35] . Although PNKP levels were comparable in all the extracts ( Fig . 6A ) , PNKP’s activity was significantly decreased ( ∼45% ) in the NE of mutant ATXN3 ( Q-70 ) -expressing compared to WT or vector control cells ( Fig . 6A , ln 3 vs . lns 1 , 2 ) . We also performed comet assays to examine the level of DNA SBs , and indeed found a significant increase in tail moment with the mutant ATXN3-expressing cells ( Fig . 6B ) , which is consistent with decreased PNKP activity and subsequent accumulation of DNA SBs . Furthermore , comet assays were conducted in PNKP-depleted and mutant ATXN3-expressing human SH-SY5Y cells and compared with the appropriately paired control cells ( S9 Fig . ) . As expected , PNKP-depleted and mutant ATXN3-expressing cells also showed comparable amounts of DNA damage . Furthermore , we tested PNKP-mediated total single-strand break repair ( SSBR ) using a 3’-P-containing oligo substrate , and found that total SSBR was also significantly lower ( 55±4 . 2% ) in the mutant cell NE . However , supplementation with purified PNKP rescued the repair to the level of WT extract ( arbitrarily set as 100% ) . These data further support the idea that the mutant ATXN3 specifically blocks the activity of PNKP , but not that of DNA polymerase or ligase ( S6 Fig . ) . Finally , we measured PNKP’s 3’-phosphatase activity in the NEs prepared from four different regions of the brains of the transgenic mice expressing expanded human ATXN3 ( CMVMJD135 ) vs . WT ATXN3-expressing mice [36] . Extracts were obtained from the animals at an age ( 25 weeks ) at which they manifest loss of strength , decreased coordination of movement , loss of balance , and abnormal reflexes [37] . PNKP activity was affected in the mutant mice ( n = 5 ) , mostly in extracts obtained from the deep cerebellar nuclei , a key region known to be affected in human SCA3 neuropathology ( Fig . 6C ) . Taken together , these results indicate that the pathological form of ATXN3 affects PNKP activity and subsequent global SB repair in vivo . The studies described above were helpful in understanding the basic biochemistry of the effects of WT vs . mutant ATXN3 on PNKP’s activity in cultured cells and in mouse tissues , which then prompted us to examine their relevance to human pathology . We received three SCA3 patient and age-matched control tissues from the same region of the brain ( details in the accompanying manuscript by Gao et al ) . Although we failed to prepare intact nuclei and measure PNKP activity from post-mortem brain tissues , we were able to isolate total genomic DNA , and so analyzed the accumulation of DNA SBs in a long fragment of the POLB gene , using LA-QPCR as described [38] . We indeed found significantly higher levels of SBs in the genomic DNA of the SCA3 patients ( 0 . 64 vs 0 . 14/10 Kb ) than in DNA from the control group ( Fig . 7 ) , consistent with our observations in cells and mouse tissues . Likewise , our accompanying manuscript by Gao et al . also showed the formation of 53BP1 foci , a key transducer of the DNA damage response , in SCA3 but not control brains ( their Fig . 3 & S5 ) , further supporting our hypothesis . Machado-Joseph disease , or spinocerebellar ataxia type 3 ( MJD/SCA3 ) , is one of the most common dominantly inherited ataxias worldwide . Many years have passed since the cloning of ATXN3 , and to date the pathogenic mechanism responsible for the disease is still not clearly understood , so no therapy is available for it . Several reports suggest that both WT and pathological forms of ATXN3 have protease , deubiquitinating ( DUB ) , and autocatalytic activities , and are involved in the ubiquitin-proteasome pathway [39–42] . The pathological form of ATXN3 is prone to aggregation , and is thought to exert toxic effects in a dominant manner , although it has also been suggested that some loss of function of ATXN3 contributes to the disease . However , ATXN3 knockout mice have no significant SCA3-like phenotype [43] , so the lack of DUB activity is not sufficient to explain the pathogenesis . Furthermore , various studies suggest that the formation of aggregates may not necessarily be required for pathological ATXN3 to exert its toxicity; aggregate formation could be a secondary phenomenon [44 , 45] . The relationship of inclusion bodies to cellular dysfunction in SCA3 pathogenesis thus remains controversial [44 , 45] . Therefore , understanding the molecular mechanism responsible for the toxic gain of function of the pathological form is important for devising ways to combat the disease . Our serendipitous and unexpected identification of ATXN3 , a poly Q-containing protein with no established linkage to DNA repair , as a part of the PNKP complex prompted us to investigate ATXN3’s role in PNKP-initiated DNA end processing . Here we have clearly shown that both WT and mutant ATXN3 interact directly with PNKP . Immunohistochemical studies involving transgenic mouse tissues and human brains also showed close association of PNKP with both forms of ATXN3 ( Also see Gao et al . Fig . 2 and Fig . S3 , S4 ) . However , WT ATXN3 stimulates , and by contrast mutant ATXN3 significantly blocks , PNKP’s 3’-phosphatase activity , resulting in the accumulation of DNA SBs . However , how the mutant ATXN3 blocks PNKP’s 3’-phosphatase activity , but not that of DNA polymerase β or DNA ligase IIIα , warrants further investigation . Our GST pull-down data clearly show that the kinase domain interacts with both forms , while the phosphatase domain interacts only with the WT but not the mutant ATXN3 ( Fig . 2D ) . This aberrant interaction of the pathological form may be responsible for blocking PNKP’s 3’-phosphatase activity . A recent study showed a role of ATXN3 in protecting cells against H2O2-induced oxidative stress [46] . The decreased 3’-phosphatase activity in the NE from ATXN3-depleted cells , which show the accumulation of SBs , and the presence of PNKP , Polβ and Lig IIIα in the ATXN3 IP further supports WT ATXN3’s role in PNKP-mediated DNA SB repair and is thus consistent with the above findings . Whether WT ATXN3 plays any role in other types of DNA end processing in association with such other enzymes as TDP1 , TDP2 etc . also warrants further investigation . Furthermore , it has recently been shown that PNKP is phosphorylated by ATM ( Ataxia telangiectasia mutated ) and DNA-PK in response to DNA damage , which prevents degradation via ubiquitination , and the cellular level of PNKP is maintained via this process [47–49] . Whether ATXN3 plays any role in controlling PNKP’s posttranslational modification via its DUB activity , and thereby in regulating PNKP’s cellular steady-state level , is currently under investigation in our laboratory . The human brain is one of the most metabolically active tissues and consumes large amounts of oxygen . Oxidative stress-induced DNA SBs are quite common in such tissues . DNA SBs can also arise spontaneously in the brain as a result of normal physiological neuronal activity [50] . If not repaired , DNA SBs can block transcription , which is active at all cell cycle stages and particularly important in postmitotic tissues like neurons . Recently it has been clearly documented that deficiencies in DNA end-processing activity ( such as that of PNKP , TDP1 and Aprataxin ) are linked to neurological diseases [1–4 , 9] . Pathological ATXN3-mediated inhibition of PNKP’s activity , particularly in the context of heterozygosity ( one WT and one mutant ATXN3 allele ) , would be a slow and progressive phenomenon , which could provide an explanation as to why the SCA3 pathology is largely related to age . We therefore hypothesize that the accumulation of persistent DNA SBs due to lower PNKP activity triggers an intrinsic signaling event leading to dysregulated neuronal gene expression that impairs neuronal function , leading to neurodegeneration and the development of ataxia . Our accompanying manuscript clearly shows that either PNKP depletion or the expression of mutant ATXN3 leads to ATM-mediated activation of two parallel proapoptotic pathways; one is p53- and the other c-Abl→PKCδ-mediated apoptotic cell death , a hallmark of neuropathogenesis ( Gao et al . Figs . 4–7 , Figures S15–S17 ) . These data thus provided further support for our hypothesis . It is noteworthy that persistent accumulation of DNA SBs and elevated p53-dependent apoptosis have also been found to be an important pathogenic feature in Fragile X syndrome ( one of the most common form of inherited mental retardation ) , which is caused by the transcriptional silencing of fragile X mental retardation protein ( FMRP;[51] ) . FMRP is primarily localized in the cytoplasm; however , a small amount is present in the nucleus , which raised the possibility that the protein might have a role there as well . Recent studies involving both Drosophila and mammalian systems showed a novel and unanticipated role of nuclear FMRP protein , which takes part in the DNA Damage Response ( DDR ) pathway via γH2AX phosphorylation in a chromatin binding-dependent manner [52 , 53] . In a separate report it was also shown , that a Drosophila FMRP mutant ( dfmr1 ) is hypersensitive to genotoxic stress [51] . Collectively , all these data reflect a degree of mechanistic similarity between ATXN3 and FMRP in regulating DDR , and their subsequent role in neuronal survival via maintaining genome stability . Repeat expansions and instabilities are causal factors for numerous inherited neurological disorders , including SCAs [54 , 55] . A recent report showed elevated expression levels of DNA repair proteins in the cerebellum compared to the striatum , and consequent higher repeat instability in the striatum as well . These data suggest that higher level/activity of DNA repair proteins act as a safeguard against repeat instability , which in turn leads to reduced somatic genome instability in the specific region of brain dictating the related disease pathologies [56] . In conclusion , MJD/SCA3 is a complex disease; modulation of various cellular processes , such as protein aggregation and loss of DUB activity may all play a role in the disease process . Our studies show that the accumulation of DNA SBs due to decreased PNKP activity is likely to be the major contributor to SCA3 pathogenesis . Therefore , upregulating the expression of PNKP might be a promising therapeutic strategy for combating SCA3 pathogenesis . Human gastric epithelial AGS ( purchased from ATCC ) and human embryonic kidney ( HEK-293 ) cells were cultured and maintained in DMEM/F12 containing 10% FBS at 37°C . Mesencephalic dopaminergic rat cell lines ( CSM14 . 1 , a gift from Bernd Evert , University of Bonn ) conditionally expressing vector alone or WT human ATXN3 ( Q23 ) or pathological ATXN3 ( Q70 ) were cultured and maintained at 33°C in DMEM with 10% FBS containing 0 . 1 mg/ml G418 , 0 . 1 mg/ml hygromycin , 4 . 0 ug/ml puromycin and 1 . 0 μg/ml tetracycline as described previously [35] . The human neuroblastoma cell line SH-SY5Y ( ATCC number CRL-2266 ) was cultured at 37°C in a 1:1 mixture of DMEM/high glucose nutrient ( Invitrogen ) supplemented with 10% ( v/v ) fetal bovine serum ( FBS ) ( Biochrom ) , 2 mM glutaMAX ( Invitrogen ) , 100 U/mL penicillin and 100 μg/mL streptomycin . To generate ATXN3-depleted cells , SH-SY5Y cells were transfected with an shRNA sequence targeting ATXN3 or a scrambled shRNA sequence , as described elsewhere and the stably transduced cells were selected 48 h post-transfection with 500 ng/ml puromycin . Stably infected cell lines were cultured and maintained as described earlier in presence of 25 ng/mL puromycin ( Sigma Aldrich ) . The medium was changed every two days . Differentiation was induced by exposure to 0 . 1 μM all-trans-retinoic acid ( RA , Sigma Aldrich ) in opti-MEM ( Invitrogen ) supplemented with 0 . 5% FBS for 7 days; the medium was replaced every two days . PNKP and ATXN3 depletion was carried out in HEK-293 cells using siRNAs ( 80 nM ) purchased from Sigma ( SASI_Hs01_00067475 ) and Dharmacon ( On-target siRNA , J-012013-05 ) , respectively . The control siRNA was purchased from Sigma ( Mission universal control , SIC001 ) . The cells were harvested 60 h post-transfection and nuclear extracts were prepared as described [57] . A large-scale immunoprecipitation from AGS ( gastric epithelial ) cell nuclear extracts ( 100 mg , benzonase treated to remove DNA and RNA to avoid DNA-mediated co-immunoprecipitation ) used mouse IgG ( control ) and anti-PNKP antibody ( mouse monoclonal Ab , Cytostore ) - conjugated agarose beads as described earlier [58] . The immunoprecipitates ( IPs ) were washed extensively with cold TBS ( 50 mM Tris-HCl , pH 7 . 5; 200 mM NaCl ) containing 1 mM EDTA , 1% Triton X-100 and 10% glycerol . The complexes were then eluted from the beads stepwise with 25 mM Tris-HCl , pH 7 . 5 containing 300 , 400 and 500 mM NaCl . The eluates were subjected to 2-dimensional gel electrophoresis ( 2-DE ) separation and the protein spots ( Sypro Ruby , Molecular Probes ) that were specifically present in the PNKP IP and not in the IgG IP were subjected to mass spectroscopic identification in the University of Texas Medical Branch Biomolecular Resource Facility . Co-IP analysis was performed from HEK-293 and SH-SY5Y cells according to established protocol by Aygun et al , with modifications as applicable [57] . In situ Proximity Ligation Assay ( PLA ) between PNKP ( anti-mouse Ab , a gift from Michael Weinfeld ) and ATXN3 ( anti-rabbit Ab , Proteintech ) was carried out according to the protocol as described [58] using a Duolink PLA kit ( QLink Bioscience Cat# LNK 92101 K101 , Uppsala , Sweden ) . The 3’-phosphatase activity of PNKP in the nuclear extract or with purified recombinant PNKP was assayed as we described previously [58 , 59] . Genomic DNA from HEK-293 and SH-SY5Y cells was extracted using the Qiagen Genomic-tip 20/G kit per the manufacturer’s directions . This kit is particularly useful , as it minimizes DNA oxidation during the isolation step and has been previously used for LA-QPCR assays [33 , 38] . For isolation of genomic DNA from postmortem brain tissues , we followed the protocol of Kovtun et al . as described [60] . To decrease aerial oxidation during genomic DNA preparation , TEMPO ( 2 , 2 , 6 , 6-tetramethylpiperidine-N-oxyl ) was added to all solutions at a concentration of 100μM immediately before use [60] . The DNA was quantitated by Pico Green ( Molecular Probes ) in a 96-well plate . Gene-specific LA-QPCR assays for measuring DNA SBs were performed as described earlier [33] using LongAmp Taq DNA Polymerase ( New England BioLabs ) . A 10 . 4 kb region of the HPRT gene or 12 . 2 kb of the POLB gene was amplified from human genomic DNA using the primers described previously [38] . To ensure the linearity of PCR amplification with respect to the number of cycles and DNA concentration , preliminary assays were carried out . Since amplification of a small region would be independent of DNA damage , a small DNA fragment from the same gene was also amplified for normalization of amplification of the large fragment [33] . The amplified products were then visualized on gels and quantitated with ImageJ software system . The extent of damage was calculated in terms of lesion/10 kb genome following Poisson’s distribution according to methods as described [34] . We received the bacterial expression vectors for ATXN3-Q29 ( WT ) and ATXN3-Q72 ( mutant ) as a kind gift from Randall Pittman ( Univ . of Pennsylvania ) and purified both recombinant proteins as described[19 , 20] . WT PNKP and its domains were purified as described previously [58] . Purified fractions were dialyzed in PBS containing 50% glycerol and 1 mM DTT and stored at −20°C . GST pulldown assays were performed as described previously [61] . Briefly , GST-tagged full-length PNKP or its three individual domains ( 20 pmol ) were bound to glutathione-Sepharose beads ( 20 μL ) , washed thoroughly with buffer A ( 25 mM Tris-Cl pH 7 . 5 , 0 . 1% Triton X-100 , 0 . 1 mM EDTA and 10% glycerol ) containing 150 mM NaCl , and then incubated with WT or mutant ATXN3 ( 20 pmol ) with constant rocking for 4 h . at 4°C in 0 . 5 ml of 150 mM salt containing buffer A . After extensive washing with 200 mM NaCl containing buffer A , 20% of the bound proteins were separated by SDS-PAGE for immunoblotting analysis using an anti-ATXN3 Ab ( Abcam ) . CMVMJD135 mice , expressing human ataxin-3 carrying 135 glutamines , were used in this study [37] . These mice display a progressive motor phenotype starting at an age of 6 weeks , with extensive phenotypic overlap with the human disease; they also develop ATXN3-positive neuronal inclusions in different regions of the brain and spinal cord , as well as a cell number and/or volume decrease in key regions for the disease , such as the pontine nuclei and the dentate nuclei of the cerebellum . Transgenic mice and control non-transgenic littermate mice ( n = 5 per genotype ) with a mean age of 25 weeks were sacrificed by decapitation , and brain slices were obtained for the macrodissection of pontine nuclei , substantia nigra , deep cerebellar nuclei and hippocampi using a stereomicroscope ( Model SZX7 , Olympus America Inc . , Center Valley , PA , USA ) . Nuclear extracts from these different brain regions were obtained as previously described [62] .
We report that human polynucleotide kinase 3’-phosphatase ( PNKP ) , a major DNA strand break repair enzyme , stably associates with Ataxin-3 ( ATXN3 ) . This protein contains repeats of the amino acid glutamine , and the expansion of these repeats from 14–41 to 55–82 glutamines leads to a neurological disorder called Spinocerebellar ataxia type 3 ( SCA3 ) , also known as Machado-Joseph Disease ( MJD ) . However , how this expansion of glutamine leads to ataxia has remained unclear . Here we show that normal ATXN3 protein stimulates , but the expanded ATXN3 inhibits , PNKP’s DNA repair activity , causing an accumulation of DNA damage . Furthermore , a SCA3 mouse model showed decreased PNKP activity , mostly in a region that is highly affected in MJD patients’ brains . Analysis of human MJD patients’ neuronal DNA showed significant accumulation of DNA strand breaks . Collectively , the accumulation of DNA damage due to decreased PNKP repair activity is likely to induce neuronal cell death , a hallmark of SCA3/MJD pathogenesis .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[]
2015
The Role of the Mammalian DNA End-processing Enzyme Polynucleotide Kinase 3’-Phosphatase in Spinocerebellar Ataxia Type 3 Pathogenesis
The T-cell factor ( TCF ) family of transcription factors are major mediators of Wnt/β-catenin signaling in metazoans . All TCFs contain a High Mobility Group ( HMG ) domain that possesses specific DNA binding activity . In addition , many TCFs contain a second DNA binding domain , the C-clamp , which binds to DNA motifs referred to as Helper sites . While HMG and Helper sites are both important for the activation of several Wnt dependent cis-regulatory modules ( W-CRMs ) , the rules of what constitutes a functional HMG-Helper site pair are unknown . In this report , we employed a combination of in vitro binding , reporter gene analysis and bioinformatics to address this question , using the Drosophila family member TCF/Pangolin ( TCF/Pan ) as a model . We found that while there were constraints for the orientation and spacing of HMG-Helper pairs , the presence of a Helper site near a HMG site in any orientation increased binding and transcriptional response , with some orientations displaying tissue-specific patterns . We found that altering an HMG-Helper site pair from a sub-optimal to optimal orientation/spacing dramatically increased the responsiveness of a W-CRM in several fly tissues . In addition , we used the knowledge gained to bioinformatically identify two novel W-CRMs , one that was activated by Wnt/β-catenin signaling in the prothoracic gland , a tissue not previously connected to this pathway . In sum , this work extends the importance of Helper sites in fly W-CRMs and suggests that the type of HMG-Helper pair is a major factor in setting the threshold for Wnt activation and tissue-responsiveness . During metazoan development , Wnt/β-catenin signaling , often called “canonical” Wnt signaling and hereafter referred to as “Wnt signaling” , is required to drive multiple stage and tissue specific events [1]–[4] . Wnt signaling is essential in such diverse events as specification of the anterior/posterior body axis , and limb , heart , intestinal and craniofacial development [1] , [5]–[8] . In several cases , Wnts have been shown to act as morphogens , regulating different targets in a concentration dependent manner [9]–[11] . The pathway is also needed in adult tissues for stem cell maintenance and wound healing [12]–[16] , and disregulated Wnt signaling has been implicated in a host of cancers and other human pathologies [17]–[19] . How a single signaling pathway accomplishes such a wide range of outcomes remains a major question in developmental biology and tissue homeostasis . Variation in Wnt-dependent cis-regulatory modules ( W-CRMs ) likely contribute to the diversity of Wnt transcriptional responses , though the mechanisms are poorly understood . Members of the T-cell factor ( TCF ) family of transcription factors ( TFs ) are principal mediators of Wnt signaling [20] , [21] . In many contexts , TCFs act as a transcriptional switch , binding with co-repressors on W-CRM chromatin in the absence of signal , and then recruiting β-catenin and other co-activators in response to Wnt signaling [22] , [23] . ChIP-seq studies have found that TCFs co-localize with several other TFs in specific cell types [24]–[31] , and combinatorial control may be one method to achieve tissue or temporal specificity . While not as well appreciated , the sequence composition of the TCF binding sites in W-CRMs can also have a major influence on its transcriptional output [32] , [33] . A better understanding of the cis-regulatory logic of W-CRMs will shed more light on how they differ in their responsiveness to Wnt signaling , and how TCFs regulate this process . All TCFs share a highly conserved High Mobility Group ( HMG ) domain , which binds DNA with sequence specificity [34]–[37] . The HMG recognition motif is a 9–11 bp sequence with the consensus SCTTTGWWSWW . Sequences roughly conforming to this consensus have been shown to be required for activation of numerous W-CRMs [1] , [38] . Reporter genes with 3–16 copies of high affinity HMG binding sites behind a basal promoter , such as TOPFLASH , have been used successfully as an experimental readout for Wnt signaling in a number of contexts [38]–[41] . However , such high-density clusters of perfect HMG sites are not found in naturally occurring W-CRMs [1] , [38] . Furthermore , there are several instances where synthetic HMG site reporters do not respond to endogenous Wnt signaling in vertebrate tissues [42] , [43] . In Drosophila embryos and larval imaginal discs , where Wingless ( Wg , a fly Wnt ) signaling is highly active , synthetic HMG site reporters have little or no expression [38] , [44] . These results strongly suggest that under physiological conditions , HMG sites are not sufficient for Wnt activation of W-CRMs . We have previously reported that several fly W-CRMs contain a GC-rich motif , found near HMG sites , that was critical for Wnt activation [44] . This motif , termed the Helper site , was bound by a second DNA-binding domain in TCF/Pangolin ( TCF/Pan , the fly TCF ) known as the C-clamp [44] . The C-clamp was originally discovered in “E-tail” isoforms of mammalian TCF1 and TCF4 genes [45] . These TCF isoforms also bound Helper sites , which were essential for the activation of specific mammalian W-CRMs [45]–[47] . Reporters containing only multimerized copies of Helper sites did not respond to Wnt signaling , but these motifs synergized with HMG sites to greatly enhance the Wnt activation of reporter constructs [44] . The presence of an intact C-clamp domain imparts increased affinity for DNA containing both HMG and Helper sites and a functional C-clamp is required for TCF/Pan activation of fly W-CRMs [44] , [48] . These data support a bipartite binding model for C-clamp containing TCF family members , where HMG domain-HMG site and C-clamp-Helper site interactions allow TCF to properly locate W-CRMs and regulate Wnt target genes . Surprisingly , our initial characterization of Helper site sequences in Drosophila W-CRMs identified numerous putative Helper elements with variable spacing and orientation with respect to HMG sites ( Figure 1A ) . This was interesting , because bipartite binding by TFs is typically very sensitive to the spacing and orientation of the two sites . Examples of this spacing/orientation constraint include several type II nuclear receptor/RXR heterodimers [49]–[51] and Smad heterodimers [52] , [53] . Spacing and orientation is also important for the POU family member Pit-1 [54] , [55] , and the spacing of half-sites has been shown to determine whether target genes are activated or repressed . In contrast , the related zinc finger DNA binding proteins SIP1 and δEF1 have a high tolerance for half-site spacing and orientation variability , perhaps because the two DNA-binding zinc finger clusters are separated by a large and presumably flexible linker region [56] . Given the short ( 10 aa ) spacer between the HMG and C-clamp domains in TCF/Pan , it was unclear whether all the variable HMG-Helper site pairs found in W-CRMs were bona fide TCF binding sites . As no consistent organizational preference was seen between the functional HMG and Helper sites ( asterisks , Figure 1A ) , a systematic approach was needed to determine the constraints of HMG-Helper pair flexibility . In this report , we examined the rules of TCF/Pan binding to HMG-Helper site pairs using several experimental approaches . We identified two HMG-Helper site configurations that were bound by TCF/Pan with highest affinity in vitro , one where the Helper site is located 6 bp upstream of the HMG site , and the other where it is immediately adjacent downstream . These two HMG-Helper site configurations also had the greatest transcriptional activity in many tissues , and were most enriched in genomic regions bound by TCF/Pan . We suggest a model where the DNA-bending activity of the HMG domain enables TCF/Pan to recognize both these HMG-Helper site configurations . However , our data also make clear that the presence of a Helper site near a HMG site in any orientation and with variable spacing enhanced TCF/Pan binding , and many of these “non-optimal” arrangements had transcriptional activity , some with striking tissue-specificity . In addition , we have shown that altering the orientation/spacing of an HMG-Helper site pair in a W-CRM has a dramatic effect on its sensitivity to the Wg morphogen in imaginal tissues . Finally , we used our knowledge of the cis-regulatory code for TCF/Pan binding to informatically identify new W-CRMs . One of these drove expression in the prothoracic gland ( PG ) , a major component of larval ring gland , an endocrine tissue not previously linked to Wg signaling . We found that Wg is expressed in the ring gland , and that blocking Wg signaling in this organ resulted in early larval developmental arrest . These findings highlight how a better understanding of DNA recognition by TCF/Pan can enhance our ability to identify novel W-CRMs and discover new aspects of Wnt biology . The Drosophila Helper site was previously defined by sequence alignment of several functional motifs as having the consensus GCCGCCR ( R = A/G ) [44] . However , a shorter consensus has been reported for vertebrate E-tail TCFs ( RCCG ) [45] . To test whether all seven nucleotides of the longer consensus were required for maximal activation , we performed serial mutagenesis on the second Helper motif in the nkdIntE W-CRM luciferase reporter ( Figure 1B ) . This reporter was highly activated by expression of Armadillo ( Arm , the fly β-catenin ) , which contains a point mutation rendering it resistant to degradation ( Arm* ) [44] , [57] . Substitution of any of the first four positions had as dramatic a reduction in reporter activation as mutating the entire 7 bp motif . Mutation of the last three positions had a slightly less severe reduction ( Figure 1B ) . Thus , at least in this context , all seven bp in the GCCGCCR motif are important for maximal activation by Wnt signaling . Previous evidence supported the idea that HMG and Helper sites work in closely spaced pairs . For example , the contribution of individual HMG sites to W-CRM activation varied widely , with HMG sites proximal to Helpers sites more likely to contribute to activation [44] , [57] . To further test the HMG-Helper site pair hypothesis , we again used the nkdIntE W-CRM , previously found to contain three functional HMG binding sites , and two functional Helper sites [44] . The arrangement of these functional sites suggests that there are two closely spaced HMG-Helper site pairs , separated by 101 bp ( Figure 1A ) , but there remained a formal possibility of longer-range interactions between HMG and Helper sites . As previously reported [44] , activation by Arm* is nearly abolished by mutation of the three HMG binding sites ( Figure 1C ) . Four additional nkdIntE mutants were created , leaving one HMG and one Helper site intact . The two constructs retaining a HMG site and Helper site in close proximity activated target gene transcription at levels higher than the HMG mutant control . The first pair had a small but reproducible activation , while the activation of the second intact pair was more pronounced ( Figure 1C ) . In contrast , the reporters where the intact HMG and Helper sites were separated ( P1Dist & P2Dist ) were not activated . These data support the idea that HMG and Helper sites must be in close proximity to respond to Wnt signaling . There are four possible orientations for HMG-Helper site pairs , which we have termed Akimbo ( AK ) , Rewind ( RW ) , Fast Forward ( FF ) , and Knock Knee ( KK ) ( Figure 1D ) . Helper sites are defined by the aforementioned seven bp GCCGCCR consensus ( Figure 1B ) . We used the eleven bp consensus of SCTTTGWSWW determined for TCF/Pan [58] to define HMG sites . It should be noted that the four orientations indicate the relationship between the HMG and Helper sites , and not the relationship of these bipartite motifs to the nearest transcription start site ( TSS ) . Therefore , it is possible to have either the Helper or HMG site first in all four orientations , depending on which strand contains the consensus ( Figure 1D ) . The spacing of each pair is defined by the number of bp between the two motifs , e . g . , the examples in Figure 1D have a spacing of 6 bp and will hereafter be referred to as AK6 , FF6 , etc . We previously reported that the presence of a Helper site increased the ability of TCF/Pan to bind to DNA in vitro [44] . These experiments utilized an AK5 HMG-Helper site configuration . To determine the relative binding affinities of different HMG-Helper site pairs , we performed electromobility shift assays ( EMSAs ) with a recombinant His-tagged protein containing both the HMG and C-Clamp domains of TCF/Pan , a labeled AK6 probe ( see Figure 1D for sequence ) and unlabeled competitor oligonucleotides containing the 0 and 6 bp versions of each orientation . The AK6 probe was labeled with an infrared ( IR ) -dye , allowing quantification of the gel shift with the Licor Odyssey IR platform ( see Materials and Methods for further details ) . Representative blots are presented ( Figure 2A ) and the data from multiple experiments are summarized by showing the half maximal inhibitory concentrations ( IC50 ) for each competitor ( Figure 2B ) and the dose-response curves on semi-log line graphs ( Figure 2C ) . The competition assays clearly showed that TCF/Pan had a preference for oligonucleotides containing an AK6 or FF0 motif . The IC50 for AK6 and FF0 were 5 . 1 and 9 . 4 nM , respectively ( Figure 2B ) . RW6 , KK0 , FF6 and AK0 were in the next group , with IC50's between 38 . 7–66 . 6 nM . KK6 and RW0 had the lowest relative affinity ( IC50 of 99 . 7 and 189 nM , respectively ) , which was still greater than two HMG site only oligonucleotides ( IC50 of 292 and 969 nM ) ( Figure 2B ) . The data indicate that AK6 and FF0 are bound with the greatest affinity by TCF/Pan , but also demonstrate that the presence of a nearby Helper site in any orientation enhances its recognition by TCF/Pan . To explore the functional orientation/spacing constraints between various HMG-Helper site configurations , we created a series of synthetic W-CRMs containing two HMG-Helper site pairs upstream of a minimal promoter . All four orientations were tested for the ability to activate a luciferase reporter gene at 0 , 3 , 6 , 9 and 12 bp spacing in transfected Kc cells ( see Supplemental S1 for complete sequences used ) . Three out of the four orientations ( AK , FF & KK ) exhibited levels of activation by Arm* higher than reporters containing HMG sites alone or the empty vector ( EV; Figure 3A ) . Spacing of HMG-Helper pairs affected the level of activation in an orientation-dependent manner . The AK reporters were significantly different from the HMG site only reporters at most spacings tested , but peak activity occurred with AK6 ( Figure 3A ) . In contrast , for FF , activation was greatest at 0 bp spacing , with much weaker activation at greater distances . The KK orientation constructs showed weak activation at several spacings , though activation was slightly greater when the HMG and Helper sites were closer together . In contrast to the other three orientations , the RW reporters were not able to activate gene transcription more potently than the HMG site controls at any of the spacings tested ( Figure 3A ) . To explore the spacing requirements of the AK and FF HMG-Helper site pairs in the context of endogenous enhancers , we chose two previously characterized W-CRMs from the nkd locus . First , we used a modified nkdIntE , termed nkdIntEP2P , where the first two HMG sites and Helper are mutated , leaving only the endogenous AK6 motif ( Figure 3B ) . We replaced this motif with either AK or FF motifs containing 0 , 6 , or 12 bp spacers . In this context , AK6 promoted the most robust activation , while the AK0 and AK12 constructs had lower levels of activation , consistent with the behavior of the synthetic constructs . Also consistent with the synthetic data , FF0 was the only spacing of the FF nkdIntEP2P constructs to activate at levels significantly different than the HMG only control ( Figure 3B ) . We then examined a second W-CRM , nkdUPE2 , previously shown to have a specific HMG and Helper site that were major contributors to Wg activation [57] . This HMG-Helper pair ( green box in Figure 3C cartoon ) has a degenerate FF1/KK0 conformation . Mutation of the HMG site resulted in a dramatic decrease in activation by Arm* ( Figure 3C ) . We altered this HMG-Helper site pair to an AK1 , AK6 , or FF6 configuration . The AK motifs were more flexible in the range of functional spacing , as both AK1 and AK6 containing W-CRMs activated transcription as robustly as the WT FF1 element ( Figure 3C ) . The FF motif displayed a strong preference for the 1 bp spacer configuration , with strongly decreased activation from the FF6 element ( Figure 3C ) . However , the FF6 motif retained some activation by Arm* , as compared to the HMG site mutant ( Figure 3C ) . The data with the nkdIntE and nkdUpE reporters indicate that the configurations that worked well ( e . g . , AK6 , FF0 ) in the synthetic reporters in cell culture ( Figure 3A ) also are optimal for the nkd W-CRMs in cell culture reporter assays . It should also be noted that increasing the spacing of the HMG-Helper site pairs ( e . g . , AK12 , FF6-12 ) always resulted in a decrease in transcriptional activity , consistent with a requirement for these motifs to be relatively near each other . To test whether the functional constraints for HMG-Helper site configurations observed in cell culture assays also held true in the context of an intact organism , transgenic reporter lines with different HMG-Helper pairs were generated in Drosophila . ΦC31 site directed integration of reporter constructs was utilized to eliminate position effects [59] . All four orientations at 0 and 6 spaces were tested , as these HMG-Helper pairs displayed distinct outputs in cell culture ( Figure 3A ) . The same sequences used in the cell culture reporters were utilized in the transgenic reporters ( sequences provided in Table S1 ) . None of the constructs displayed strong expression during embryogenesis ( Figure S1 ) . In contrast , in imaginal discs from wandering 3rd instar larva , several HMG-Helper site reporters had expression patterns consistent with activation by Wg signaling ( Figure 4A , 4B ) [1] , [60]–[62] . These activities were similar to the expression pattern of Wg ( Figure S2 ) , and were Helper site dependent , as the HMG site only reporters had no detectable expression over the basal Hsp70 promoter ( Figure 4A , 4B ) . Consistent with our cell culture data , the most potent activity was seen with both the AK6 and FF0 HMG-Helper pairs ( Figure 4A , 4B ) . Other configurations ( AK0 , FF6 , KK0 ) displayed weaker expression . Interestingly , with the exception of RW0 , the presence of Helper sites in all other orientation/spacings tested displayed more activity than the HMG site only controls in the imaginal discs ( Figure 4A , 4B ) . These results indicate that Helper sites have a surprising degree of flexibility in potentiating the ability of HMG site to respond to Wg signaling . While the AK6 and FF0 synthetic reporters displayed the most activity in imaginal discs , there were tissue-specific differences in their expression . AK6 was the most robust responder to Wg signaling in wing imaginal discs ( Figure 4A ) , while FF0 was the most highly expressed reporter in eye/antennal discs ( Figure 4B ) . In some non-imaginal tissues , the other two orientations displayed the highest level of activation . For example , RW0 drove robust expression in the larval epidermis , in the cells underlying the naked cuticle located between denticle belts ( Figure 5C ) , while other generally favorable configurations , like FF0 , had less expression ( Figure 5B ) . In addition , the AK6 reporter had extremely weak expression in the corpora allata ( CA ) , also known as the medial secretory cells of the ring gland ( Figure 5E ) , while KK6 was expressed at much higher levels ( Figure 5F ) . This expression was completely inhibited by expression of a dominant negative version of TCF/Pan ( TCFDN ) [58] in the CA ( Figure 5G′ ) . A summary of all the collected expression data from the eight HMG-Helper site reporters is shown in Figure 5H . FF0 and AK6 were clearly the strongest reporters in imaginal discs and had intermediate expression in the epidermis . However , they were weakly expressed in the CA . Strikingly , RW0 , which had no detectable expression in the imaginal discs , displayed high expression in the epidermis and CA . KK0 & KK6 had weak expression in the discs , no activity in the epidermis and the highest expression in the CA ( Figure 5H ) . These data suggest the possibility that altering HMG-Helper site architecture may be a way to create a repertoire of tissue-specific responses to Wg signaling . The in vitro DNA binding assays described earlier ( Figure 2 ) are a reductionist approach to understanding HMG-Helper site recognition by TCF/Pan . An alternative is to determine whether HMG-Helper site pairs are enriched in genomic sequences bound by TCF/Pan . A genome-wide survey of TCF/Pan localization in germband extended Drosophila embryos was performed and made publicly available [28] . Germband extension is a developmental stage when Wg signaling is patterning the embryonic epidermis and mesoderm [63]–[66] . For one timepoint ( 6–8 hr after fertilization ) , 2079 high confidence TCF/Pan peaks were identified [28] . We analyzed the DNA covered by these TCF/Pan peaks ( ∼2 . 9×106 bp ) for HMG-Helper pairs and compared these regions to equivalent randomly selected intronic and intergenic DNA . To analyze these genomic sequences , we created a program to identify HMG and Helper site pairs , which could then be sorted for orientation and distance ( see Materials and Methods ) . Position Weight Matrices ( PWMs ) of each motif were created from the collection of functional HMG and Helper sites we have identified [44] , [57] ( Figure S3 ) . This allowed us to analyze DNA sequences using different stringencies for calling HMG and Helper sites . We considered PWM values of 4 . 5 for HMG sites and 6 . 5 for Helper sites to be a fairly stringent criteria for these motifs , while 3 . 5 and 5 . 0 ( for HMG and Helper sites respectively ) was considered a more relaxed calling criteria . Regardless of the criteria used , HMG-Helper pairs were enriched in the TCF/Pan bound regions . With the stringent criteria , pairs with 0–15 bp spacers were 3 . 48 times more likely to occur in bound peaks than in random DNA ( Figure 6A ) . This enrichment level was considerably higher than that obtained for HMG sites only ( 1 . 46 times enriched in bound DNA ) or for the Helper sites , which were underrepresented in bound DNA ( 0 . 76 times ) compared to random DNA . Using the relaxed criteria for calling motifs , many more HMG-Helper sites were identified ( 2139 versus 448 ) , and they were 2 . 4 fold enriched in TCF/Pan bound versus random DNA ( see Figure S4 ) . A closer look at the spacing between HMG-Helper pairs in all four orientations revealed two general messages . First , the enrichment over random DNA was most pronounced in configurations that were favorable for in vitro binding and/or transcriptional activity in cell culture and imaginal discs . For example , at the stringent calling criteria , FF0-2 and AK0-6 pairs were 6 . 1 times as likely to be found in TCF/Pan bound compared to random DNA ( Figure 6A ) . Second , despite this first point , it was also true that HMG-Helper sites in every orientation at almost every spacing were enriched in TCF/Pan bound DNA ( Figure 6A ) , and this was also true at the more relaxed criteria for calling motifs ( Figure S4 ) . It should also be noted that there were a number of palindromic motifs ( e . g . YGCCGGCR ) that were double called , either as both AK and RW or as both FF and KK . These pairs are represented as the overlapping area in the Venn diagrams ( Figure 6A ) . In addition to examining TCF/Pan localization in the Drosophila genome , Junion and co-workers surveyed four other TFs involved in cardiogenesis: the GATA factor Pannier , phosphorylated Mad ( pMAD ) , Tinman ( Tin ) and Dorsocross ( Doc ) . They found that many genomic locations contained several of these TFs , which often contained functional W-CRMs that were active in cardiac or mesodermal cells [28] . To determine if the frequency of HMG-Helper site pairs was different at sites where TCF/Pan co-localized with these TFs , we partitioned the TCF/Pan bound peaks into those in which the peak center was within 150 bp of another TF's peak , and those in which the center was not within 150 bp of any of the tested TFs . We called this latter class of peaks “TCF unique” , though this is only known for the TFs included in the analysis . This caveat aside , it is still interesting to note that FF0-2 and AK0-6 pairs were 16 . 25 times more likely to be found in the TCF unique peaks compared to random DNA , while these motifs were less enriched in the peaks shared with Pannier ( 4 . 42 fold ) and pMad ( 3 . 78 fold ) ( Figure 6B; Figure S5 ) . Even less enrichment was observed in the peaks TCF/Pan shared with Tinman and Dorsocross ( 3 . 07 & 1 . 80 fold , respectively ) ( Figure S5 ) . These data suggest that the mechanism ( s ) for recruitment of TCF/Pan to chromatin differs depending on the prevalence of co-localizing TFs . We next wanted to test if we could alter the activity of an endogenous W-CRM in vivo by replacing a suboptimal HMG-Helper site pair with an “optimal” configuration . nkdUPE2 was a good candidate , since this W-CRM is active in the imaginal discs [44] , [57] , and contains an endogenous RW4 HMG-Helper site pair ( green box , Figure 7A ) which contributes only weakly to activation by Wg signaling in cell culture [57] . The RW4 motif was reconfigured to an AK6 pair through site-directed mutagenesis ( Figure 7A ) . Strikingly , this “optimized” W-CRM reporter displayed increased expression in the wing , haltere and eye/antennal imaginal discs , as well as in the embryonic epidermis ( Figure 7B–7F′ ) . The domain of reporter gene expression was also increased in the wing discs ( arrows in Figure 7B , 7B′ ) . The expression of the optimized reporter was inhibited by TCFDN ( Figure S6 ) , as we have described previously for the wild type reporter [57] . These results suggest that the optimized W-CRM has greater sensitivity to the secreted Wg morphogen . Previously , we used in silico searches for clusters of HMG and Helper sites to identify novel W-CRMs , without factoring in the orientation and spacing of potential HMG and Helper site pairs [44] . As our data indicate certain conformations , such as FF0-1 , are overrepresented in TCF/Pan-bound DNA and drive robust activation by Wg signaling in multiple contexts , we tailored a computational search for FF1 motifs . A stringent calling criterion was used , to keep the number of hits at a manageable level . The search was performed on the right arm of chromosome 3 , containing more than 20 Mb of sequence , using Target Explorer , an on-line search algorithm [67] . The stringent criteria resulted in a short list of 23 hits ( Figure S7 ) . We chose two putative W-CRMs that contained additional lower stringency HMG-Helper pairs near the initial FF1 hit for further analysis . One W-CRM is located in the intergenic region between the related genes forkhead domain containing 96C a and b ( fd96Ca and fd96Cb ) ( Figure 8A ) . A transgene containing this W-CRM driving lacZ was robustly expressed in ventral and dorsal stripes after germband retraction , in a pattern overlapping the expression of Wg ( Figure 8B ) . To confirm that the reporter was dependent on Wg signaling , we examined its expression in embryos where Arm was depleted by driving an armRNAi transgene via the ubiquitous daughterless ( da ) -Gal4 driver [68] . Arm depletion resulted in a nearly complete loss of reporter expression ( Figure 8B′ ) . In addition to its role in Wg signaling , Arm is also required for cell adhesion [69] , [70] , raising the possibility that depletion of Arm indirectly effects expression of the W-CRM reporter . This is unlikely , because daGal4>UASarmRNAi embryos were morphologically normal at stage 13 and had normal expression of Wg ( Figure 8 , 9B′ ) . In addition , these embryos secreted cuticle with the standard patterning defects seen with reduced Wg signaling [63] , [71] , but no cuticle defects associated with loss of cellular adhesion [69] , [70]; ( Figure S8 ) . These data indicate that the cis-regulatory element identified between fd96Ca and fd96Cb is a bona fide W-CRM . fd96Ca and b transcripts were previously reported to be expressed in 14 pairs of ventral stripes after germband extension [72] . To determine whether this expression was dependent on Wg signaling , we examined expression in embryos where Wg signaling was inhibited . Using probes designed to unique regions of the fd96Ca and b transcripts , we determined that fd96Cb was expressed in ventral stripes , reminiscent of the W-CRM expression pattern , and that this expression was greatly reduced or lost in da-Gal4>armRNAi and da-Gal4>TCFDN embryos ( Figure S9 ) . Our results strongly suggest we have identified a W-CRM that is required for Wg-dependent activation of fd96Cb in embryos . The second putative W-CRM is located at chromosomal position 3R:24 . 4M , in the 3′ UTR of the forkhead ( fkh ) gene . In 3rd instar larvae , a lacZ reporter containing this element was strongly expressed in the PG , a part of the ring gland ( Figure 9B , middle panel ) . Although the PG had not been previously linked to Wg signaling , Wg protein was clearly detectable in this tissue by immunostaining using two independent antibodies ( Figure 9B , S10 ) . To confirm that the 3rd instar expression pattern was dependent on Wg signaling , the PG-specific phantom ( phm ) -Gal4 driver [73] was used to drive TCFDN . A tub-Gal80ts transgene was included [74] , so that expression of TCFDN was limited to 24 hr prior to dissection and staining . This treatment resulted in a dramatic reduction of lacZ expression compared to controls in late 3rd larval instars ( Figure 9C′ ) . The reduction is quantified in Figure 9D . These results indicate that the 3′ UTR of fkh contains a PG-specific W-CRM . fkh has been previously shown to be downstream of Wg signaling in the salivary placode [75] and has been shown to be required for the maintenance of Wg expression in the developing hindgut [76] . Combined with the promixity of the 3R:24 . 4M W-CRM to the fkh promoter , this suggested that fkh might be a Wg target in the PG . However , using an anti-Fkh antisera [77] , we found no detectable expression of Fkh in the ring gland , suggesting that the 3R:24 . 4M W-CRM may act at a distance to regulate expression of another gene . While the identity of the gene ( s ) regulated by the 3R:24 . 4M W-CRM is not clear , our finding that the reporter is dramatically inhibited by expression of TCFDN suggests that Wg signaling may play a role in ring gland biology . Consistent with this , when TCFDN is expressed via the phmGal4 from embryogenesis on , developmental arrest occurred during the first larval instar with 100% penetrance . These results argue that Wg signaling has a previously unappreciated role in the development of the ring gland . Previous work has shown that TCFs containing C-clamp domains recognize two distinct DNA sequence motifs , HMG sites ( via the HMG domain ) and Helper sites ( via the C-clamp ) [44]–[46] , [48] , [78] . The close proximity of these motifs suggested that they act as HMG-Helper site pairs , which we confirmed through site-directed mutagenesis ( Figure 1C ) . Since HMG and Helper sites are often clustered in W-CRMs ( Figure 1A ) , it was not readily apparent what orientation and spacing constraints exist for these sites to form a functional bipartite TCF binding site . In this report , we employed a variety of approaches to determine which HMG-Helper site configurations enhanced TCF/Pan binding in vitro and in vivo , and which ones allowed transcriptional activation by Wnt/β-catenin signaling . Our analysis revealed that HMG-Helper pairs in the FF0 and AK6 arrangement are preferred in a number of situations . These configurations were bound by TCF/Pan with the highest affinity in vitro ( Figure 2 ) and were highly enriched in chromatin bound by TCF/Pan in embryos ( Figure 6 ) . In cell culture , synthetic reporters with FF0 and AK6 pairs were the most highly activated by Wnt signaling ( Figure 3A ) . Similar results were also obtained in transgenic reporter assays in several imaginal discs ( Figure 4 ) . These results demonstrated a strong correlation between DNA binding affinity of HMG-Helper pairs for TCF/Pan and their ability to mediate Wnt-dependent activation of transcription in several contexts . While the aforementioned data support the view that some HMG-Helper site configurations are better than others , additional analyses paint a more complex picture . In the context of endogenous W-CRMs , FF1 and AK6 were also the most active in promoting transcriptional activation , but AK1 was just as good in some contexts ( Figure 3B , 3C ) . This dovetailed well with the computational analysis of TCF/Pan ChIP-Seq data , where AK0-6 showed the highest enrichment for this orientation ( Figure 6 ) . However , AK0 showed only moderate affinity in vitro ( Figure 2 ) , similar to other configurations ( KK0 , FF6 , RW6 ) which had reduced or no functional activity in synthetic reporters in cultured cells ( Figure 3A ) and imaginal discs ( Figure 4 , 5H ) . The correlation between DNA binding affinity and transcriptional activation was poorest in the larval epidermis and CA , e . g . , RW0 and KK6 drive robust activity in these tissues despite being weakly bound in vitro , while higher affinity motifs drive much weaker expression . A disconnect between in vitro binding affinity and transcriptional activation in cells has also been observed for glucocorticoid receptor [79] . This work and our data demonstrate that some caution is needed when inferring functional significance from in vitro binding studies . Another general lesson from our work is that the presence of a Helper site near a HMG site , no matter the orientation , increased TCF/Pan binding affinity and its ability to mediate Wnt activation of transcription . This is evident in the EMSA data , where all eight HMG-Helper pairs were bound with greater affinity than HMG sites alone ( Figure 2 ) , and in TCF/Pan bound chromatin , where enrichment of HMG-Helper pairs was observed over a surprisingly wide array of orientation/spacings ( Figure 6 ) . This flexibility was also observed functionally in the synthetic reporters , where HMG site alone constructs had no detectable expression but all eight HMG-Helper site configurations tested had detectable reporter activity in some tissues ( Figure 5H ) . How can the HMG and C-clamp domains , which are separated by only ten amino acid residues , bind to HMG-Helper pairs with such diversity ? We think it likely that DNA bending by TCF/Pan is a major contributor to this flexibility of DNA recognition . Murine LEF1 has been shown to bend DNA more than 110° [80] and TCF/Pan possesses a similar ability [33] . The C-Clamp is located 10 amino acids C-terminal to the basic tail ( BT ) in TCF/Pan [1] , which may place the C-clamp in the interior of the DNA bend , allowing it to “swing” , and interact with Helper sites located either “upstream” of the HMG binding site ( AK ) or “downstream” ( FF ) ( Figure 10 ) . The bend is centered between the third and fourth position in the eleven bp HMG site , placing Helpers in the FF orientation further away from the C-terminus of the basic tail ( BT ) of TCF/Pan ( Figure 10 ) . This could explain why FF0 was bound preferentially over FFs with larger spacing between the HMG and Helper sites . Conversely , AK6 may be bound with highest affinity ( at least in vitro ) compared to AK0 due to less steric hindrance from the amino acids connecting the BT and the C-clamp ( Figure 10 ) . In addition to DNA bending , the semi-palindromic nature of the Helper site likely explains why KK and RW configurations also enhance TCF/Pan binding ( Figure 2 & 6 ) and have transcriptional activity ( Figure 3A , 4 & 5 ) . For example , the KK0 sequence ( HMG site-TGGCGGCG ) can also be viewed as a degenerate FF1 , with a C to G substitution at positions 2 and 5 of the Helper site ( Figure 1D ) . The same is true for the RW configuration ( e . g . , RW0 could be a degenerate AK1 ) . Viewed in this way , the IC50 data becomes more coherent , with the FF and KK configurations ranked FF0>KK0>FF6>KK6 in terms of affinity for TCF/Pan and the AK and RW ones ranked AK6>RW6>AK0>RW0 ( Figure 2B ) . Defining KK and RW as degenerate FF and AK orientations , respectively , can explain why these motifs mirror the spacing constraints of their reverse configuration partners , and why they are bound with weaker affinity and typically display less transcriptional activation activity . In the wing imaginal disc , Wg has been proposed to act as a morphogen , forming a concentration gradient emanating from the dorsal/ventral boundary and regulating target gene expression in a concentration-dependent manner [81]–[84] . How W-CRMs differently respond to this Wg morphogen gradient has not been previously investigated . To address this important question , we utilized the nkdUPE2 reporter , which is activated in areas of high Wg ligand concentration in the wing disc [57] . Replacing a low affinity RW4 motif in this W-CRM with a high affinity AK6 motif elevated the level of reporter gene expression , and broadened the expression domain ( Figure 7 ) . These results argue that increasing the affinity of TCF/Pan for the W-CRM increases the sensitivity of the W-CRM to respond to the Wg morphogen . Our data are reminiscent of classic studies of CRMs that are controlled by gradients of TFs in the syncytial blastoderm stage of Drosophila embryogenesis . The affinity of the binding sites for the c-rel homolog Dorsal has been shown to set threshold responsiveness in dorsal/ventral patterning , with higher affinity sites being more sensitive to the Dorsal gradient [85] . In contrast , higher affinity sites have been shown to restrict the domain of expression of CRM reporters for the transcription factor Cubitus Interruptus ( Ci ) , an effector of Hedgehog signaling [86] , [87] , possibly due to homo-cooperative interactions with the repressive form of Ci [87] , [88] . Although Ci and TCF/Pan both act as transcriptional switches , our study indicates that the relationship between binding site affinity and interpretation of the signaling gradient are diametrically opposed for these two factors . Another interesting feature of our work is the tissue-specific responses of our synthetic HMG-Helper site reporters in transgenic fly tissues . In imaginal discs , the strength of expression of these reporters was largely correlated with binding affinity ( Figure 4 , 5H ) . However , low affinity RW and KK motifs , which had little or no activity in imaginal tissues , drove robust expression in the larval epidermis and the CA cells of the ring gland ( Figure 5C , F ) . Given that these simple reporters presumably only contain TCF/Pan sites plus a minimal promoter , the data suggest that TCF/Pan is allosterically regulated by DNA in a tissue-specific manner . Allosteric regulation of TFs by their cognate binding sites is known to occur [52] , [55] , [79] , [89] , [90] , and has been proposed previously for TCF/Pan [32] , [33] . In these cases , the type of DNA binding site is thought to control whether the TF activates or represses transcription . Our data suggest an additional aspect of allosteric regulation of TCF , i . e . , TCF/Pan bound to different HMG-Helper pairs may allow interactions with distinct co-regulators , which enable it to activate transcription in a tissue-specific manner . The aforementioned data demonstrates that different HMG-Helper pairs can profoundly influence the strength and/or tissue-responsiveness of promoters to Wnt signaling . While this was only examined in detail for a handful of reporters , our computational analysis supports the view that HMG-Helper pairs of all four orientations and various spacings contribute to TCF/Pan binding to chromatin ( Figure 6 , S4 , S5 ) . Therefore , we speculate that there are many other such examples in the genome , and that the flexibility of TCF/Pan to HMG-Helper pairs provides a versatile evolutionary mechanism for CRMs to modulate their response to Wnt signaling . The genome sequences of many metazoans indicates that almost all invertebrates have a single TCF containing a C-Clamp , while vertebrates have four or more TCFs , with E-tail isoforms of the TCF1 and TCF4 genes containing a C-clamp [1] , [21] . While the HMG and C-clamp domains are highly conserved in most metazoans , POP-1 , the C . elegans TCF , is somewhat divergent [1] . Perhaps more importantly , the linker sequence between the HMG and C-clamp domains is variable , ranging from 5–40 aa , e . g . , it is 23 aa in human TCF1E , compared with 10 aa in TCF/Pangolin and 9 aa in POP-1 [1] . These differences could influence the rules for preferred HMG-Helper site configurations in different organisms . Despite these concerns , the available data suggests that other metazoans have a similar bias for HMG-Helper pair configurations as we have found in Drosophila . We have recently characterized four W-CRMs in C . elegans , identifying a functionally important HMG-Helper pair in each one . Three of these were FF orientations of 0 , 1 & 2 spaces , while the fourth is an AK7 [78] . Furthermore , in a search for new C . elegans W-CRMs , 3 putative modules containing HMG and Helper clusters were chosen based on sequence conservation and individual site quality , however , only the module containing an optimal motif ( AK7 ) was bound by POP-1 in an in vitro binding assay [78] . These results suggest that the rules for POP-1 DNA binding share important similarities with TCF/Pan . In humans , an in vitro protocol for enriching preferred sequences flanking an HMG site for TCF1E reveals Helper-like motifs ( RCCG ) that are bound by the C-clamp [45] , [46] . This consensus is shorter than the Helper motif we identified in flies ( GCCGCCR ) [44] . However , the functional Helper sites identified in several W-CRMs that are activated by TCF1E in a colon cancer cell line share the consensus GCCGCY [46] , consistent with human Helper sites containing at least six nucleotides . In regard to HMG-Helper site spacing/orientation , the in vitro studies found preferred binding with either AK2-9 or FF0-11 configurations [46] . Systematic mutagenesis of Helper sites in the Sp5 W-CRM revealed three functional HMG-Helper pairs with configurations of AK7 , RW1 and FF1 , and other W-CRMs that were Helper site-dependent had predominately FF and AK configurations [46] . While analysis of additional W-CRMs in flies , worms , humans and other systems is required , the general rules for TCF-DNA recognition outlined in this report clearly provide a strong foundation for further studies . The high level of degeneracy in TCF binding sites [91] makes in silico detection of W-CRMs difficult . The use of evolutionary conversation can facilitate such searches , e . g . , the EEL algorithm [92] . We previously demonstrated that searching for clusters of HMG and Helper sites in the fly genome could identify W-CRMs that are directly activated by Wnt signaling in cell culture [44] . In this report , we incorporated the knowledge gained from analyzing the functional architecture of HMG-Helper site pairs to refine our computational searching . Our basic strategy employed searching the genome for high quality “optimal conformation” HMG-Helper pairs , followed by secondary searches for nearby lower quality pairs , which resulted in the identification of several novel W-CRMs . We utilized the aforementioned strategy to screen chromosome 3R for high quality FF1 pairs . This analysis revealed stretches containing multiple HMG-Helper pairs near the fkh and fd96C loci , which also possessed W-CRM activity in embryos and the ring gland ( Figure 8 , 9 ) . Our results indicate that searches biased for those HMG-Helper site configurations that are bound by TCF/Pan with highest affinity in vitro can successfully identify novel W-CRMs . Given our functional data that other “non-optimal” HMG-Helper pairs can also recruit TCF/Pan and promote Wnt-dependent transcription , often in tissue-specific ways ( Figure 4 , 5 ) , additional searches for these configurations should be a useful approach for W-CRM identification . For example , the mab-5 gene in C . elegans is a known target of Wnt signaling [93] , but a W-CRM in its regulatory DNA had not been identified [94] . Using our search protocol , we identified a FF7 pair 9 . 4 kB upstream of the mab-5 ATG , which was demonstrated by others to have W-CRM activity in mab-5 expressing cells [94] . Expression of this reporter was significantly reduced by mutation of the HMG site identified by our search [94] . These HMG and Helper sites are fairly divergent ( i . e . , TCTTTTGCCTC & GCCATAA ) which highlights another application of the results in our report: functional TCF sites that diverge from the consensus can still be identified if HMG-Helper site pairing is considered , as long as the amount of DNA to be searched is not too extensive ( e . g . , <12 kb ) . Computational searching for HMG-Helper pairs offers a complimentary approach to genome-wide surveying of TCF/Pan binding using ChIP-seq . While the region containing the fd96c W-CRM was identified as a TCF/Pan-bound region in fly embryos [28] , the 3R:24 . 4M W-CRM was not , highlighting the limitation of using one source of material for ChIP-seq analysis . On the other hand , while computational analysis of HMG-Helper pairs may help to prioritize which TCF/Pan ChIP-seq peaks might be functionally relevant , it is also likely that TCF/Pan is recruited to many W-CRMs by protein-protein interactions , given that HMG-Helper pair enrichment is markedly reduced in TCF/Pan-bound regions that are also occupied by other TFs ( Figure 6B , S5 ) . Despite our success with in silico identification of W-CRMs , our results indicate that connecting these W-CRMs with endogenous targets may not be straightforward . In the case of the W-CRM in the fd96C locus , part of its pattern is very similar to that of endogenous fd96Cb expression . However , the W-CRM reporter is also expressed in other parts of the embryo ( Figure 8 , S9 ) , possibly because the fd96C locus contains other inhibitory CRMs that refine gene expression , as has been found for other genes [95] . For the W-CRM found in the 3′ UTR of the fkh gene which is highly active in the PG ( Figure 9 ) , we found no evidence for endogenous Fkh expression in this tissue . Given that CRMs can act at great distances and pass over nearby promoters in Drosophila and vertebrates [96]–[99] , it is possible that this W-CRM regulates other gene ( s ) on chromosome 3R . Another benefit of in silico based discovery of W-CRMs is highlighted by our identification of the 3R:24 . 4M W-CRM , which is expressed in the PG cells of the ring gland ( Figure 9C , 9C′ , 9D ) . This endocrine organ is a master regulator of Drosophila molting behavior [100] , [101] , but had not been previously linked to Wnt signaling . Wg protein was detected on PG cells ( Figure 9B , S10 ) , and transient inhibition of Wg signaling in the PG results in reduced expression of the 3R:24 . 4M W-CRM reporter in third larval instar ( Figure 9 ) . Wg activity in this tissue is biologically important , because constitutive disruption of the Wg pathway results in developmental arrest during first larval instar , presumably due to the inability to molt . Interestingly , some synthetic HMG-Helper pairs ( e . g . , KK6 ) are highly active in the CA region of the ring gland and require Wg signaling for activity ( Figure 5 ) . Why the synthetic elements and the endogenous 3R:24 . 4M W-CRM are active in different cells of the ring gland is not clear . We are currently exploring the role of Wg signaling in ring gland biology and think it likely that computational searches for W-CRMs will uncover additional roles for the Wg pathway in other tissues . Synthetic HMG-Helper pairs were synthesized by Integrate DNA Technologies ( IDT; Coralville , IA ) and cloned into a modified pGL3-Basic vector ( Promega ) containing an hsp70 minimal promoter [32] for cell culture assays , or the pLacZattB vector [59] for transgenic fly generation , using BglII and XhoI restriction sites . The nkdIntE and nkdUPE2 reporter gene vectors were described previously [44] , [57] , and mutagenesis was carried out using the Stratagene QuickChange kit ( Agilent ) . For the fd96CMid and fkh3′UTR W-CRMs , the fragments were amplified using Roche High Fidelity enzyme , using w118 genomic DNA as the template , and cloned into TOPO TA ( Invitrogen ) as an intermediate before being moved into the pLacZattB vector , using the Acc65I and NotI sites . pAcArm* and parmLacZ have been described previously [32] , [44] , [57] . The protein expression vector for EMSA was generated by cloning the region encoding the HMG domain and the C-clamp into the XmaI and SacI restriction sites of the pET52b ( + ) vector ( Merck Millipore ) . Drosophila Kc167 cells were cultured in Schneider's Drosophila Medium ( Gibco ) supplemented with 10% Fetal Bovine Serum ( Gemini Bioscience ) . 250 ul of cells were seeded in 48 well plates , at a density of 1million cells/ml , and transient transfections were performed using Fugene transfection agent ( Roche ) . Each well received 20 ng luciferase reporter vector and 2 ng pArmLacZ . Wnt signaling was activated by transfection with 10 ng pAcArm* , ( a constitutively active Arm protein ) , and pAC5 . 1 EV was used as filler DNA to 100 ng total for each well . Cells were lysed and treated three days later using the Tropix Luc-screen kit ( Applied Biosciences ) and Luciferase and LacZ activity assayed using the Promega Glomax system . pArmLacZ was used to normalize for transfection efficiency . A His-tagged fragment of TCF/Pan containing both the HMG and C-Clamp domains was purified from E . coli strain BL21 following IPTG induction for 4 hours @ 37° using column purification on Nickel beads ( Invitrogen ) with Immidazole elution . LB growth media supplemented with 10 uM ZnCl . dsDNA probes were purchased from IDT and labeled probe was tagged with a 5′ 700 IR moiety on both strands . Competition assays were performed using the LI-COR Odyssey Infrared platform , and infrared intensity of the IR dye-labeled probe/protein complexes were calculated using Image Studio 2 . 0 . The IC50 values were calculated using Prism 6 for Mac OS X ( Graphpad Software , La Jolla California ) , as were the saturation binding curves . Three independent experiments were used to perform a least-squares non-linear fit . Binding reactions were performed as described in [44] , briefly , with 50 ug/ml poly ( dIdC ) . 0 . 05% NP40 , 50 mM MgCl2 and 3 . 5% glycerol in binding buffer ( 10 mM Tris-HCl , pH 7 . 5 , 50 mM KCl , 1 mM DTT ) . Each reaction , containing 6 pmol recombinant protein and 0–2 . 4 pmol competitor dsDNA ( dose indicated in figure 4A ) was incubated for 5 min on ice , 25 minutes at RT before 20 fmol IR-dye labeled probe was added and reactions were incubated for an additional 30 minutes . A complete list of the probes used can be found in Table S1 . Synthetic and endogenous W-CRMs were cloned into the pLacZattB vector [59] and injected by Rainbow Transgenics ( Camarillo , CA ) using a φ-C31 site directed integration strategy . All constructs were injected into line 24749 , integration site 86Fb . 1–3 individual lines were analyzed for each construct , and as expected , no variation in expression level or pattern was seen between lines . Candidate W-CRM constructs were recombined with UAS lines expressing a dominant negative TCF/Pan [58] or an armRNAi hairpin [102] and crossed to the appropriate GAL4 driver line using standard techniques . daGal4 [68] was used to drive expression in the embryonic epidermis , while the ring gland-specific driver phmGAL4 ( created by M . B . O'Connor ) was obtained from Michael Stern . The CA-specific driver Aug21Gal4 [103] was obtained from the Bloomington Stock center . Cuticle preparations were performed as previously described [71] . To detect β-galactosidase activity , third-instar larval discs were fixed in 1% gluteraldehyde ( in PBS ) , and incubated in staining solution ( 10 mM NaPO4 , 150 mM NaCl , 1 mM MgCl2 , 6 mM K4[FeII ( CN ) 6] , 6 mM K3[FeIII ( CN ) 6] , and 0 . 3% Triton X-100 , plus 2 mg/ml X-gal ) for 25 min at room temperature . After the reaction was stopped , discs were mounted in 70% glycerol . Images were taken on a Nikon Eclipse E600 upright microscope with Spot basic software and processed using Gimp v2 . 8 or Adobe Photoshop CS5 . 1 . Immunostaining was performed as described in [104] , using rabbit anti-LacZ ( MP biomedicals ) and mouse anti-Wg concentrate ( Developmental Studies Hybridoma Bank , University of Iowa ) . Embryos were collected for 24 hours before processing , and both antibodies used at a dilution factor of 1∶1200 . For the PG , larvae were collected at the third instar larval phase , and a 1∶600 dilution of each antibody was used . For all samples , CY3 ( Jackson Immunochemicals ) and Alexa 488 ( Molecular Probes ) conjugated secondary antibodies were used at a 1∶300 dilution . Affinity purified rabbit anti-Wingless antisera was used at a 1∶20 dilution . Images were taken on a Leica DM6000B confocal microscope and processed using Gimp v2 . 8 or Adobe Photoshop CS5 . 1 . 1–3 individual lines were analyzed for each construct , and representative images are shown . Normalized pixel intensity was calculated using Leica LAS software to measure pixel intensity in bounded nuclei . Mean LacZ fluorescent intensity for each nucleus was normalized to mean DAPI fluorescent intensity and Tukey box plots were generated using open source software ( http://boxplot . tyerslab . com/ ) . For in situ hybridizations , digoxigenin-labeled RNAprobes were designed to unique regions in fd96Ca and b ( see Table S1 for sequences ) and hybridizations were carried out following the protocol outlined in [105] . Training sequences for PWMs were taken from previously defined functional sites in W-CRMs depicted in Figure 1A . PWM scores were calculated using the formula: weighti , j = ln{[ ( ni , j+pi ) / ( N+1 ) ]/pi}∼ln ( fi , j/pi ) . The high confidence TCF/Pan bound regions [28] were searched for bipartite motifs and binned according to orientation and spacing using the dm3 genomic assembly in Matlab . To generate a random set of DNA sequences to analyze , an aggregate list of all sequences found in the 5′ , intergenic , intronic , and 3′ data sets was created . Each sequence from the set was assigned an index 1 through N , where N was the index of the last sequence in the aggregate set . A random ordering of all indices was then created and used to iterate over the data set , thus guaranteeing the same sequence could not be selected more than once . For each iteration , if a sequence contained a minimum size of 50 base pairs it was analyzed using the same processes as was used on the target data set . When the number of random sequence base pairs equaled or exceeded the number of base pairs in the target data set , the random data analysis was concluded . For each run of the random sequence analysis , the random number generator was seeded such that successive runs did not analyze the same fragments .
Regulation of gene expression is controlled in large part by proteins known as transcription factors , which bind to specific DNA sequences in the genome . The DNA binding domains of transcription factors recognize short stretches ( 5–11 base pairs ) of DNA with considerable sequence degeneracy . This means that a single DNA binding domain , on its own , cannot find its targets in the vast excess of genomic sequence . We are studying this question using TCF/Pangolin , a Drosophila transcription factor that mediates Wnt/β-catenin signaling , an important developmental cell-cell communication pathway . TCF/Pangolin contains two DNA binding domains that bind to a pair of DNA motifs known as HMG and Helper sites . We used a combination of biochemistry , genetics and bioinformatics to elucidate the spacing and orientation constraints of HMG-Helper site pairs . We found that HMG-Helper site spacing/orientation influenced the sensitivity of a target to Wnt signaling , as well as its tissue-responsiveness . We used this information to improve our ability to search the Drosophila genome for Wnt targets , one of which was activated by the pathway in the fly ring gland , the major endocrine organ in insects . Our work is relevant to related mammalian TCF family members , which are implicated in development , stem cell biology and the progression of cancer .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biochemistry", "signal", "transduction", "developmental", "biology", "model", "organisms", "cell", "biology", "nucleic", "acids", "genetics", "biology", "and", "life", "sciences", "molecular", "genetics", "wnt", "signaling", "cascade", "molecular", "cell", "biology", "cell", "signaling", "computational", "biology", "signaling", "cascades", "research", "and", "analysis", "methods" ]
2014
Bipartite Recognition of DNA by TCF/Pangolin Is Remarkably Flexible and Contributes to Transcriptional Responsiveness and Tissue Specificity of Wingless Signaling
Cohort studies , randomized trials , and post-licensure studies have reported reduced natural and vaccine-derived protection against rotavirus gastroenteritis ( RVGE ) in low- and middle-income countries . While susceptibility of children to rotavirus is known to vary within and between settings , implications for estimation of immune protection are not well understood . We sought to re-estimate naturally-acquired protection against rotavirus infection and RVGE , and to understand how differences in susceptibility among children impacted estimates . We re-analyzed data from studies conducted in Mexico City , Mexico and Vellore , India . Cumulatively , 573 rotavirus-unvaccinated children experienced 1418 rotavirus infections and 371 episodes of RVGE over 17 , 636 child-months . We developed a model that characterized susceptibility to rotavirus infection and RVGE among children , accounting for aspects of the natural history of rotavirus and differences in transmission rates between settings . We tested whether model-generated susceptibility measurements were associated with demographic and anthropometric factors , and with the severity of RVGE symptoms . We identified greater variation in susceptibility to rotavirus infection and RVGE in Vellore than in Mexico City . In both cohorts , susceptibility to rotavirus infection and RVGE were associated with male sex , lower birth weight , lower maternal education , and having fewer siblings; within Vellore , susceptibility was also associated with lower socioeconomic status . Children who were more susceptible to rotavirus also experienced higher rates of rotavirus-negative diarrhea , and higher risk of moderate-to-severe symptoms when experiencing RVGE . Simulations suggested that discrepant estimates of naturally-acquired immunity against RVGE can be attributed , in part , to between-setting differences in susceptibility of children , but result primarily from the interaction of transmission rates with age-dependent risk for infections to cause RVGE . We found that more children in Vellore than in Mexico City belong to a high-risk group for rotavirus infection and RVGE , and demonstrate that unmeasured individual- and age-dependent susceptibility may influence estimates of naturally-acquired immune protection against RVGE . Rotavirus is the leading source of gastrointestinal disease burden in children globally , with nearly 10 million severe cases and 193 , 000 fatalities estimated to occur annually [1] . One decade after their rollout in high-income settings , live oral rotavirus vaccines are currently being introduced to national immunization programs of low- and middle-income countries ( LMICs ) . However , randomized controlled trials and post-licensure studies have reported lower vaccine efficacy and effectiveness against rotavirus gastroenteritis ( RVGE ) in LMICs compared to higher-income settings [2 , 3] . Understanding this performance gap is essential to maximizing the impact of rotavirus vaccines where they are needed most . Recent observational studies have investigated how factors such as oral polio vaccine co-administration [4 , 5] , exposure to breast milk antibodies [6] , environmental enteropathy [7] , and nutritional status [8 , 9] influence susceptibility of children to RVGE and performance of oral vaccines . Variation in susceptibility among individuals within and between studies—due to these or other unmeasured risk factors—is well known to influence estimates of vaccine efficacy and effectiveness [10–13] . Differential removal of highly-susceptible individuals to a partially-immune state constitutes a form of frailty bias or effect modification that may persist even in randomized studies [10 , 14 , 15]; we use the term bias here in reference to discrepancies between common measures of association , such as hazard ratios and risk ratios , and the per-exposure biological effect of immunity ( from vaccination or natural infection ) on infection and/or disease endpoints [16 , 17] . Demonstrations of the impact of variation in susceptibility have arisen in both experimental and theoretical studies [18 , 19] . Refinements in our ability to characterize such variation both statistically and experimentally [20–27] , together with formalizations of per-exposure measures of intervention efficacy in trials [28–30] and observational studies [16 , 17] , have highlighted the potential for heterogeneity in susceptibility to influence epidemiologic measurements . While the possibility of such frailty bias in rotavirus vaccine studies has been raised [15 , 31 , 32] , distinguishing its contribution to variation in estimates of vaccine protection against RVGE has been difficult given the concordance of observed patterns with multiple hypotheses [33] . Importantly , the rate of asymptomatic infections and the distribution of risk factors across settings are not easily measured or compared [34] , and individual variation in susceptibility may be only partially attributable to known or measured risk factors . Similarly-designed birth cohort studies undertaken in socioeconomically-distinct LMIC populations of Mexico City , Mexico and Vellore , India provide an opportunity to characterize heterogeneity in susceptibility to rotavirus infection and RVGE , and to assess its influence on estimates of immune protection [35 , 36] . While the two studies supplied similar estimates of naturally-acquired immune protection against re-infection , differences in estimates of protection against RVGE reflected discrepancies in estimated vaccine efficacy between Latin America and South Asia [37–39] . Whereas no children in Mexico City experienced moderate-to-severe RVGE after two or more previous infections , two previous infections were associated with only 57% protection against moderate-to-severe RVGE among children in Vellore [35 , 36] . Paired re-analysis of the studies has provided evidence that differences owe , in part , to the influence of a subset of “high-risk” individuals in the Vellore cohort—who experienced high rates of rotavirus infection as well as high risk for RVGE given infection—and age-dependent risk for RVGE given infection [33] . We revisited data from these studies aiming to better understand and compare the distribution of susceptibility among individuals within the two cohorts , and to explore the implications for epidemiologic analyses . We developed a model to estimate susceptibility of children to rotavirus infection and RVGE , accounting for the natural history of rotavirus and differences between settings in transmission intensity . We conducted statistical inference via kernel-based and Markov chain Monte Carlo inference approaches , recovering near-identical parameter estimates under the two strategies . We used our findings to explore the influence of sources of bias underlying conventional measures of protective immunity . Incidence of rotavirus infection and RVGE among children enrolled in the two cohorts has been described previously [33 , 35 , 36 , 40] . Briefly , the studies enrolled 200 and 373 unvaccinated Mexican and Indian children who were followed from birth to up to 2 years and 3 years of age , respectively , yielding 3699 and 13 , 937 child-months of follow-up , and characterized the spectrum of asymptomatic to severe clinical manifestations of each rotavirus infection . In total , 315 rotavirus infections were detected in Mexico City and 1103 were detected in Vellore , with 89 ( 28% of 315 infections ) and 282 ( 26% of 1103 infections ) episodes of RVGE occurring in the two settings , respectively . Incidence was higher in Vellore , such that first infections occurred in 56% and 81% of Indian children by ages 6 months and one year , compared to 34% and 67% of Mexican children , respectively ( Fig 1A and 1B ) . The proportion of infections causing RVGE declined with a higher number of previous infections ( Fig 1C and 1D ) . However , analyses stratified by age and previous infection revealed this trend could owe to confounding by age , i . e . declining RVGE risk with older age for each of first , second , and later infections ( Fig 1E and 1F ) . At matched ages , RVGE was more common , paradoxically , during second and later infections than first infections in Vellore . In contrast , this trend was not apparent in Mexico City . We developed a set of model structures addressing biological hypotheses of rotavirus natural history , based on previous studies of transmission dynamics [41–43] and secondary analysis of the birth-cohort datasets [33] . We estimated the proportion of each cohort belonging to a “high-risk” group , and tested for evidence of variation in susceptibility to infection and/or risk of RVGE given infection among the high-risk group compared to the rest of the cohort ( see Materials and Methods ) . We also tested whether the risk of RVGE given infection varied depending on age at time of infection , and/or the number of previous infections . We estimated 33% ( 95% CI: 23% to 41% ) , 50% ( 42% to 57% ) , and 64% ( 55% to 70% ) reductions in the rates at which children re-acquired rotavirus after one , two , or three or more previous infections ( Table 1 ) , closely recapitulating estimated protection against re-infection in the original studies ( S2 Table ) [35 , 36] . Our models also captured declining risk for infections to cause symptomatic RVGE at older ages ( Fig 1B ) . The proportion of secondary and subsequent infections causing RVGE in the first year of life in Vellore closely matched expectations among children classified as a “high-risk” subset of the population ( detailed below; Fig 1F ) . We compared the fit of models with differing assumptions about acquired immune protection against RVGE given infection ( Table 1 ) . After accounting for declining risk of RVGE given infection at older ages , we did not identify improvements in fit ( based on values of the Akaike Information Criterion [44] ) when allowing for acquired immune protection against symptoms during second or later infections ( Model 2 ) . Several salient differences between the two studies were reproduced in model-based predictions . Although we predicted higher-than-observed rates of infection in Mexico City during the first six months of life , predictions accurately reflected between-setting differences in cumulative incidence by the end of the first year ( Fig 1A and 1B ) . In addition , fitted parameters recapitulated the observation of significantly lower probabilities of RVGE during second , third , and fourth infections in Mexico City as compared to Vellore ( Fig 1C and 1D ) , despite predicting RVGE in a higher-than-observed proportion of second infections in Mexico City . Our modeling framework partitioned the cohort populations across distinct risk groups ( R and RC ) with prevalences αM and 1–αM , respectively , in Mexico City , and αV and 1–αV in Vellore . Because the size of the risk group and group-specific relative risk for infection and/or disease outcomes are inversely related , the relative susceptibility and prevalence of these two risk groups were not simultaneously identifiable . We therefore estimated conditional between-group differences in susceptibility to infection ( hazard ratio ϕ ) and RVGE given infection ( relative risk ρ ) associated with particular values of αM and αV . We reconstructed the full distribution of ϕ and ρ from the marginal distributions of {ϕ , ρ}|{αM , αV} ( see Materials and Methods ) . Fitting a more complex model ( S1 Text ) which considered an exhaustive set of risk groups—including children with modified susceptibility to infection only or disease only—allowed us to verify the hypothesis of a linkage between children’s susceptibility to infection and disease given infection , which was suggested in previous analyses of the cohort data [33] . This modeling approach enabled us to compare the prevalence of children with particular susceptibility levels between cohorts ( Fig 2 ) . We estimated that 3% ( 1% to 23% ) of children in Mexico City would belong to a high-risk-stratum experiencing a ≥50% higher-than-baseline rate of acquiring rotavirus infection , compared to 13% ( 6% to 29% ) of children in Vellore ( Fig 2G ) . A subgroup with over double the baseline rate of infection would include 2% ( 1% to 8% ) of children in Mexico City and 10% ( 5% to 18% ) of children in Vellore , while only 1% ( 0% to 2% ) of children in Mexico City and 6% ( 5% to 9% ) of children in Vellore would belong to a subgroup experiencing rates of infection ≥3-fold higher than the baseline rate . Greater susceptibility to infection was associated with higher risk of experiencing RVGE given infection , regardless of the prevalence of the high-risk group ( Fig 2F ) ; fitting both ϕ and ρ , we identified ≥99 . 99% probability for excess risk of disease given infection within the sub-cohorts defined to have higher rates of acquiring infection ( S1 Table ) . Joint distributions of ϕ and ρ with the size of the risk groups were indistinguishable under the original model specification and a more complex model that allowed either linked or unlinked susceptibility to infection and disease ( S1 Text , S2 Fig ) . Our modeling approach provided a statistical basis for calculating the probability that each child belonged to the “high-risk” subgroup ( see Materials and Methods ) . To examine the validity of these estimates , we next assessed whether a child’s estimated risk of belonging to the “high-risk” subgroup was related to host factors and exposures measured in the original studies that have previously been reported to predict risk for rotavirus infection and RVGE ( Tables 2 and 3 ) . Male children were 26% ( 4% to 67% ) more likely to be among the “high-risk” subgroup than female children ( Table 3 ) . Birth weight was also a predictor of being in the “high-risk” subgroup , with each log-kilogram decrease in birth weight conferring 2 . 05 ( 1 . 02 to 5 . 03 ) -fold higher probability of belonging to the “high-risk” subgroup . However , we did not detect a significant association between susceptibility and weight at 12 months . In each cohort as well as in the pooled analysis , children without siblings were more likely to belong to the “high-risk” subgroup than children with siblings . In comparison to children whose mothers had completed <5 years of education , children whose mothers had completed ≥10 years of education were 25% ( 0% to 50% ) less likely to belong to the “high-risk” subgroup . We also identified several factors predicting within-cohort variation in susceptibility that were consistent with findings in primary analyses of the studies [35 , 36] . In Vellore , children whose household members were involved in producing bidis ( indigenous cigarettes ) —an indicator of lower household socioeconomic status—were 45% ( 10% to 122% ) more likely than other children to belong to the “high-risk” subgroup . In Mexico City , children with a shorter duration of breastfeeding were more likely to belong to the “high-risk” subgroup , although this association did not reach conventional thresholds of statistical significance in our analysis . Among children experiencing RVGE in the cohorts , those who experienced moderate-to-severe RVGE symptoms ( defined by a Vesikari score ≥11 ) on at least one episode were 44% ( 13% to 122% ) more likely to belong to the “high-risk” subgroup , suggesting model-based measures of susceptibility to rotavirus infection and ( any ) RVGE given infection also predicted the severity of rotavirus disease . In addition , children who experienced higher rates of diarrheal episodes caused by pathogens other than rotavirus were more likely to belong to the “high-risk” subgroup within each cohort . In Vellore , we also found a positive association between the incidence of acute respiratory infections and the likelihood that a child belonged to the “high-risk” subgroup; this information was not available for the Mexico City cohort . We next conducted simulation studies ( Fig 3 ) to assess how variation in transmission intensity and in the susceptibility of children could influence estimates of naturally-acquired immune protection against rotavirus infection , RVGE , and RVGE given infection [45]—as measured by the hazard ratios of infection and RVGE , and relative risk of RVGE given infection—following one , two , or three previous infections , compared to zero previous infections . We compared estimates from in silico cohorts with differing prevalence of “high-risk” children ( α ) exposed to varying forces of infection ( Λ ) . We accounted for susceptibility differences between risk groups by sampling from the joint , unconditional distribution of {ϕ , ρ} , thereby isolating the effect of differences in risk-group prevalence . We did not identify a large of impact of susceptibility differences on estimates of protection against reinfection ( i . e . estimates of NE^ were similar across different levels of Λ and α ) , which may help to explain why these estimates were nearly equal in the original studies [35 , 36] . However , we found that estimates of protection against RVGE—which were lower in primary analyses of the Vellore cohort—were expected to decline in settings with higher transmission intensity , reflecting acquisition of infection at younger , higher-risk ages . The impacts of heterogeneity in susceptibility were outweighed by the impacts of unaccounted-for age-dependent symptom risk . For a population exposed to transmission intensity on the order of one rotavirus infection per susceptible child-year at risk , increasing the prevalence of the “high-risk” subgroup ( α ) from 0% 50% reduced the estimate of protection against RVGE conferred by one previous infection by 9% ( –12% to 27% ) , in absolute terms . Increasing transmission intensity to the equivalent of four infections per susceptible child-year at risk led to a reduction of 14% ( –8% to 34% ) at α = 0 and , similarly , of 12% ( –6% to 27% ) at α = 0 . 5 , in absolute terms . Evidence of naturally-acquired immunity against rotavirus from birth-cohort studies provided an impetus toward the development of live oral rotavirus vaccines , which are now among the most effective strategies for the prevention of severe illness and deaths due to RVGE globally [46] . However , challenges have persisted in understanding and addressing the lower protective efficacy of rotavirus vaccines in high-burden LMIC settings , which mirrors protection derived from naturally-acquired immunity [47 , 48] . Our analysis suggests that discrepant estimates of protection may in part reflect epidemiological bias , attributable to differences between settings in transmission intensity and differential susceptibility of children to rotavirus infection and RVGE , individually and by age . Lower estimates of protection in settings with high rotavirus burden thus reflect factors other than weaker immunity among children in LMICs . Accounting for aspects of the natural history of rotavirus enabled us to directly compare the susceptibility of children enrolled in birth cohort studies undertaken in socioeconomically-distinct settings . Although we estimated only modestly higher susceptibility for the average child in Vellore as compared to Mexico City , individual variation in susceptibility was considerably greater within the Vellore cohort . We estimated that a higher proportion of children in Vellore , as compared to Mexico City , showed elevated rates of rotavirus infection as well as excess risk for RVGE given infection . This finding can account for several unexpected features of the epidemiology of rotavirus in Vellore . The increasing probability of RVGE in association with first , second , and later infections occurring at matched ages that we identified , particularly in Vellore ( Fig 1F ) , reflects high risk for RVGE given infection among individuals susceptible to frequent rotavirus infection . In other words , children who experienced two or more infections before 6 months of age , or three or more infections before 12 months of age , are more likely to belong to a subgroup with pronounced susceptibility to rotavirus infection and disease , given infection . Indeed , our analysis identified that susceptibility to rotavirus infection was positively associated with susceptibility to RVGE given infection among individual children ( S1 Table , S2 Fig ) . While the proportion of children belonging to a “high-risk” subgroup constituted a source of epidemiologic bias in simulation studies , and was expected to lead to estimates of weaker protection against RVGE in settings with higher transmission intensity such as Vellore , the degree of bias imposed was not large . Several other studies have recently addressed transmission-dynamic factors that may contribute to the apparent underperformance of rotavirus vaccination in high-transmission settings [32] . Using data from the PROVIDE trial of monovalent rotavirus vaccine in Bangladesh , Rogawski and colleagues demonstrated that acquisition of naturally-acquired immunity may contribute to lower estimates of vaccine efficacy due to earlier and more frequent infection within the control arm; impacts on estimates of protection are most notable in high-transmission settings , and among children in their second year of life [15] . Here we were able to account for the contribution of all previous infections to naturally-acquired immunity , including subclinical infections , and to account for age-specific RVGE risk . Selection bias resulting from variation in individual susceptibility can result in further downward bias [31] , underscoring the need for per-exposure estimates of immune effectiveness such as we have sought in this analysis . Directly comparing susceptibility between populations or settings is difficult because determinants of susceptibility are often unknown or unmeasured , and may be imperfectly characterized by measurable epidemiological risk factors . The contributions of susceptibility and transmission intensity to disease incidence rates are not easily disentangled . Our analysis employed a novel approach to characterize susceptibility of children in two cohorts based on a model that included known aspects of rotavirus natural history , facilitated by access to similar measurements from settings with distinct risk profiles and force of infection . Our estimates of susceptibility appear externally valid based on their association with previously-reported risk factors for RVGE [49–52]: male children , children with lower birth weight , and children whose mothers had lower educational attainment were more likely to belong to a higher-risk subset of the population in our analysis . In Vellore , children whose households were involved in bidi work—a marker for lower socioeconomic status—were also at higher risk [36] , while in Mexico City , we observed a trend toward lower risk associated with longer breastfeeding , consistent with previous studies [53 , 54] . In addition , we observed higher incidence of diarrhea caused by pathogens other than rotavirus among children who were found to have greater susceptibility to rotavirus . This observation may signify the presence of environmental enteric dysfunction within the cohorts , or other sources of variation in immune status or pathogen exposure . In Vellore , children who we estimated were more susceptible to rotavirus also experienced higher incidence of respiratory infections , as reported previously [36] . While the associations we identify ( in particular with time- or age-specific risk factors ) do not measure causal effects in either direction , our inferences pertaining to within-cohort susceptibility are supported by the fact that children classified by the model as having “high risk” exhibit risk factors widely believed to be associated with rotavirus infection and RVGE . These and other host factors associated with susceptibility to rotavirus infection and RVGE have also been reported to predict weaker immune responses to live enteric vaccines such as those against rotavirus . While our model does not address variation in the strength of immune responses among individuals or across settings , 58% of Indian children versus 90% of Mexican children seroconverted after Rotarix immunization in previous studies [47 , 55] . Nonetheless , near-equal naturally-acquired protection against re-infection was noted among children in the birth cohort studies in Vellore and Mexico City . Our findings demonstrate that some degree of the reported variation in protection against RVGE can be attributed to epidemiological biases resulting from differential transmission intensity and differential susceptibility of children , although we found age-dependent diarrhea risk was a more important contributor to variation in estimates . The finding that older age diminishes risk for children to experience RVGE given rotavirus infection has been suggested in previous analyses of the cohort datasets [33] . Our simulation study demonstrates that such age-related symptom risk enhances protection against RVGE in low-transmission settings . Deferring infections to later ages significantly reduces the risk for children to experience symptoms upon reinfection . While the mechanisms underlying age-dependent diarrhea risk are not precisely known , the observation has been reported in mouse , rat , rabbit , and gnotobiotic piglet models of rotavirus infection [56–59] . Age-dependent TLR3 expression and host responses to rotavirus enterotoxins contribute to this observation in mice [60 , 61] . Other aspects of immune maturation , intestinal development , and the establishment of gut microbial communities may further drive associations between age and diarrhea risk in both humans and animals [62] . Furthermore , the greater dehydrating effect of diarrhea in younger children with smaller body volumes may contribute to severity—and thus the reporting and diagnosis—of RVGE in early-life infections [63] . There are several limitations to our analysis . Whereas we assume exponentially-distributed infection times ( consistent with a constant hazard of infection ) , this provides an imperfect fit to the timing of early-life infections , particularly in the Mexico City cohort . The departure between predictions and observations may reflect the protective effect of maternal antibodies , as reported previously [35 , 64] , or the influence of age-specific social mixing patterns on transmission [65] . Thus , our model tended to overestimate the probability of RVGE associated with second rotavirus infections in Mexico City , although this discrepancy was not sustained for third and fourth infections . Our analyses also do not distinguish between homotypic and heterotypic protection because we lack genotype data for serologically-detected infections , which constitute the majority of infections in both cohorts . Although moderate-to-severe RVGE episodes are the primary endpoint of most studies evaluating vaccine efficacy and effectiveness , our analysis addressed RVGE episodes of any severity . Only 7% of children in Mexico City experienced RVGE episodes with Vesikari score ≥11 , limiting the statistical power for analyses of moderate-to-severe RVGE . Nonetheless , previous analyses of the studies identified similar risk factors for mild and moderate-to-severe RVGE [33]; moreover , we find that children identified by our method to face higher risk for rotavirus infection and RVGE likewise experienced higher risk for moderate-to-severe manifestations of RVGE episodes . Thus , our findings may inform the interpretation of studies with moderate-to-severe RVGE endpoints . Our ability to account for variation in susceptibility to infection as well as disease , and indeed to identify a linkage between these traits , is a unique advantage afforded by data describing both clinically-apparent and subclinical infections . While methods exist to account for frailty in time-to-event data [10 , 66] , as may be present in studies with only one class of endpoints ( such as serological studies of infection or clinical trials with disease endpoints ) , susceptibility to disease given infection is also of interest . Importantly , our findings suggest that age , rather than naturally-acquired immunity , determines risk for rotavirus infections to present symptomatically , together with individual-level susceptibility factors . Adaptations of our model to the natural history of other pathogens may facilitate similar studies in other disease-specific contexts . Whereas other models have used continuous distributions to characterize individual susceptibility , this approach has generally relied on the ability to measure or even manipulate exposure intensity at the individual level , for instance by measuring infectious contacts or through controlled-dose challenge experiments [20–30] . As our data presented the opportunity to compare exposure intensity between cohorts but not between individuals , we considered a simpler case of dichotomous risk groups within cohorts , and determined how the sizes of cohort-specific risk strata ( α ) were jointly distributed with the degree of risk elevation ( ϕ , ρ ) . A priori knowledge of risk strata , for instance based on previous estimates of covariate effect sizes , presents an alternative strategy to infer distributions of individual-level susceptibility [67] . Birth-cohort studies have been instrumental to our understanding of the natural history of rotavirus . Uncertainties surrounding differences in the epidemiology of rotavirus in socioeconomically-distinct populations underscore the need for a theoretical basis for comparing outcomes of individual studies . Our approach permitted assessment of how age , acquired immunity , and variation in individual susceptibility independently contributed to infection and disease risk in distinct birth cohorts , helping to resolve discrepancies in estimated protection that arose in primary analyses of the datasets . The modeling framework we introduce here may thus have applicability to studies of other partially-immunizing pathogens . The two birth cohort studies followed similar protocols that have been described previously [35 , 36] . Children were enrolled at birth and followed to 24 and 36 months of age in Mexico City and Vellore , respectively . The studies aimed to detect all rotavirus infections , both symptomatic and asymptomatic . Rotavirus infections were detected by three approaches: ( 1 ) sera were drawn every 4 and 6 months in Mexico City and Vellore , respectively , and tested for IgA or IgG titer increases; ( 2 ) asymptomatic stool samples were collected weekly in Mexico City and every two weeks in Vellore and tested for rotavirus; and ( 3 ) diarrheal stools were collected by field workers every time mothers alerted the study teams of any change in a child’s stool pattern ( S2 Table ) . Virus detection was performed by ELISA in Mexico City and by ELISA or real-time PCR in Vellore . In Mexico City , 200 children were recruited and retained for 77% of the scheduled follow-up period , while our analysis of the Vellore dataset included the 373 children ( 83% of 452 enrolled ) who completed follow-up . Data were available for 96% ( 1037/1080 ) and 99% ( 2565/2598 ) of scheduled serum tests; 97% ( 15 , 503/16 , 029 ) and 93% ( 26 , 902/28 , 906 ) of scheduled asymptomatic stool tests; and 85% ( 963/1133 ) and 99% ( 1829/1856 ) of reported diarrheal episodes in Mexico City and Vellore , respectively . To better understand variation in susceptibility among children within each cohort , we evaluated associations between individual-level factors ( Table 2 ) and the probability for each child to belong to the high-risk ( R ) subgroup . For each of 10 , 000 draws of θ , we measured the probability of belonging to the high-risk group , equal to P ( R|Yi , s ) for ρ>1 or 1−P ( R|Yi , s ) for ρ<1 , for each child ( in all samples , we identified ϕ>1 for ρ>1 and ϕ<1 for ρ<1 ) . We used least-squares regression to test for associations between covariates and children’s log-transformed probability of being in the high-risk group , using estimated regression parameters to measure relative risks ( Table 3 ) . Models included a setting term to account for differential prevalence of high-risk children . We pooled relative risk estimates across our draws of θ to recover their distribution . To examine potential bias in conventional estimates of naturally-acquired immune protection , we used our model of the natural history of rotavirus infection to simulate individual histories of infection and RVGE over the first three years of life , sampling from estimated parameters describing the effects of age ( β0 , β1 , β2 ) and previous infection ( ψ1 , ψ2 , ψ3 ) on susceptibility to RVGE and infection , respectively . We conducted simulations under an external force of infection ( Λ ) ranging from 0 . 2 to 4 infections per year , assigning 0% to 50% ( α ) of children to the high-risk subgroup R; values of ϕ and ρ were drawn independently of α so that we could determine the effect of differences in the proportion of high-risk children on estimates of protection . We sampled exponentially-distributed infection times ( calculated from time of birth or previous infection ) , and defined the occurrence of RVGE for each individual infection as a Bernoulli random variable using the model-predicted probability of RVGE given infection . For each cohort simulation , we measured the hazard ratio for reinfection and RVGE from the incidence rate ( IRk ) of infection and RVGE after one , two , or three previous infections , relative to the IR0 from birth . We also measured the relative risk of RVGE given reinfection among children who had experienced one , two , or three previous infections , relative to those with no previous infections , calculated from the proportion ( pk ) of infections with RVGE . We defined estimates of natural immune efficacy ( NE^ ) as NE^k=1−IRkIR0 ( 11 ) for protection against infection and RVGE among children who had experienced k previous infections , and NE^k=1−pkp0 ( 12 ) for risk of RVGE given infection among children who had experienced k previous infections .
Differences in susceptibility can help explain why some individuals , and not others , acquire infection and exhibit symptoms when exposed to infectious disease agents . However , it is difficult to distinguish between differences in susceptibility versus exposure in epidemiological studies . We developed a modeling approach to distinguish transmission intensity and susceptibility in data from cohort studies of rotavirus infection among children in Mexico City , Mexico , and Vellore , India , and evaluated how these factors may have contributed to differences in estimates of naturally-acquired immune protection between the studies . Given the same exposure , more children were at high risk of acquiring rotavirus infection , and of experiencing gastroenteritis when infected , in Vellore than in Mexico City . The probability of belonging to this high-risk stratum was associated with well-known individual factors such as lower socioeconomic status , lower birth weight , and incidence of diarrhea due to other causes . We also found the risk for rotavirus infections to cause symptoms declined with age , independent of acquired immunity . These findings can , in part , account for estimates of lower protective efficacy of acquired immunity against rotavirus gastroenteritis in high-incidence settings , mirroring estimates of reduced effectiveness of live oral rotavirus vaccines in low- and middle-income countries .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "children", "medicine", "and", "health", "sciences", "respiratory", "infections", "pathology", "and", "laboratory", "medicine", "geographical", "locations", "pulmonology", "north", "america", "diarrhea", "age", "groups", "vaccines", "research", "design", "signs", "and", "symptoms", "gastroenterology", "and", "hepatology", "cohort", "studies", "infectious", "disease", "control", "families", "research", "and", "analysis", "methods", "infectious", "diseases", "epidemiology", "rotavirus", "infection", "people", "and", "places", "diagnostic", "medicine", "population", "groupings", "natural", "history", "of", "disease", "viral", "diseases", "mexico" ]
2019
Heterogeneous susceptibility to rotavirus infection and gastroenteritis in two birth cohort studies: Parameter estimation and epidemiological implications
Wolbachia are required for filarial nematode survival and fertility and contribute to the immune responses associated with human filarial diseases . Here we developed whole-mount immunofluorescence techniques to characterize Wolbachia somatic and germline transmission patterns and tissue distribution in Brugia malayi , a nematode responsible for lymphatic filariasis . In the initial embryonic divisions , Wolbachia segregate asymmetrically such that they occupy only a small subset of cells in the developing embryo , facilitating their concentration in the adult hypodermal chords and female germline . Wolbachia are not found in male reproductive tissues and the absence of Wolbachia from embryonic germline precursors in half of the embryos indicates Wolbachia loss from the male germline may occur in early embryogenesis . Wolbachia rely on fusion of hypodermal cells to populate adult chords . Finally , we detect Wolbachia in the secretory canal lumen suggesting living worms may release bacteria and/or their products into their host . Filarial nematodes are the causative agents of human filariasis , affecting over 150 million individuals . The most pathogenic diseases , lymphatic filariasis and onchocerciasis , ( river blindness ) comprise a major cause of global morbidity in the tropics , with over 1 billion people at risk of these arthropod-transmitted infections [1] , [2] . Three filarial nematode species are responsible for lymphatic filariasis: Wuchereria bancrofti , Brugia malayi and Brugia timori , causing pathologies that include hydrocoele and lymphoedema ( elephantiasis ) . Onchocerciasis is caused by Onchocerca volvulus , leading to skin disease , “onchocercoma nodules” and visual impairment , including blindness . These parasitic nematodes rely on alpha-proteobacterial Wolbachia endosymbionts for development , viability and fertility ( for reviews see , [3] , [4] ) . This obligate dependence was first discovered using anti-Rickettsial tetracycline antibiotics , in in vitro and in vivo model systems . Treatments deplete Wolbachia , resulting in embryonic arrest and a decrease in microfilarial ( larval ) production [4] . Human trials with doxycycline or rifampicin provide evidence for long-term sterilization and macrofilaricidal ( adulticidal ) effects against both lymphatic filariasis and onchocerciasis [5]–[8] . Wolbachia play a significant role in the pathogenesis of filarial disease [9]–[14] . Wolbachia activate inflammatory immune responses , including antibody responses and induction of corneal keratitis in the case of O . volvulus infection , and are implicated in the inflammation response leading to blindness , induced by release of Wolbachia antigens from degenerating microfilariae [3] . In lymphatic filariasis , the major pathologies are attributable to death and destruction of adult worms within the lymphatic vessels and activation of innate inflammation; effects which are lost following antibiotic depletion of bacteria and absent from soluble extracts derived from filarial species naturally lacking Wolbachia such as Acanthocheilonema viteae [4] . To better understand the endosymbiont interaction with the parasitic nematode , it is of primary importance to characterize Wolbachia localization at the host tissue and cellular levels . The histology of the parasitic nematode B . malayi was established more than half a century ago by differential contrast microscopy ( DIC ) on whole mount adult specimens [15] . Subsequent DIC and electron microscopy studies carried out on cross sections revealed the presence of intracellular bacteria [16]–[20] which were only “re-discovered” and identified as Wolbachia decades later by phylogenetic analysis and genomic studies [21] , [22] . Wolbachia are present primarily in the lateral hypodermal chords of both adult males and females and in the ovaries , oocytes and embryonic stages within the uteri of females . The absence of Wolbachia in the male reproductive system indicates that the bacterium is vertically transmitted through the cytoplasm of the egg and not through the sperm [19] , [23] . Although Wolbachia are observed in all stages of the host life-cycle , there are significant variations in bacterial growth kinetics in host development [24] , . Bacterial numbers remain constant in microfilariae ( mf ) and the mosquito-borne larval stages ( L2 and L3 ) , but the Wolbachia multiply rapidly beginning within the first week of infection of the mammalian host . Features of the symbiotic relationship left unresolved include the localization and segregation patterns of Wolbachia during embryogenesis , which are essential to understanding the specific localization in adult somatic tissue and the germline . To address this issue , we developed fixation , immunofluorescent staining and imaging protocols to characterize Wolbachia in whole-mount B . malayi embryos and adult specimens at the tissue , cellular and sub-cellular levels . These studies demonstrate that Wolbachia localize to the posterior of the egg upon fertilization and segregate asymmetrically during early embryogenesis , in a lineage-specific manner , resulting in only a small fraction of the cells in the developing embryo containing the endobacteria . Specifically , Wolbachia concentrate in the C blastomere hypodermal descendants , and in the P blastomere germline precursors . The asymmetric and lineage-specific segregation of Wolbachia during the initial stages of embryogenesis resembles that of some Caenorhabditis elegans polarity and lineage-specific determinants , and suggests that Wolbachia may interact with the counterparts of these determinants in B . malayi . This transmission pattern readily explains the tissue specific pattern of Wolbachia localization in the adult hypodermal lateral chords and female germline . The absence of the bacteria from the embryonic germ line precursors in nearly half of the embryos suggest Wolbachia loss from the male germline may occur during embryogenesis . We find that Wolbachia rely on fusion of hypodermal cells to populate young adult chords . We also detected Wolbachia in the lumen of the secretory-excretory canals embedded in the hypodermal lateral chords , suggesting that in addition to dead or degenerating parasites , live adult worms may also release bacteria and/or their products through this route into the host tissues . Living B . malayi adult male and female worms were supplied by TRS Laboratories ( Athens Georgia ) . The worms were raised in jirds and the procedures described below were performed approximately 1 to 3 days after their removal . To prepare worms for whole mount immuno-fluorescence analysis , they were soaked in M9 buffer ( see Buffers in Supplementary Experimental Procedures ) for 30 seconds to allow them to uncoil and immediately placed in liquid nitrogen . M9 was then removed and replaced with ( PBS+ Paraformaldehyde ( PFA ) 4% final- ( Electron Microscopy Sciences ) ) 1/3+2/3 Heptane on a rotator for 30 minutes at room temperature . If required , worms were cut or open with a blade to expose the different tissues to antibodies prior to fixation . All fixation and immunostaining steps gave better results in eppendorf tubes in rotation compared to whole mount animals on slides . For propidium iodide ( PI ) ( Molecular Probes ) DNA staining , worms were incubated overnight at room temperature in PBS + RNAse A ( 15 mg/mL , Sigma ) , in rotating tubes followed by PI incubation ( 1 . 0 mg/mL solution ) for 20 minutes in PBS ( 1∶50 ) and a 5 minute wash . For DAPI DNA staining alone , fixed worms were simply pulled out of the tube with a curved needle , placed on a glass slide with thin needles in a line of PBS . The PBS was then aspirated and worms mounted into Vectashield with DAPI ( Vector Laboratories ) and left at 4 degrees overnight: DAPI penetrates all tissues and stains Wolbachia very well . To prepare embryos for whole-mount immuno-fluorescent analysis , females were cut into sections with a blade on a glass slide . The sections were collected and the slide rinsed with PBS and collected in an 0 . 5mL eppendorf tube . PFA and heptane were added as described above . The tube was vortexed for one minute at this step . After fixation for 10 to 20 minutes , embryos were immersed in ( 1/4 water , 1/4 KOH 10M , 1/2 NaClO 15% ) for 30 seconds to facilitate removal of the eggshell ( optional ) , centrifuged , and rinsed in PBST . Prior to each change of solution or rinse , samples were centrifuged for 1 min at 4 , 200 rpm . This procedure yielded hundreds of embryos per female , and allowed staining of at least half of them . As an alternative procedure we used the freeze crack techniques that work with C . elegans embryos but these gave unsatisfactory results , likely due to the smaller size of the Brugia embryos . For protocols used to determine the identity of specific embryonic blastomeres and conditions for primary and secondary antibody incubations see Methods S1 . For live fluorescent analysis of Wolbachia and host nuclei , adult worms were incubated in RPMI medium with 1/10 , 000 Syto11 ( Invitrogen ) or vital Hoechst for 30 minutes , and observed as for C . elegans on an 2% agarose pad with Sodium Azide 25mM between slide and coverslip ( http://www . wormbook . org/chapters/www_intromethodscellbiology/intromethodscellbiology . html ) . To observe the Secretory-Excretory canal , we added 50µL of Resorufin ( Sigma ) at 10 µg/mL , 1/10 , 000 Syto11 for approximately 30 minutes to an hour , and washed the worms in RPMI for 15 minutes . Worms were mounted in PBS and anesthetized with Sodium Azide . Confocal microscope images were captured on an inverted photoscope ( DMIRB; Leitz ) equipped with a laser confocal imaging system ( TCS SP2; Leica ) using an HCX PL APO 1 . 4 NA 63 oil objective ( Leica ) at room temperature . Images in epifluorescence were captured on a Leica DMI 6000B microscope and a Zeiss Axioscope 2 plus microscope . The fertilization and embryogenesis of B . malayi resemble that of other secernentean nematodes . The sperm entry activates the oocyte to complete meiosis I and II and defines the posterior pole of the egg [26] , [27] . All examined species of secernentean nematodes undergo asymmetric cleavage leading to early separation of soma and germ line , and establishment of five somatic cell lineages [28]– . This is followed by a developmental phase during which organ identity is specified . Subsequent morphogenetic events such as ventral closure and an elongation phase due to contraction of circumferential actin bundles in the hypodermis lead to newly hatched larvae appearing very similar among nematodes species . It has been shown that despite this high similarity in the anatomy of the first stage larvae ( most often the species variation being acquired during larval life ) , variations can exist from the first asymmetric divisions [31] , [32] . Although the cell lineage of B . malayi ( a Rhabditia Spirurida of clade III of the Secernentea ) has not been established , parallels with the completely defined lineage of C . elegans ( a Rhabditia Rhabditida of clade V of the Secernentea ) are likely [32] , [33] . In secernentean nematodes , the first division cleaves the zygote asymmetrically into somatic cell AB and a smaller P1 germ line precursor cell ( Fig . 1A ) . Most of the embryonic ectodermal cells ( hypodermal and neuronal cells ) are derived from the anterior AB blastomere . The posterior P1 blastomere , after three rounds of division , primarily gives rise to the somatic gonad , pharynx , ectodermal and mesodermal derivatives ( MS ) , gut ( E ) , posterior hypodermal derivatives ( C ) , body wall muscles ( D ) and P4 blastomeres . During gastrulation , the posterior P4 cell follows the gut precursors inward and divides to produce the two germline precursors Z2 and Z3 . Based on the similarity between the C . elegans lineage and embryonic maps , putative germ line precursor cells can also be localized ( the counterparts of the C . elegans Z2 and Z3 ) during the process of elongation ( i . e . when the embryonic tail reaches half the length of the worm body ) . In contrast to C . elegans embryonic development , B . malayi embryos grow and increase their volume in the uterus ( Fig . 1B , C ) . The length of the one-cell egg increases from about 16 µm to 38 µm for an egg containing a mature worm-shaped embryo ( Fig . 1D ) . Thus , unlike C . elegans , the B . malayi eggshell grows and suggests that uptake of nutrients through the eggshell occurs while the embryo is still in the uterus . These observations may reflect fundamental metabolic differences during embryonic development between the parasitic B . malayi and free living C . elegans . We used propidium iodide ( PI ) to stain the host chromatin and the bacterial DNA , and used an anti-WSP ( wBm Surface Protein ) specific to Wolbachia to perform a fluorescent analysis of the Wolbachia segregation in the Brugia embryo . The anti-WSP revealed that the punctate staining obtained with PI corresponds to the Wolbachia DNA and does not stain mitochondrial DNA ( i . e . Fig . 2 ) . During fertilization , Wolbachia appear distributed throughout the oocyte completing meiosis , although more concentrated in the vicinity of the maternal chromatin in the anterior pole ( Fig . 2A , B ) . This may reflect an interaction with the microtubule spindle as observed at earlier stages ( i . e . Fig . S1 ) . As early as the pronuclei migration stage , Wolbachia dramatically relocalize towards the posterior pole of the egg ( P0 , Fig . 2 C to E , n>50 ) . We then followed Wolbachia segregation patterns in the two rounds of division following pronuclear fusion to create a diploid P0 zygotic nucleus . P0 division produces anterior -identified by the localization of polar bodies at the anterior surface ( Fig . 1A and Fig . 2F ) - and posterior localized , AB and P1 blastomeres respectively . Wolbachia always asymmetrically localize in P1 ( Fig . 2E , F , n>50 ) . P1 divides to produce EMS and P2 daughter blastomeres ( Fig . 1A ) . Wolbachia preferentially segregate to the posteriorly localized P2 blastomere . P2 divides to produce a dorsal C blastomere ( Fig . 2JI ) and a posterior P3 blastomere ( Fig . 2JII ) . Most of the Wolbachia segregate to the C blastomere and a minority segregate to the P3 blastomere . Although during the first zygotic division , the majority of Wolbachia preferentially localize in the P1 blastomere , a few localize to the AB blastomere . Division of the AB blastomere produces daughter blastomeres ABa and ABp ( Fig . 2G ) . Wolbachia titer in these descendants is variable but always lower than in the direct descendants of the P1 lineage ( Fig . 2H , I ) . In the 12-cell embryo ( Fig . 2J ) P2 has divided to give dorsally C ( Fig . 2JI ) and the posterior P3 ( Fig . 2JII ) . Most of the Wolbachia are in C , followed by P3 . The titer in the AB descendants , MS or E , although variable , is always lower than that in C and P3 . In the next rounds of divisions , C divides asymmetrically to give muscle cells and hypodermal cells ( Fig . 1A ) [33] . However without specific lineage markers , following the descendants of specific blastomeres is not possible after the 12-cell stage . Fortunately morphogenesis , as revealed by phalloidin-based actin staining , in the early B . malayi embryo is strikingly similar to that of C . elegans ( Fig . 2KI to KIV ) [34] . At this stage , the cellular proliferation is over , and circumferential actin bundles in hypodermal cells contract , transforming the round-shaped embryo into a worm . In both B . malayi and C . elegans , the hypodermis is composed of intercalated dorsal cells , lateral and ventral cells organized like the C . elegans hyp7 , seam and P cells ( Fig . 2KI ) . Under the dorsal and ventral hypodermal cells run the muscle quadrants from the anterior to the posterior ( Fig . 2KII , III ) . Deeper in the embryo , the embryonic neuroblasts , pharyngeal and gut cells can also be localized ( Fig . 2KIII , IV ) . Assuming that the lineage of B . malayi is very similar to the established lineage of C . elegans , we could verify the vertical transmission of Wolbachia in the embryonic blastomeres . Our observations of early stages showed that the Wolbachia were diluted out in the AB descendants , and in the MS and E blastomeres ( Figs . 1A , 2G to JII ) . During morphogenesis , we constantly found the Wolbachia enriched in the dorsal posterior hypodermis , and absent from nearly all anterior cells including neuroblast and pharyngeal cells , as well as muscle and gut cells ( Fig . 2KI to KIV , n>30 ) . This also implies that other asymmetrical segregations of Wolbachia occur in the C lineage to exclude them from the C-derived muscle cells and concentrate them in the hypodermis . Because the germline precursor P4 has already divided into Z2 and Z3 during morphogenesis and because these cells are often difficult to identify ( Fig . 3A to C ) we used the anti-histone H3K4me2 . It has been demonstrated that in C . elegans as well as in Drosophila melanogaster , a subset of nucleosome modifications ( dimethylation on lysine 4 of histone H3 and acetylation on lysine 8 of histone H4 ) are absent from germline precursors but present in all the other blastomeres . In C . elegans embryos , H3K4me2 marks all the blastomeres , including P4 , until it divides symmetrically into Z2 and Z3 [35] . Lysine 4 dimethylation on histone H3 is involved in transcription regulation and its absence reveals transcriptional quiescence [36] . In B . malayi however , we found embryos containing only one H3meK4-negative cell , suggesting that the putative P4 blastomere reorganizes its chromatin architecture to enter transcriptional quiescence prior to division ( Fig . 3D , E ) . We found half Wolbachia-infected and half non-infected putative P4 blastomeres or putative Z2/Z3 germline cells ( Fig . 3D to L ) . It is likely the embryos with uninfected blastomeres are males and those with infected blastomeres are females . We also found the average number of Wolbachia did not differ from early to mid embryogenesis ( 70+/−12 ( n = 10 ) ) and is in general agreement with the average number detected in microfilariae using qPCR [24] . Although this may suggest that asymmetric relocalization prior to division is the major cause for specific enrichment of a given blastomere , it does not rule out a possible stimulation/repression of bacterial replication due to asymmetrically localized cues . In fact , we noticed that in P2 , prior to division , Wolbachia appeared as doublets in the enriched antero/dorsal pole while as individual units in the posterior/ventral pole . This was supported by a WSP staining surrounding the doublets , suggesting active replication ( Fig . S2A , B ) . B . malayi adults , like any secernentean nematodes , have a simple and conserved anatomy . Non segmented , these worms have body walls organized in four longitudinal rows of hypodermal chords secreting the cuticle , and separated by four muscle quadrants . Lateral chords contain the excretory-secretory canal , while dorsal and ventral chords surround the nerves . They lack circulatory and respiratory systems . A nerve ring located around the pharynx constitutes the central nervous system ( Fig . S3D , E ) . The triradiate pharynx is connected to the gut . Females have two gonads starting in the posterior and ending in the anterior vulva , while the male has one gonad starting in the anterior and ending in the posterior cloaca . To determine Wolbachia distribution in adult tissues , we stained whole-mount fixed adults either with DAPI or live specimens with the vital dye Syto11 ( [37] , cf . Fig . 4 and Fig . S4 ) . Detailed measurements of body and tissues features have already been reported [15] . The two female distal gonad arms located in the posterior ( several millimeters separate the two ovaries distal ends ) coil along an anterior-posterior axis ( Fig . 4F ) . The ovaries lead anteriorly to the two uteri that are also coiled around one another ( i . e . Fig . 4B ) , and filled with sperm that has migrated in their distal parts ( Fig . 4A , E ) . The amount of sperm is variable between females and may reflect the time of observation after copulation . Oogenesis begins at the distal region of the ovaries and as the oocytes mature they are pushed proximally and are fertilized in the distal part of the uteri , where developing embryos are present in the proximal regions ( Fig . 4A , C , D; Fig . S5 ) . Thousands of microfilariae are released in the lymph of the host through the ovejector that ends the vulva where the uteri meet , in the anterior part of the female , specifically at the level of the posterior pharynx ( Fig . 4A , B , C; Fig . S3A to C ) . The male gonad consists of a testis posterior to the pharynx of the nematode , connected to the sperm duct which in turn leads to a widened seminal vesicle where mature sperm is stored ( Fig . 4A; Fig . S4 ) . The gonad ends in the cloaca where two specialized spicules are used for mating ( Fig . S4 ) . The intestine is a thin empty tube connected at the anterior to the pharynx , and at the posterior to the ventral rectum close to the posterior tip in both male and female worms ( Fig . 4A , F; Fig . S6 ) . Gonads and intestine fill the pseudocoel contained within the body wall . Lateral chords are prominent in Brugia . They are formed through fusion of hypodermal cells producing a syncytial chord surrounding the secretory-excretory canal and in between muscle quadrants [32] . The lateral chords project a thin layer of cytoplasm over the muscles to connect the dorsal and ventral chords . These dorsal and ventral chords , containing the dorsal and ventral nerves , are very thin and difficult to observe by differential contrast microscopy but can be revealed by staining the surrounding muscles ( Fig . S3F to H ) . Uteri appear closely apposed or embedded in the lateral chords ( Fig . S7 ) . The body wall possesses a slight periodicity , and hypodermal chords and muscle quadrants turn several times around the central axis of the worm between the two tips . The male posterior end is coiled three to four times in the region encompassing the spicules , probably to ensure a better grip during mating ( Fig . S4 ) . In both male and female worms ( n>30 ) , Wolbachia concentrate around the two rows of hypodermal nuclei in lateral chords . While most worms displayed two infected lateral chords ( Fig . 5A to D ) , in about 40% only one of the two chords was infected ( the left or the right chord ) . We also observed worms with half of a chord infected ( Fig . 5E , F ) , sometimes in a mosaic pattern ( Fig . 5I , J ) , possibly reflecting the earlier mosaicism in Wolbachia segregation during embryonic development . In the chords , the Wolbachia like the nuclei are located in the basal part , while the circumferentially oriented actin bundles are in the apical compartment ( Fig . 5K to L′ ) . In addition , no adult was found with both lateral chords completely lacking Wolbachia , suggesting that Wolbachia localization in these chords may be essential for worm survival . Conversely , the Wolbachia are completely absent from the intestinal cells , the somatic gonad ( gonadal contractile sheath cells and epithelium , Fig . S6 ) and the muscle quadrants ( Fig . 5 ) . It is hard to clearly draw a conclusion on the presence of Wolbachia in the nervous system , due to the low quality of the nerve ring chromatin staining with PI but the bacteria appear either absent or at very low titer in this organ ( Sup . Fig . 3D , E ) . We stained the secretory-excretory canals with phalloidin in non-fixed worms , to avoid the overwhelming signal coming from actin-rich tissues ( i . e . muscles ) . Despite variable results , we have been able to locate the secretory-excretory pore close to the mouth ( Fig . 6A ) . By increasing the phalloidin signal in fixed animals , we could reveal the lumen of the canal ( Fig . 6B to G , between arrowheads ) . We found propidium iodide spots present in the lumen of the canal in variable amounts , similar to those in infected parts of chords ( Fig . 6B to D ) , but also in the lumen of the canal in non-infected parts of chords ( i . e . Fig . 6E to G ) . We confirmed these observations on worms kept alive , by visualizing the secretory-excretory canal with the fluorescent marker resorufin . This marker is a substrate of P-glycoproteins and multidrug resistance associated proteins , localized in the apex of polarized cells , involved in excretory processes ( cf . [38] ) . Resorufin concentrates in the chords and neighboring tissues before its excretion via the canal . We combined it with the DNA vital dye syto11 ( Fig . 6H to M ) . Altogether these data suggest that adult Brugia may secrete/excrete low numbers of Wolbachia into their host . In the female and male germinal zones , oogoniae or spermatogoniae are partially surrounded by an actin rich membrane connected to the actin-rich central rachis at the distal part of the ovary ( Sup . Fig . 5A , C , D ) . These germ cell nuclei initially organized in a syncitium , then cellularize and detach from the central rachis while migrating proximally towards the uterus or the sperm duct ( Fig . S5G to J ) . All female germ cells are infected and contain an average of 35+/−6 . 8 Wolbachia ( n = 13; Fig . S5A to C ) in the most distal part of the ovary , before complete cellularization . This suggests a high replication rate of the bacteria in the mitotic region of the ovary ( Fig . S5A to C , G , H ) . More mature oogoniae are located more proximally in the ovary and contain slightly more bacteria ( 49+/−10 , n = 8 ) . Mature oocytes are fertilized when encountering sperm in the distal uterus to give zygotes . Surprisingly , analogous studies in the male germline revealed no bacteria at any stage of spermatogenesis ( n = 3 males ) . Although it is difficult to distinguish bacteria from mature sperm chromatin , cytological observations at earlier stages of spermatogenesis left no doubt on the absence of Wolbachia in the male germline ( i . e . Fig . S5D to F , I , J ) . Characterization of the transmission mechanisms , distribution pattern and titer of Wolbachia in the germline and soma is of primary importance for understanding the biology of the interaction between Wolbachia and its host B . malayi . We found in B . malayi a high Wolbachia/ host nuclei ratio in early embryogenesis and in the adult lateral chords . Wolbachia were also concentrated in the female germline but absent from the male germline ( summarized in Fig . 7A ) . To understand the origin of this distribution pattern , we examined Wolbachia segregation during early embryogenesis . Despite variability in the Wolbachia titer among embryos of the same stage , the bacteria were present in all embryonic blastomeres until about the 6-cell stage , but greatly enriched in the posterior pole , following fertilization . Our data indicate that Wolbachia are present in the most posterior blastomeres , P2 and EMS at the 4-cell stage , followed by C and P3 in all embryos at the 12-cell stage , that is to say both male and female embryos . Presence in C is the main source of transmission to the hypodermis , while maintenance in P3 and subsequently P4 ensures transmission to the germline ( Fig . 7B ) . During the mitotic proliferation of oogoniae , association of Wolbachia with the mitotic spindle is likely used to ensure an even segregation in the female germline . Interactions of Wolbachia with the host microtubules has been well documented in arthropods ( i . e . [39] ) . During fertilization , the primary enrichment could be due to a passive mechanism involving the deep cytoplasmic flow oriented towards the posterior [40] . It is also well established that in C . elegans the sperm entry induces partitioning of the evolutionary conserved cell polarizing factors PARs [40] , [41] . Brugia PAR orthologs and their downstream effectors may be responsible for keeping the Wolbachia in the posterior . Asymmetric segregation has been described as a common feature of Wolbachia localization in arthropods , such as in Drosophila germline and somatic cells , in wasp species and mosquito germlines [42] , [43] . Whether the mechanisms used to enrich the posterior of the embryos , to subsequently invade the germ cell precursors , is due to convergent evolution or to common developmental pathways remains to be determined . The latter may provide new targets in anti-Wolbachia based therapies in filariasis . An evolutionarily conserved mechanism for posterior localization maybe supported by the mode of invasion of the chords . Instead of invading the AB lineage , the main source of hypodermal blastomeres , Wolbachia utilize the posterior C blastomere . It is tempting to speculate that during the evolution of the Wolbachia-nematode interaction , the bacteria followed conserved posterior determinants to ensure transmission to the germline , and subsequently acquired an affinity for the C blastomere and its ectodermal derivatives . In secernentean nematodes , fixed lineages contribute to different types of tissues . This raises the intriguing question of the mechanisms underlying the transmission of the bacteria to the proper differentiated blastomeres . The segregation pattern of Wolbachia in the early embryo could result from sensing regulatory networks patterning the embryo , to asymmetrically segregate and proliferate . From the 2 to 12-cell stages , their transmission pattern is very similar to the expression pattern of the C . elegans homeodomain protein PAL-1 , required for the C-lineage expression [44] . In a second phase , C-derived ectodermal derivatives could trigger Wolbachia proliferation [45] . Likewise , germline-specific factors are likely to play a role in segregation in the P germline lineage . It is significant however that some embryos appeared devoid of Wolbachia in the P4 blastomere and the Z2/Z3 germline cells , implying a possible loss of Wolbachia after establishment of the P3 blastomere and before establishment of Z2/Z3 . What happens to these Wolbachia remains unclear , they may all segregate into the P4 sister , the D blastomere , to be diluted out without replicating for instance , as observed in the descendants of AB , E or MS . We hypothesize that embryos with and without Wolbachia in the P4 blastomere are female and male embryos respectively , since we find a ratio identical to the equal sex ratio described in larvae of the closely related Brugia pahangi [46] . Our data do not allow us to rule out possible mechanisms of transcellular invasion from neighboring tissues to non-infected germ cells at later stages , or later loss of Wolbachia in the male germline when Wolbachia are initially observed in the germline precursors . In Brugia , sex determination if of XX/XY type , and males possess a heterogametic pair of chromosomes [47] . Wolbachia may sense the gender of the embryo prior to the establishment of the P4 blastomere . Such an early sensing of the embryo's gender may involve interactions with a X- chromosome dosage compensation machinery [48] . In C . elegans for instance , this protein complex is active as early as the 30-cell stage , before formation of the P4 blastomere [49] , [50] . Based on lessons from C . elegans genetics and cell biology on embryonic cell fate establishment , immunofluorescence and RNAi techniques on relevant Brugia orthologs should help us to understand the molecular mechanisms of Wolbachia transmission . We observed the highest bacteria titer in the adult lateral hypodermal chords . Some worms however possess partially infected chords , or one chord lacking Wolbachia . This observation may explain the wide range in Wolbachia load between individual worms as measured by qPCR [24] . Observations at the embryonic level revealed few infected hypodermal cells , mainly posterior-dorsal , in which the bacteria multiplied ( i . e . Fig . 2K ) . A common feature of secernentean nematodes is that during development , hypodermal cells fuse creating a syncytium in the adult [51] . Since we did not find nuclei in the adult ventral and dorsal chords , it is likely that all the hypodermal dorsal and ventral nuclei migrate laterally in Brugia . Thus Wolbachia may spread through fusion of infected with uninfected hypodermal cells . The developmental timing of hypodermal fusion is unknown . However since we observed Wolbachia invasion of lateral chords in young adults ( Fig . 5I , J ) , hypodermal fusion in Brugia is likely to have occurred during larval or young adult stages . This would predict a dramatic increase in Wolbachia titer per host nuclei during larval stages and early adult , and is supported by quantitative PCR data [25] . Hence , the selective pressure for somatic invasion must be less important than in the germline , since vertical transmission from a single hypodermal cell of a chord is theoretically sufficient to ensure a successful colonization . We have performed our cytological studies in young adults while B . malayi can live for many years . This could explain the presence of these partially non-infected chords . It would be interesting to determine whether aged adults contain fully infected lateral chords . The nematode hypodermal chords have been shown to play a fundamental function in the metabolism of stored carbohydrate and protein synthesis , as well as the uptake of nutrients via the transcuticular route [51] , [52] . Wolbachia may participate in these lateral chord functions . Moreover it has been recently demonstrated that part of the stress response induced in Wolbachia-depleted B . malayi by tetracycline is an upregulation of amino acids synthesis and protein translation , suggesting an initial compensation for the lack of Wolbachia [53] . Depletion of Wolbachia with antibiotics has been shown to reduce the production of microfilariae and to affect embryogenesis [53]–[55] . This last study also shows that tetracycline treatments result in Wolbachia degeneration in the germline and embryos prior to Wolbachia loss in the lateral chords . Defects in embryogenesis may still be due to a perturbed metabolism starting at the level of the hypodermal chords rather than a direct effect on the few Wolbachia present in embryonic hypodermal and germ line cells . Support for this idea comes from the fact that Wolbachia are present exclusively in the female germ line and not in the male germ line . Thus while Wolbachia are transmitted vertically through the female germline , they may not be necessary for germline development . Selective pressure in the germline may be greatly reduced in endosymbionts such as Wolbachia that are involved in metabolic mutualism . In contrast , Wolbachia are parasitic in many arthropod species and accordingly have a profound influence on host germline function [43] . Second , we observed an increase in embryo size during development suggesting nutrient uptake from the uterus . Third , both in live specimens and in whole mount fixed adults a tight association between lateral chords and the uterus was observed , arguing for a role of the chords in supplying the production demands of microfilariae ( i . e . Fig . 5H and Fig . S7 ) . It has been established that Wolbachia release in the human body , presumably from degenerating worms , has a crucial impact on the development of river blindness and lymphatic filariasis , by activating the host immune response [3] , [12] , [13] , [14] . We detected variable amounts of Wolbachia in the secretory-excretory canals , present in the chords , even in non-infected regions of the chords . This suggests that in addition to degenerating worms , live adults may release Wolbachia , through the excretory pore . PCR analysis of short term in vitro culture supernatant was unable to detect Wolbachia DNA , although 90 Wolbachia proteins were detected in ES products [56] . Furthermore , immunohistochemistry of O . volvulus does not detect the abundant release of Wolbachia into the surrounding tissues [57] . Nevertheless , low numbers of Wolbachia and/or their products may be released via the excretory/secretory canal as previously hypothesized [58] , and act as an additional source of immunostimulatory components that contribute to the known innate and adaptive immune responses typical of filarial infections [59]–[61] .
Filarial diseases affect over 150 million people in tropical countries . They are caused by parasitic nematodes like Brugia malayi that rely on their endosymbiont Wolbachia for their survival and fertility . These bacteria are a recognized drug target in the search for treatments killing adult worms . To understand the transmission of Wolbachia from the embryonic to adult stages , we developed new techniques to track these bacteria at the cellular and tissue levels . These techniques include immunofluorescence in whole mount adult tissues and embryos . We found that Wolbachia segregate asymetrically in specific cells , in a lineage-specific manner during early Brugia embryogenesis , and rely on cell fusion to subsequently populate the adult hypodermal chords . From the chords , the Wolbachia can be secreted in the secretory-excretory canal , suggesting that in addition to dead worms releasing the bacteria in the human body , living worms may also secrete Wolbachia , whose role in stimulating the immune system in filarial pathologies is now well established .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "developmental", "biology/embryology", "infectious", "diseases/neglected", "tropical", "diseases", "developmental", "biology/microbial", "growth", "and", "development", "cell", "biology/microbial", "growth", "and", "development", "infectious", "diseases/helminth", "infections" ]
2010
Asymmetric Wolbachia Segregation during Early Brugia malayi Embryogenesis Determines Its Distribution in Adult Host Tissues
Hereditary periodic fever syndromes are characterized by recurrent episodes of fever and inflammation with no known pathogenic or autoimmune cause . In humans , several genes have been implicated in this group of diseases , but the majority of cases remain unexplained . A similar periodic fever syndrome is relatively frequent in the Chinese Shar-Pei breed of dogs . In the western world , Shar-Pei have been strongly selected for a distinctive thick and heavily folded skin . In this study , a mutation affecting both these traits was identified . Using genome-wide SNP analysis of Shar-Pei and other breeds , the strongest signal of a breed-specific selective sweep was located on chromosome 13 . The same region also harbored the strongest genome-wide association ( GWA ) signal for susceptibility to the periodic fever syndrome ( praw = 2 . 3×10−6 , pgenome = 0 . 01 ) . Dense targeted resequencing revealed two partially overlapping duplications , 14 . 3 Kb and 16 . 1 Kb in size , unique to Shar-Pei and upstream of the Hyaluronic Acid Synthase 2 ( HAS2 ) gene . HAS2 encodes the rate-limiting enzyme synthesizing hyaluronan ( HA ) , a major component of the skin . HA is up-regulated and accumulates in the thickened skin of Shar-Pei . A high copy number of the 16 . 1 Kb duplication was associated with an increased expression of HAS2 as well as the periodic fever syndrome ( p<0 . 0001 ) . When fragmented , HA can act as a trigger of the innate immune system and stimulate sterile fever and inflammation . The strong selection for the skin phenotype therefore appears to enrich for a pleiotropic mutation predisposing these dogs to a periodic fever syndrome . The identification of HA as a major risk factor for this canine disease raises the potential of this glycosaminoglycan as a risk factor for human periodic fevers and as an important driver of chronic inflammation . Shar-Pei dogs have been companion animals for centuries within China where they were commissioned to guard and hunt , and to sometimes serve as fighting animals . At the beginning of the communist era dog ownership was highly taxed and the breed was brought close to extinction . A few Chinese Shar-Pei dogs were exported to the United States in the early 1970's and Shar-Pei descending from this limited number of animals have undergone strong selection for a wrinkled skin phenotype and heavily padded muzzle and are called the “meatmouth” type ( Figure 1A–1C ) and have now found global popularity . The ancestral Shar-Pei , referred to as the “traditional” type Shar-Pei , still occurs and it presents with a less accentuated skin condition ( Figure 1D ) . The major constituent of the deposit in the thickened skin is hyaluronan or hyaluronic acid ( HA ) . HA is a large , multifunctional , linear , negatively charged , non-sulfated glycosaminoglycan of the extracellular and pericellular matrices . It is composed of repeating disaccharides and is widely spread throughout epithelial , connective and neural tissues [1] , [2] . The biological role of HA depends on its size , location and equilibrium between synthesis and degradation [1]–[3] . Meatmouth Shar-Pei show two- to five-fold higher serum levels of HA compared to other breeds [4] , allowing us to propose the term hyaluronanosis , a definition also used for a comparable human condition [5] . HA is synthesized at the plasma membrane by three HA synthases , HAS1 , HAS2 and HAS3 , with HAS2 being the rate limiting-enzyme [6] . HAS2 is overexpressed in dermal fibroblasts of Shar-Pei compared with other canine breeds [7] suggesting a regulatory mutation as causative for hyaluronanosis . HA is deposited throughout the skin of Shar-Pei , often in microscopic lakes and grossly evident vesicles , leading to the formation of thickened skin folds around the head and tibiotarsal ( hock ) joints ( Figure 1E ) . Almost all Shar-Pei seem to be affected by hyaluronanosis , however the extent varies among individuals and adults exhibit less skin folds and hyaluronanosis than puppies . Strong selection by breeders for dogs who retained their skin folds into adulthood has altered the phenotype of the breed to the more commonly heavily wrinkled meatmouth type . Meatmouth Shar-Pei also suffer a strong predisposition to an autoinflammatory disease , Familial Shar-Pei Fever ( FSF ) , which clinically resembles some human hereditary periodic fever syndromes , such as Familial Mediterranean Fever ( FMF ) [8] . Both diseases are characterized by seemingly unprovoked episodes of fever and inflammation and both FMF and FSF present as short ( 12–48 hour ) recurrent bouts of high fever , accompanied by localized inflammation usually involving major joints ( especially the tibiotarsal joints ) . Patients with FMF or Shar-Pei with FSF can suffer episodes as often as every few weeks , but in the interim seem symptom free . However , since acute phase reactants may endure between episodes , a subclinical state and chronic autoinflammation may persist ( Linda Tintle unpublished data ) . As a secondary complication , the chronic state puts human patients , as well as affected Shar-Pei dogs , at risk of developing reactive systemic AA amyloidosis and subsequent kidney or liver failure [8] , [9] . In Shar-Pei , the fever episodes are typically more frequent during the first years of life and the percentage of affected dogs is very high , estimated to be 23% in the US in 1992 [9] . In order to find candidate loci for the breed-specific phenotype ( hyaluronanosis ) , known to be under selective pressure , we screened the genome for signatures of selective sweeps . These sweeps can be recognized as long chromosomal segments with a low degree of heterozygosity within populations [10] . Using 50 , 000 single nucleotide polymorphisms ( SNPs ) distributed throughout the dog genome , the level of heterozygosity in windows of ten consecutive SNPs was compared between a set of Shar-Pei ( n = 50 , all from the US , Table S1 ) and the average of 24 other canine breeds ( n = 230 ) . On four chromosomes ( Cfa 5 , 6 , 13 and X ) the reduction in heterozygosity in Shar-Pei was greater than 4-fold the average of control breeds ( Figure 2A ) . The strongest signal of reduced heterozygosity appeared within a 3 . 7 Mb stretch on chromosome 13 ( CanFam 2 . 0 Chr13: 23 , 487 , 992–27 , 227 , 623 ) ( http://genome . ucsc . edu/ ) near the HAS2 gene , where almost complete homozygosity was observed in Shar Pei ( Figure 2C ) . Here the reduction in heterozygosity was greater than 10-fold in Shar-Pei and several smaller regions showed complete homozygosity . The same region was confirmed to show high levels of homozygosity when the analysis was repeated in 37 additional Shar-Pei dogs sampled from Spain ( Table S1 ) and was overlapping a sweep region reported by others for this breed [11] . The strong signal , together with the known function of HAS2 and its aberrant expression pattern in Shar-Pei , made this region an obvious candidate for the mutation causing the wrinkled skin phenotype ( hyaluronanosis ) . In parallel , we performed a genome-wide association study to map the susceptibility locus for FSF , using Shar-Pei strictly classified as FSF affected ( n = 24 , classification code FSF+A and FSF+ , described in Materials and Methods ) and unaffected ( n = 17 , classification code H+ , described in Materials and Methods ) . Five SNPs were significantly associated ( best SNP praw = 7 . 0×10−7 , pgenome = 0 . 005 based on 100 , 000 permutations; software package PLINK http://pngu . mgh . harvard . edu/~purcell/plink [12] ) , all on chromosome 13 ( CanFam 2 . 0 Chr13: 22 . 4–30 . 7 Mb , Figure 2B ) . After correcting for putative stratification , two outlier cases were removed ( Figure S1 ) and the same SNPs , forming the same signal of association remained ( best SNP praw = 2 . 3×10−6 , pgenome = 0 . 01; Table S2 ) with a genomic inflation factor of 1 . 2 . When the association signal and the sweep signal were compared they appeared interspersed , so that individual SNPs were either part of homozygous regions or showed association with FSF ( Figure 2C ) . It was therefore difficult to determine exactly where the strongest association fell , as variation is required to detect association . Targeted sequence capture technology was used to further investigate the sweep signal and to search for the hyaluronanosis causative mutation . We resequenced 1 . 5 Mb around and upstream of our candidate gene , HAS2 ( CanFam 2 . 0 Chr13: 22 , 937 , 592–24 , 414 , 650 ) in four Shar-Pei ( two meatmouth type with high serum HA levels and two traditional type ) and three control dogs from other breeds . The obtained sequences were mapped to the boxer reference sequence providing at least 5X coverage for 96–98% of the resequenced region in each individual . The targeted region also included the large intergenic noncoding RNA , HAS2 antisense ( HAS2as; Table S3 ) which has been proposed as a negative post-transcriptional regulator of HAS2 mRNA [13] . After masking repetitive sequences we identified ∼670 indels and ∼1 , 500 SNP in each dog ( Table S4 ) as well as two overlapping duplications in the Shar-Pei ( Figure 3A ) . Nine mutations ( eight SNPs and one indel ) located in conserved elements as well as two SNPs possibly regulating transcription , were selected for further investigation due to their unique pattern in the sequenced Shar-Pei dogs . Additional genotyping in Shar-Pei and dogs from other breeds ( Tables S1 , S5 ) showed these mutations were not specific to Shar-Pei and the variants were subsequently excluded as causative . The two duplications were named after the Shar-Pei type in which they were first identified . The “meatmouth” duplication was the larger fragment , 16 . 1 Kb ( CanFam 2 . 0 Chr13: 23 , 746 , 089–23 , 762 , 189 ) with breakpoints located in repeats ( a SINE at the centromeric end and a LINE at the telomeric end ) and individual copies separated by seven base pairs ( Figure 3B ) . The “traditional” duplication was 14 . 3 Kb ( CanFam 2 . 0 Chr13: 23 , 743 , 906–23 , 758 , 214 ) and was identified in the two Shar-Pei with a less accentuated skin phenotype ( Figure 3B ) . We first examined the duplications via Southern blot with control breeds ( n = 2 ) , traditional ( n = 2 ) and meatmouth Shar-Pei ( n = 6 ) ( Figure 3C ) . As the digest cut outside and within both duplications , we were able to observe the absence of the variants from control breeds and separate restriction patterns in traditional and meatmouth type Shar-Pei . Interestingly , one meatmouth dog contained both duplication types ( Figure 3C lane 6 and confirmed by PCR across break points , data not shown ) . Two copy number assays were developed to quantify these elements . The first ( CNV-E ) measured only the meatmouth duplication whilst the second ( CNV-748 ) , detected both the traditional and meatmouth duplications . Copy number analysis was estimated as the relative fold enrichment ( ΔΔCt ) between an amplicon within the duplication and one outside the duplication in a housekeeping gene . Assay CNV-E was run on 90 Shar-Pei and 73 dogs from 24 other breeds ( Table S1 ) and assay CNV-748 on a subset of 44 Shar-Pei and 14 dogs from other breeds . Assay CNV-748 demonstrated that both the traditional and meatmouth duplications are unique to the Shar-Pei breed ( Figure 4 and Figure S2 ) . We used the results of both assays to search for a relationship between Familial Shar-Pei Fever ( FSF ) and either meatmouth copy number ( Assay CNV-E ) , traditional copy number ( the normalized difference between CNV-748 and CNV-E ) or total traditional+meatmouth copy number ( Assay CNV-748 ) . Shar-Pei dogs were strictly classified as affected by FSF ( n = 28 , FSF+A and FSF+ ) or unaffected by FSF ( n = 16 , H+ ) . The most significant association was found when only the meatmouth copy number was considered ( p<0 . 0001 , Figure 4 ) although a weaker association with total copy number ( p<0 . 01 ) was also seen . The observed association between fever and meatmouth copy number , despite the very high homozygosity in this region , strongly suggests that a high copy number is not just a genetic marker for FSF but is causally related to the development of disease . Of the 153 dogs analyzed with the meatmouth copy number assay , 31 Shar-Pei and 18 control animals also had serum measures of HA available . No clear association was detected between HA levels and copy number ( Figure S3 ) , however the mean HA level in Shar-Pei with ≥ six copies was 905±403 ug/L ( n = 21 ) , whilst Shar-Pei with fewer copies had a mean concentration of 770±494 ug/L ( n = 12 ) and control breeds had HA serum levels of 206±145 ug/L ( n = 19 ) . Interestingly , the three traditional Shar-Pei dogs had serum HA levels between 73 and 266 ug/L , which fell within the normal range [4] . The link between copy number and the expression of HAS2 and HAS2as was examined on a smaller scale using dermal fibroblasts cultured from six separate meatmouth Shar-Pei . The expression of both genes was calibrated against the Shar-Pei with lowest copy number ( CNV estimate = 5 ) and both genes showed an increasing trend of expression with copy number ( Figure 5 ) . These data suggest that a regulatory element for HAS2 is located in the duplicated region , however the interpretation of the HAS2as result is less clear . A single study of a human osteosarcoma cell line demonstrated that the expression of two isoforms of HAS2as were able to reduce HAS2 expression , and so these mRNAs may act as regulators of HA production [13] . Our data could indicate that HAS2as expression is also influenced by a regulator element in the duplication , or that HAS2as is up-regulated in response to HAS2 levels . If either of these scenarios were true , it is possible that if RNA expression were measured at multiple time points we would see temporal HAS2 repression . It could also be that the interaction between canine fibroblast HAS2 and HAS2as does not mirror the human system and that the canine antisense mRNA is non-functional . At present our results must be considered as preliminary and it is clear that further exploration of the interaction between canine HAS2 and HAS2as is required . Here we have identified a 16 . 1 Kb duplication located approximately 350 Kb upstream of HAS2 . This is clearly a derived mutation since it occurs as a single copy sequence in other dog breeds . We postulate that this is a causative mutation associated with both hyaluronanosis and Shar-Pei fever , as the observed correlation between copy number and susceptibility to Shar-Pei fever was not expected if this was a linked , neutral polymorphism . We suggest that the unique region of the meatmouth type duplication identified in Shar-Pei contains one or more regulatory elements that alter the expression of HAS2 . It appears possible that as the duplication copy number increases , so does the copy number of potential enhancer elements within the duplication , likely leading to a higher expression of HAS2 and elevated HA levels , and resulting in the development of hyaluronanosis in this breed . We propose a scenario whereby the traditional duplication arose de novo in the traditional type of Shar-Pei causing a milder skin phenotype . This event made the region unstable and allowed the second meatmouth duplication to occur . Breeders subsequently selected the meatmouth duplication as a higher copy number enhanced the phenotypic effect in appearance . However , it is not yet possible to say whether the meatmouth duplication first occurred at low frequency in the Chinese Shar-Pei population and quickly rose during breeding in America , or if the mutation occurred spontaneously during breed expansion in the West . Tandem duplications are notoriously unstable and may show copy number variation due to unequal crossing-over , as is clearly illustrated by the copy number variation of a 450 Kb duplication associated with dominant white colour in pigs [14] . The meatmouth Shar-Pei duplication adds to the list of copy number variants ( CNVs ) , which affect phenotypic traits in domestic animals ( e . g . dominant white in pigs [14] , gray color in horses [15] , the hair-ridge in Rhodesian ridgeback dogs [16] , and pea-comb in chicken [17] ) , several of which are linked not only to the desirable trait but also to disease . Interestingly , all of these except pea-comb , represent novel duplications derived from single copy sequences . This is in contrast to most reported CNVs in humans , which are mainly benign and represent expansions or contractions of duplicated sequences [18] . Although we failed to find a significant correlation between serum HA levels and copy number , this does not exclude our proposed hyaluronanosis scenario . Difficulties in correlating fluctuating serum levels of HA with other clinical and biomedical parameters have also been reported in many human studies , where no or only weak correlations were observed [19] , [20] . We have shown that the 16 . 1 Kb duplication appears only in meatmouth Shar-Pei , a breed type that has elevated levels of HA compared to both traditional Shar-Pei and other breeds , and that copy number correlates with a breed-specific syndrome associated with excessive HA deposition and the over expression of a HA synthesizing gene . Because HA is primarily a component of the extracellular matrix , serum measurements may only broadly reflect total body HA . Hyaluronan can bind to several cellular receptors ( e . g . CD44 , RHAMM and layilin ) , however it is the interaction between CD44 and HA which acts as a biological regulator , differentially modulating the cellular microenvironment in response to homeostatic versus inflammatory conditions [21] . Alterations in the balance between native high molecular weight HA versus fragmented HA may result in activation of innate immunity . HA has been linked to sterile inflammation as an endogenous response molecule to sterile tissue injury [21] . Shorter fragments of HA can be generated by environmental insults such as sterile trauma [22] , reactive oxidative species ( ROS ) [23] , or pathogenic hyaluronidases , and it is these low molecular weight fractions which can become pro-inflammatory danger associated molecular pattern ( DAMP ) molecules [22] , [24] mimicking microbial surface molecules . Using a mouse model , Yamasaki and colleagues [25] showed that HA can interact with the cell through two separate pathways that culminate in the release of IL-1β , which together with IL-6 , is one of the main promoters of fever . In the first route , CD44 bound HA is degraded at the plasma membrane by hyaluronidase-2 ( HYAL2 ) prior to endocytosis and further cleavage by lysosomal hyaluronidase-1 ( HYAL1 ) . The resultant small intracellular oligosaccharides of HA activate the NLRP3 inflammasome , a multiprotein complex consisting of the NLRP3 scaffold , the ASC adaptor and caspase-1 [26] . In the second arm , the CD44-HA complex activates toll like receptors 2 and 4 ( TLR2 and 4 ) , leading to intracellular IL-1β mRNA transcription and the formation of pro-IL-1β . Activation of the NLRP3 inflammasome by HA oligosaccharides allows cleavage of this pro-IL-1β by caspase-1 and subsequent release of IL-1β . The NLRP3 inflammasome is present in the cytosol of many cells including monocytes , macrophages and mast cells , and has been implicated in the pathogenesis of numerous autoinflammatory diseases in humans including the cryopyrin-associated periodic syndromes which result from mutations in NLRP3/CIAS1 [26] . The actual role of excessive HA in Shar-Pei needs to be investigated further . Shar-Pei may experience exogenous fragmentation of their over-abundant HA from sterile or pathogenic trauma . This , plus endogenous degradation of excessive native HA , may contribute to induction of recurrent episodes of fever and inflammation . Acute fever events in Shar-Pei respond rapidly to dipyrone , a potent antipyretic and analgesic pyrazolone , which has been demonstrated to inhibit IL-1β induced fever [27]–[29 and Linda Tintle unpublished data] . It is therefore not surprising that the strong selection on the hyaluronanosis phenotype , with increased levels of cutaneous HA , may predispose Shar-Pei to autoinflammation , potentially contributing to other pathologies seen in this breed . One such example is renal medullary amyloidosis . Histopathologically , kidneys of Shar-Pei in renal failure have multifocal non-suppurative tubulointerstitial nephritis with fibrosis . Medullary amyloidosis predominates and glomerular deposition , although consistent , is highly variable in its extent [8] , [30] . The renal medulla is naturally HA rich and enhanced renal interstitial HA accumulation can be coupled to inflammatory responses , such as ischemia-reperfusion injury , transplant-rejection , tubulointerstitial inflammation and diabetes [31] . In addition , Shar-Pei are prone to mast cell disease including mast cell tumors [32] , [33] . The binding of HA to CD44 has been shown to play a critical role in regulation of murine cutaneous and connective tissue mast cell proliferation [34] . As the CD44-HA interaction may modulate local immune responses through regulation of mast cell functions [35] , excessive HA and its subsequent damage and degradation may play a role also in the Shar-Pei breed’s predilection for allergic skin disease and other mast cell driven inflammation . This study suggests that HAS2 dysregulation can trigger a periodic fever syndrome in dogs and therefore it will be relevant to examine the approximately 60% of human fever patients who currently have unexplained disease . Previously , the role of hyaluronan in sterile inflammation has focused on HA signaling and degradation; for example a deficiency of hyaluronidase causing mucopolysaccharidosis type IX in humans has some autoinflammatory features [36] . However by directly implicating HAS2 in inflammation , we suggest that a reexamination of genes further up the biosynthetic pathway , such as those involved in HA synthesis and polymerization is called for . In addition , the canine mutation appears regulatory in nature and therefore regulators of HA should be also be included in a broader scope pathway analysis of human patients with unexplained autoinflammatory disease . Finally , this study illustrates how copy number variations can shape phenotypic traits and how strong artificial selection for certain phenotypic traits may not only affect the desired trait but also the health of the animal . All dog samples were collected from pet dogs after owner consent following the ethical approval protocols ( SLU , Dnr: C103/10 , MIT 0910-074-13 ) . DNA was extracted from blood samples using QIAamp DNA Blood Midi Kit ( QIAGEN ) or PureLink Genomic DNA kit ( Invitrogen ) . All dogs , their breed type , geographic origin , health status and experiment in which they were utilized are listed in Table S1 . Classification of Shar-Pei fever: Purebred Shar-Pei individuals were divided into the following six groups based on their medical records and evidence by owner and/or veterinarian: 1 . FSF+A , the individual had experienced recurrent episodes of high fever accompanied by inflammation of joints from an early age ( less than one year old ) . Additionally , post-mortem examination detected depositions of amyloid in kidneys and/or liver ( amyloidosis ) . 2 . FSF+ , the individual had experienced recurrent episodes of high fever accompanied with inflammation of joints from an early age ( less than one year old ) . 3 . Atypical FSF , the individual had experienced occasional unexplained fever episodes or recurrent episodes with a late onset ( greater than three years old ) . 4 . H+ , the individual had never experienced unexplained fever and/or inflammation , was older than five years old at the time of sampling and also lacked first-degree relatives that could be classified into the groups FSF+A , FSF+ or Atypical FSF . 5 . H- , the individual had never experienced unexplained fever and/or inflammation but was younger than 5 years at the time of sampling and/or had first-degree relatives that could be classified into the groups FSF+A , FSF+ or Atypical FSF . 6 . Unknown , the individual’s medical record was not available . Hyaluronanosis: Serum Hyaluronic Acid ( HA ) concentration was used as a proxy for hyaluronanosis but no distinct cut-off value was established . However , dogs with normal and abnormal concentrations of serum HA were interpreted as before [4] . HA measurements were performed using the Hyaluronan ELISA kit ( Echelon Biosciences INC ) according to the manufacturer’s instructions . The absorbance was read at 405 nm , and a semi-log standard curve was used to calculate hyaluronic acid concentrations . A whole genome scan was performed with two array types , the 27K ( v1 ) and 50K ( v2 ) canine Affymetrix SNP chips . Results were called using Affymetrix’s snp5-geno-qc software . The 50K array was used when the rate of heterozygosity was calculated for US Shar-Pei separately and for a reference group of 24 other breeds . The ratio of heterozygosity in 10 SNP ( ≈1 Mb ) sliding windows between the two groups was used as a measure of relative heterozygosity . To look for regions of homozygosity within the Shar-Pei genome only , the software package PLINK [12] was used . This was performed both for the 50 K array with 50 US Shar-Pei and replicated for 37 Spanish Shar-Pei using 22 , 362 SNPs genotyped with the Illumina CanineSNP20 BeadChip . These data were collected with an Illumina BeadStation scanner and genotypes were scored using GenomeStudio . Regions of homozygosity were defined if shared across all Shar-Pei samples . A case-control association analysis using 17 , 227 SNP common to both the 27K and 50K arrays ( MAF>0 . 05 , call rate >75% ) was performed in Shar-Pei classified as affected ( FSF+A and FSF+ , n = 39 ) or unaffected ( H+ , n = 17 ) by Shar-Pei fever . The software package PLINK [12] was used for the analyses and to ensure genome-wide significance , p-values were corrected for multiple testing . Values used are the max ( T ) empirical p-values obtained after 100 , 000 permutations . To assess whether signals from the two genome scans overlapped , the 39 Shar-Pei with unambiguous phenotypes were analyzed with the 17 , 227 SNPs common to both SNP platforms . Targeted capture of the 1 . 5 Mb candidate region ( CanFam 2 . 0 Chr13: 22 , 937 , 592–24 , 414 , 650 ) was performed using a 385K custom-designed sequence capture array from Roche NimbleGen . Hybridization library preparation was performed as following: Genomic DNA ( 15–20 µg ) was fragmented using sonication; blunting of DNA fragments using T4 DNA Polymerase , Klenow Fragment and T4 Polynucleotide Kinase; adding A-overhangs using Klenow Fragment exo− and ligation of adaptors using T4 DNA Ligase with Single-read Genomic Adapter Oligo Mix ( Illumina ) . All enzymes were purchased from Fermentas and used following manufacturers instructions . Purification steps were performed using QIAquick PCR Purification Kit ( QIAGEN ) . Hybridization was performed following the manufacturer’s instructions without amplification of the fragment library prior to hybridization . Eluted captured DNA and uncaptured libraries were amplified using Phusion High Fidelity PCR Master Mix ( Finnzymes ) and the SYBR Green PCR Master Mix ( Applied Biosystems ) was used to estimate the relative fold-enrichment . Capture libraries with the estimated enrichment-factor of >200 were sequenced using Genome Analyzer ( Illumina ) and obtained sequences were aligned to CanFam 2 . 0 [37] and to the targeted region using Maq assembly ( http://maq . sourceforge . net/ ) [38] . For each individual , sequence coverage was calibrated by dividing the coverage in 100 bp windows by the average coverage for the total region . Three control breeds ( Pug , Neapolitan Mastiff , Standard Poodle ) and two of each type of Shar-Pei ( meatmouth type and traditional type ) were sequenced . The two traditional type Shar-Pei were sequenced at different read lengths but were aligned using the same strict criteria ( allowing two mismatches per read ) and therefore vary in the percentage of mapped reads as well as coverage when compared to the other individuals . Individual 7 ( Table S4 ) was sequenced from whole genome amplified material and this may have impacted the ability to map reads and detect SNPs . This individual was not plotted in Figure 3A , but was used in downstream analyses . All primers used were designed using Primer3 ( http://frodo . wi . mit . edu/primer3/ ) [39] and are listed in Table S6 . PCR and Sanger Sequencing was performed to investigate putative mutations ( ten SNPs and one indel ) and were carried out with 20 ng genomic DNA using AmpliTaq Gold DNA Polymerase ( Applied Biosystems ) following the manufacturer’s instructions . The amplification of the copy number variant ( CNV ) breakpoints was performed with 400 ng of DNA and a Long-range PCR with Expand Long Template PCR System Mix 1 ( Roche ) , cloned using Zero Blunt TOPO Cloning Kit ( Invitrogen ) and plasmid DNA prepared using QIAprep Spin Miniprep Kit ( QIAGEN ) . PCR products and plasmids were sequenced using capillary electrophoresis 3730xl ( Applied Biosystems ) , aligned and analyzed using CodonCode Aligner version 2 . 0 . 6 ( CodonCode ) . Four micrograms of genomic DNA from each sample was digested with BsrGI ( New England BioLabs ) and separated on a 0 . 7% agarose gel . A 910 bp probe ( targeting CanFam 2 . 0 Chr13: 23 , 746 , 12–23 , 747 , 522 ) was used to detect the duplicated region . Estimation of copy number was performed using the comparative CT ( ΔΔCT ) relative quantification method and a calibrator animal ( German Shepherd 95 ) . The duplex reaction contained a primer limited copy number assay ( CNV-E: 300 nM each of forward and reverse primers , 250 nM FAM labeled MGB probe; CNV-748: 50 nM of forward and 300 nM reverse primers , 250 nM FAM labeled MGB probe , Applied Biosystems ) and a reference assay designed to C7orf28B ( 900 nM of forward and reverse primers , 250 nM VIC and TAMRA labeled probe , Applied Biosystems ) . Real Time PCR was performed in quadruplet using 10 ng of gDNA , Genotyping Master Mix ( Applied Biosystems ) and a 7900 HT Real Time PCR machine ( Applied Biosystems ) . The PCR primers used and dogs evaluated can be found in Tables S4 and S1 respectively . Cultures of dermal fibroblasts were established from skin samples of Shar-Pei dogs as described previously [40] . Skin samples were well shaved and cleaned with 70% EtOH/Betadine before biopsy and cell isolation . Fat tissue and blood vessels were removed from the skin and then samples were washed with PBS , cut into small fragments ( 0 . 5 cm2 ) and digested with dispase II solution ( Boehringer Mannheim ) for 16 h at 4°C . The next day , after incubation for 30 min at 37°C in the same solution , the dermis was separated from the epidermis . Washed dermal samples were chopped into 1 mm3 fragments and incubated for 140 min in 15 ml of DMEM per gram of skin containing 30 mg bacterial collagenase ( Gibco ) , 18 mg hyaluronidase , 12 mg pronase , 1 . 5 mg DNAse , supplemented with bovine albumin ( all from Sigma ) and antibiotics . After digestion , cutaneous cells were washed with PBS and grown in a humidified atmosphere at 37°C with 5% CO2 for two days . Medium was changed twice a week and cells were used at passages two-five . RNA extraction from fibroblast cultures was performed as described elsewhere [41] . 500 ng of RNA was reverse transcribed using the High-Capacity cDNA Archive Kit ( Applied Biosystems ) with random primers and following the manufacturer’s instructions . Two assays were designed to target HAS2 and HAS2as cDNA , respectively . Real Time PCR in a volume of 20 ul was performed in duplicate using SYBR Green PCR Master Mix ( Applied Biosystems ) and primers at 300 nM in a 7900 HT Real-Time PCR system ( Applied Biosystems ) with standard cycling . PCR specificity assessment was performed by adding a dissociation curve analysis at the end of the run . Each amplification run contained negative controls . Relative fold-enrichment was performed using the comparative ΔCT-method with Glucose-6-phosphate dehydrogenase ( G6PD ) for normalization . http://pngu . mgh . harvard . edu/~purcell/plink/ http://www . codoncode . com/ http://genome . ucsc . edu/ http://maq . sourceforge . net/ http://frodo . wi . mit . edu/primer3/
Shar-Pei dogs have two unique features: a breed defining “wrinkled” skin phenotype and a genetic disorder called Familial Shar-Pei Fever ( FSF ) . The wrinkled phenotype is strongly selected for and is the result of excessive hyaluronan ( HA ) deposited in the skin . HA is a molecule that may behave in a pro-inflammatory manner and create a “danger signal” by being analogous to molecules on the surface of pathogens . FSF is characterized by unprovoked episodes of fever and/or inflammation and resembles several human autoinflammatory syndromes . Here we show that the two features are connected and have the same genetic origin , a regulatory mutation located close to a HA synthesizing gene ( HAS2 ) . The mutation is a 16 . 1 Kb duplication , the copy number of which correlates with HAS2 expression and disease . We suggest that the large amount of HA responsible for the skin condition predisposes to sterile fever and inflammation . HAS2 was previously not known to associate with autoinflammatory disease , and this finding is of wide interest since approximately 60% of human patients with periodic fever syndrome remain genetically unexplained . This investigation also demonstrates how strong artificial selection may affect not only desired and selected phenotypes , but also the health of domestic animals .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "genetics", "and", "genomics/disease", "models", "genetics", "and", "genomics/genetics", "of", "disease", "genetics", "and", "genomics/animal", "genetics" ]
2011
A Novel Unstable Duplication Upstream of HAS2 Predisposes to a Breed-Defining Skin Phenotype and a Periodic Fever Syndrome in Chinese Shar-Pei Dogs
Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies . Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response . Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome . However , innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated . To create a ranking of severity that would be applicable to innate immunity genes we evaluated 17 , 764 stop-gain and 13 , 915 frameshift variants from the NHLBI Exome Sequencing Project and 1 , 000 Genomes Project . Sequence-based features such as loss of functional domains , isoform-specific truncation and nonsense-mediated decay were found to correlate with variant allele frequency and validated with gene expression data . We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against Online Mendelian Inheritance in Man ( OMIM ) disease stop-gains and frameshifts . The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes . The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease , and complements existing gene-based pathogenicity scores . Specifically , the sequence-based score improves measurement of functional gene impairment , discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes . There is considerable variability in the human immune response to pathogens . The observation of genetic causes of a number of primary immunodeficiencies underscores the fundamental role of variants in immune genes - in many cases resulting in severe , pathogen-specific disorders [1] . A main challenge in the analysis of genome variation today is the assignment of a functional role to rare variants [2] . Here , large numbers of study participants would not necessarily provide the statistical power to associate a genotype with a phenotype . In this context , efforts are put toward to the computational identification of features allowing prioritization of variants for follow-up in genetic and functional analysis . Strategies to attribute a severity score to a variant , recently reviewed in [3] , include approaches based on evolutionary , physico-chemical and structural properties ( Polyphen2 [4] , SIFT [5] ) , methods based on analysis of mutation load ( e . g . the Residual Variation Intolerance Score , RVIS [6] ) , and integrative pipelines [7]–[10] . Of special interest in the study of inter-individual variability in innate immunity is the evaluation of stop-gains and frameshifts . Such variants are prevalent , having an estimated number of 100 to 200 occurrences per human genome [11] , [12] . Stop-gains and frameshifts may lead to functional consequences due to protein truncation , degradation of the transcript by Nonsense-Mediated Decay ( NMD ) [13] and dominant negative influences of protein species . In particular , rare and young variants that have not undergone purifying selection may contribute to burden of disease in a population [14]–[16] . Despite a stop-gain or frameshift variant , however , the function of a protein may be preserved because of limited truncation of functional and structural domains , or because the variant affects only one of the splice forms . A less understood possibility is the occurrence of stop-codon read-through [17] , [18] . Analyses based on gene characteristics such as evolutionary conservation and non-redundancy in the genome [19] , or mutational burden analysis [6] are used to predict the severity of stop-gain and frameshift variants . Herein , we refer to these analyses as “gene-based” . However , innate immunity genes tend to be less conserved and more duplicated than the genome average [20] and other features may be needed to assess functional relevance of a variant . The aim of this study is to explore sequence characteristics that may improve the understanding of the functional consequences of stop-gain and frameshift variants in innate immunity genes . Herein , we will refer to these analyses as “sequence-based” . For this , we first evaluated two sets of publicly available data from a total of 7595 individuals [16] , [21] including gene expression data from 421 of them [22] . Specific sequence features of truncating variants were found to correlate with allele frequency and gene expression levels . These features were used to generate a pathogenicity score that was evaluated through benchmark against OMIM disease variants . The approach was applied to assess functional consequences of stop-gain and frameshift variants in innate immunity genes , with particular attention to antiviral interferon-stimulated genes ( ISGs ) . We analysed gene variant data from a total of 7595 individuals from the NHLBI GO Exome Sequencing Project ( ESP ) [16] and the 1000 Genomes Project [21] . We considered 17764 stop-gain and 13915 frameshift variants collectively affecting 11369 autosomal protein coding genes reliably annotated by the Consensus CDS ( CCDS ) project [23] . The distributions of gene truncating variants according to allele frequency and study are presented in Table S1 . Consistent with previous reports [19] , [24] , we observed that the distribution of stop-gain and frameshift variants along the protein coding sequence of genes is biased by allele frequency ( Figure S1 ) . Variants with very low allele frequency ( MAF≤0 . 001 ) are evenly distributed , with a modest 3′ terminal enrichment . However , the distribution of stop-gain and frameshift variants becomes less uniform with increasing allele frequencies , yet does not show a clear pattern . In contrast , we observed marked distribution trends in association with the following sequence features: ( i ) loss of functional domains; ( ii ) disruption of constitutive exons ( i . e . exons present in all isoforms ) , or of principal isoforms; ( iii ) localization in potential NMD-targeted regions . In comparison to rare truncating variants , common stop-gain and frameshift variants were clearly depleted at positions leading to the loss of a functional domain ( Figure 1A ) . Analysis of splicing-dependent effects was limited to genes with multiple annotated transcripts in CCDS ( n = 5203 ) . We observed an enrichment of common stop-gain and frameshift variants in alternative isoforms ( Figure 1B ) and a depletion of common variants in principal isoforms ( Figure 1C ) . Defining principal isoform on the basis of highest expression level across tissues [25] showed comparable results . We observed that common gene truncating variants occurred less frequently in regions more than fifty nucleotides upstream the last exon-exon junction , possibly triggering NMD-mediated transcript degradation ( Figure 1D ) . For all the features discussed above , gene-truncating variants associated with disease in the Online Mendelian Inheritance in Man ( OMIM ) database exhibited a distribution bias opposite to what was observed for common stop-gain and frameshift variants ( Figure 1 ) . The same trends were observed when ESP and 1000 Genomes variant datasets were analysed separately ( Figure S2 ) . We used expression data from 421 individuals to assess the functional impact of stop-gain and frameshift variants [22] . In particular , we evaluated differences between protein truncating variants localized to NMD-targeted region compared to those that were not . Stop-gains predicted to trigger NMD ( n = 756 ) had a significantly lower expression level ( median Z-score = −0 . 59 ) than stop-gains predicted to escape NMD ( n = 379 , median = −0 . 10 ) and lower than a reference distribution of synonymous variants ( median = −0 . 04 , one-sided Wilcoxon rank-sum test p-value<2 . 2e-16 ) ( Figure 2A ) . Among stop-gains predicted to trigger NMD , singletons ( n = 488 , median Z-score = −0 . 75 ) showed a stronger decrease in expression level compared to non-singletons ( n = 268 , median = −0 . 26 , p-value = 1 . 3e-10 , Figure 2B ) , which is an indication that they represent actual variants and not sequencing or bioinformatics errors . We did not observe a similar reduction when considering 87 of the 172 frameshift variants with expression data mapping to potential NMD-target regions ( median = −0 . 14 , p-value = 5 . 7e-02 ) . To further evaluate a splicing-dependent impact on gene expression levels , we limited the analysis to 301 stop-gains predicted to trigger NMD and affecting genes with multiple isoforms described in CCDS . We observed a significant decrease in gene expression levels of NMD-triggering stop-gains affecting all isoforms ( n = 216 , median = −0 . 64 ) compared to those affecting only a fraction of isoforms ( n = 85 , median = −0 . 22 , one-sided Wilcoxon rank-sum test p-value = 2 . 5e-03 ) ( Figure 2C ) . Similar results were obtained using RPKM normalized expression values ( Figure S3 ) . These observations confirmed the functional impact of stop-gains consistently with predictions of degradation by NMD and current annotation of isoforms . We then evaluated the predictive value for pathogenicity of the sequence-based features characterized in the previous sections: percentage of sequence affected , loss of functional domains , proportion of isoforms affected , principal isoform damage , and NMD-target region . We integrated them into a naïve Bayes classifier ( Table S3 ) and assessed its performance over a dataset of 1160 pathogenic stop-gain variants found in the OMIM database and 125 common stop-gain variants that are not known to be pathogenic . Predictive performance of the pathogenicity score was validated over unseen variants excluded from the learning data using successive random subsampling ( see Methods ) . The classifier was benchmarked against a state of the art gene-based probability score proposed by MacArthur et al [19] . This gene-based score relies on conservation and protein interaction network proximity to genes associated to a recessive disease as predictive features . In the case of stop-gain variants , the performance of the gene-based method was consistent with the reported results in the original work ( Area Under the Curve ( AUC ) = 0 . 83 , Figure 3A ) . Similar ROC curves were obtained with the gene-based score RVIS [6] that provides a measure of the departure from the average number of common functional mutations in genes with a similar amount of mutational burden ( Figure S4 ) . The score based on sequence features alone showed a lower predictive value ( AUC = 0 . 67 ) . However , optimal ROCs were achieved by combining sequence and gene-based scores ( Figure 3 ) . We observe that at a False Positive Rate ( FPR ) of less than 0 . 1 there is no improvement from the combined sequence-based and from the MacArthur gene-based score that used network proximity OMIM recessive disease genes in its design . Improvement at low FPR occurs in the combination of the sequence-based score with RVIS , which does not rely on OMIM annotations . While the AUC improvement is modest , it is consistent across two datasets ( ESP and 1000 Genomes ) , over the two gene-based scores , and for the two types of variants ( stop-gains and frameshifts ) , Figure S4 . These results demonstrate that sequence features can be incorporated as an additional source of information to improve current pathogenicity prediction . The marginal improvement obtained when scores were combined motivated us to explore whether the different approaches were capturing independent information . We observed a very low correlation between gene-based and sequence-based scores ( Spearman rank correlation <0 . 13 , p-value: <2 . 2e-16 ( [0 . 10 , 0 . 13] 95% CI from 10 , 000 bootstrap samples ) . The reason for this observation is that the various scores are based on different criteria: gene conservation and centrality ( MacArthur 2012 ) , burden of variation ( RVIS ) and sequence features ( current work ) . Correlations were not increased in analyses limited to OMIM disease variants ( Figure S5 ) . Based on these results we explored the potential for complementarity across scores . First , we analysed whether the sequence-based score was better powered to detect functional impact as measured by effect on gene expression . We observed a stronger correlation with expression levels for the sequence-based score ( Spearman rank correlation = 0 . 21±0 . 03 , p-value: <5e-12 ) than either gene-based scores ( 0 . 06±0 . 04 , p-value>0 . 05 for MacArthur 2012 score and 0 . 13±0 . 03 , p-value<5e-05 , for RVIS score ) , Figure 4 . Second , we analysed OMIM genes that carry variants annotated as pathogenic in OMIM as well as unknown or non-pathogenic variants . Here , the variants are scored differently using a sequence-based approach , while all share the same gene-based score . Figure 5 depicts this situation for 95 OMIM disease genes carrying multiple stop-gains . The genes with the highest pathogenicity gene-based scores also carried variants with very low severity as determined by a sequence-based score . Third , we checked whether the performance of the sequence-based score varies depending on the degree of gene conservation , as measured by dN/dS ratio in the same set of OMIM disease genes . Figure 6 shows that , for genes below the protein-coding genome average dN/dS ( 0 . 261 ) , the MacArthur and RVIS gene-based scores resulted in higher pathogenicity estimates than the sequence-based score; however without discriminating between pathogenic and non-pathogenic/non-annotated variants . In contrast , for genes with dN/dS≥0 . 261 , the sequence-based score performed similarly for pathogenic variants while attributing less pathogenicity to non-pathogenic/non-annotated variants of the same gene ( Wilcoxon signed rank test p-value<0 . 012 ) . We note that OMIM variants used here were not considered for learning in the Bayesian classification ( see Methods ) . From these results , we conclude that the two types of scores are complementary . Specifically , the sequence-based score improves measurement of functional gene impairment , discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes . To test the ability to rank the functional consequences of gene truncating variants in innate immunity genes , we analysed the distribution of both the sequenced-based and gene-based pathogenicity scores in 1503 genes involved in innate immunity [20] , including 387 interferon stimulated genes ( ISGs , [26] [27] ) . We identified 856 innate immunity genes , including 230 ISGs , carrying rare gene truncating variants ( MAF<1% ) . Globally , innate immunity and OMIM genes ranked higher than the background set of the genome for both scores ( Figure 7 and Figure S6 ) . However , the highest scores were obtained for stop-gain variants in OMIM genes , particularly for variants in innate immunity genes that are not observed in the ESP or the 1000 Genomes Project samples ( Figure 7 ) . The latter result is consistent with their extreme rarity and severity . We note that OMIM variants used here for validation were not considered for learning in the Bayesian classification ( see Methods ) . Despite their apparent agreement in Figure 7 , correlation between the sequenced-based and gene-based pathogenicity scores was very low ( Spearman correlation below 0 . 31 in all sets of genes analyzed ) indicating that both scores provide complementary information . Given the observation that truncating variants can be associated with important differences in functional impact , we estimated the number of individuals in the study population that carried variants consistently annotated as highly pathogenic by one or several scores . Among 7595 individuals and 1503 innate immunity genes , 33 individuals carried rare ( MAF<0 . 01 ) stop-gains and 85 carried rare frameshifts that scored with high severity ( pathogenicity rank percentile < = 20% ) in all scores ( sequence-based , MacArthur 2012 and RVIS ) . For the smaller set of 387 ISGs , we identified 8 individuals carrying rare stop-gains and 4 carrying rare frameshifts with high severity in all scores . We then focused on truncating variants in genes associated with viral inhibition in cellular assays [26] , [27] . A total of 13 out of 42 genes carried such variants ( observed in at least 2 people ) , which were very rare overall ( MAF<0 . 0053; Table S4 ) . Specifically , two genes had variants with high predicted pathogenicity based on both scores: MX1 which controls Influenza A virus in vitro and HPSE which is involved in metapneumovirus , respiratory syncytial virus and yellow fever virus control . While the gene-based scores were by definition identical for all variants affecting a same gene , the sequenced-based score sharply distinguished the variants according to different predictive pathogenicity ( Table S3 ) . This observation was consistent with the observed differences in gene expression levels available for some of the variants . Numerous Mendelian disorders leading to severe infection are caused by rare functional variation of innate immunity genes [1] . Here , we identified multiple stop-gain and frameshift variants in this family of genes in the general population , especially among interferon stimulated genes . These are generally heterozygous rare variants that may or may not result in clinical consequences . To understand the nature and possible consequences of these variants , we first analyzed their characteristics at the genome level . The genome-wide analysis of more than 30'000 variants provided the statistical power to identify sequence specific features for severity and to build a pathogenicity score . This sequence-based pathogenicity score was then applied to the analysis of variants in interferon stimulated genes with antiviral activity . We observed that the distribution of stop-gain and frameshift variants in the sequence is biased by the allele frequency . Thus , we speculated that tolerance to these variants would reflect their impact on functional domains , on isoforms , and on degradation by NMD . Our results clearly underscore that rare stop-gain and frameshift variants are subject to purifying selection [15] , [28] . Indeed , those variants are kept at very low frequency when they result in the loss of functional domains , when they are located in NMD-targeted regions , or when they disrupt the principal isoform or constitutively spliced exons . The potential molecular impact of heterozygous rare truncating variants was examined using mRNA expression data [22] . Stop-gain variants predicted to trigger NMD degradation resulted in a measurable decrease in global expression levels . This is in line with recent findings showing a reduction in expression levels of the variant allele compared to the reference allele in heterozygous individuals when stop-gains occur in NMD target regions [19] , [22] , [29] . In all analyses , singleton variants associated with highest functional impact , consistent with higher severity of lower frequency rare variants and indicative of general accuracy in variant calling . A possible limitation to our analysis is that we use lymphoblastoid cell line expression data [22]; the impact of specific variants may be allele and tissue-specific [30] . To further explore the functional consequences of gene truncating variants , we analysed the collective contribution of various severity features to the prediction of pathogenicity . For this we built a model on a learning set that was validated through benchmark against OMIM disease variants . These sequence-based features improved the ranking of OMIM variants when added to a predictive model that use gene-based features . Specifically , the sequence-based score appeared particularly suited for functional prediction ( gene expression ) and for the analysis of variants in less conserved genes . We provide a web-based tool ( http://nutvar . labtelenti . org/ ) allowing the analysis of user-provided variants . We hypothesized that such a sequence-based approach would be of particular interest for the study of innate immunity genes because , as a group , these genes tend to be less conserved than the genome average and hence need special consideration . The analysis showed that our sequence-based score is able to rank variants in innate immunity genes according to their pathogenicity and provides complementary information to previously proposed gene-based scores . Indeed we found that in the case of the antiviral genes MX1 and HPSE , truncating variants ranked very highly in pathogenicity on the basis of gene-based scores while important differences were observed at sequence level suggesting significant differences in functional impact . For example the MX1 stop-gain rs35132725 exhibits all the features of severity and a negative effect on expression levels . In contrast , the MX1 frameshift rs199916659 is not expected to alter protein function . Overall , among 387 ISGs examined in 7595 individuals , more than half of the genes carried a stop-gain or frameshift variant in 1 or more individuals , usually at low allele frequency . Of these , 12 individuals carried truncating variants consistently interpreted as highly pathogenic by the three evaluated scores . This rate of 1 . 5 per 1000 carriers could be a genomic substrate of occasional homozygosity with unknown phenotypic consequences . We then evaluated those instances that concerned genes for which an antiviral effect has been established through a gain-of-function screen in vitro . This last analysis provided a short list of genes and reliable variants that could modulate responses to various viruses , including common human pathogens such as influenza . Of note , the in vitro virological inhibition data represents a technical readout , and there are a number of considerations that may diminish the in vivo consequences of these rare variants , including issues of redundancy and robustness in innate immunity networks , and the possibility of stop codon read-through . There are other limitations to the predictions based on sequence features , particularly the incomplete understanding of the functional role of alternative isoforms and their tissue specificity . Rare gene truncating variants predicted to have high pathogenicity risk in innate immunity genes should be examined for phenotypic consequences in the population . Exceptional homozygous individuals may be at risk for severe infection while heterozygous individuals could have adequate compensation or subtler phenotypes . However , there is increasing awareness of the relevance of haploinsufficiency [31] , and thus , it is not excluded that heterozygosity may be associated with apparent clinical phenotypes . Thus , the next step should include assessment in vivo of high risk variants , which requires the capacity to re-contact carrier individuals for collection of biological specimens and in-depth phenotypic assessment . Two genetic variant and annotation datasets were used: 1 ) 6503 individuals from the NHLBI GO Exome Sequencing Project ( ESP ) [16] and 2 ) 1092 individuals from the 1000 Genomes Project [21] . Variants ( SNPs and INDELs ) and annotations for the ESP exomes ( file ESP6500SI-V2-SSA137 . dbSNP138-rsIDs . snps_indels . txt . tar . gz ) were downloaded from the Exome Variant Server , NHLBI GO Exome Sequencing Project , Seattle , WA ( http://evs . gs . washington . edu/EVS/ , accessed July 2013 ) . Only variants assigned to the following categories were considered for further analysis: “stop-gained” ( including “stop-gained-near-splice” ) , “frameshift” , “coding-synonymous” ( including “coding-synonymous-near-splice” ) and “missense” ( including “missense-near-splice” ) . One base was added to the genomic coordinates reported for frameshifts in the ESP dataset to consider the actual location of the insertion/deletion event ( http://evs . gs . washington . edu/EVS/HelpDescriptions . jsp ? tab=tabs-1 ) . Variants and genotypes from the 1000 Genome Project [21] correspond to phase 1 version 3 of the 20110521 release ( ftp://ftp . 1000genomes . ebi . ac . uk/vol1/ftp/release/20110521/ , accessed August 2013 ) . SnpEff Variant Analysis software [32] ( version 3 . 3h build 2013-08-11 ) was used to annotated 1000Genome variants against SnpEff's pre-built human database ( GRCh37 . 71 ) . SnpEff categories labeled with errors or warnings in the EFF field were disregarded . Only variants assigned to the following categories were considered for further analysis: “stop_gained” , “frame_shift” , “synonymous_coding” ( including “synonymous_start” and “synonymous_stop” ) and “non_synonymous_coding” ( missense ) . Hardy-Weinberg equilibrium ( HWE ) was tested with R package GWASExactHW ( http://cran . r-project . org/web/packages/GWASExactHW/ , version 1 . 1 ) . A fraction of variants significantly deviated from HWE ( Fisher's exact p-values<0 . 05 ) , mainly due to an excess of homozygous rare allele calls , likely indicating technical artifacts . All variants not in HWE were filtered out . When both datasets where considered together , the following criteria were adopted: i ) Genomic coordinates of frameshift variants reported by both datasets were treated as reported for the ESP dataset . ii ) Allele frequencies and HWE of variants present in both datasets were derived from the sum of individuals from both studies; allele frequencies of variants present in only one dataset were taken as originally reported by the corresponding dataset . To exclude bias due to previous assumptions , results were reproduced for the two datasets considered separately as well as combined . For the combined analysis allele frequencies of variants present in only one dataset are estimated over all 7593 individuals . The analysis pipeline implemented to annotate genetic variants is depicted in Figure S7 . We restricted the analysis to protein coding genes and transcripts annotated by the Consensus CDS ( CCDS ) project [23] ( ftp . ncbi . nlm . nih . gov/pub/CCDS/ , Release 12 04/30/2013 ) . We considered only variants affecting a core set of human protein coding regions consistently annotated and of high quality . Only genes on the 22 autosomes were retained and only CCDS entries with a public status and an identical match were kept . Domains of human protein sequences were retrieved from the InterPro database [33] ( release 44 . 0 , 23/09/2013 ) . Data were downloaded through BioMart Central Portal [34] ( http://central . biomart . org/ , accessed 04/10/2013 ) , filtering fragments and considered domain boundaries corresponding to InterPro “supermatches” . Mapping from InterPro coordinates on UniProt protein sequences to CCDS sequences was done by exact matching of the complete amino acid sequences using UniProt database ( release 2013_07; [35] ) . A position within a protein coding gene was considered alternatively spliced if it was shared by only a fraction of all protein coding transcripts reported by the Consensus CCDS Project for that gene . Otherwise it was considered constitutively spliced for the purpose of the study . Annotation of principal isoforms used APPRIS ( [36]; file APPRIS-g15 . v3 . 15Jul2013/appris_data . principal . homo_sapiens . tsv accessed 03/09/2013 at URL: http://appris . bioinfo . cnio . es ) , a computational pipeline and database for annotations of human splice isoforms . APPRIS selects a specific transcript as principal isoform , i . e . the one computationally predicted as responsible of the main cellular function , being expressed in most of the tissues or developmental stages and more evolutionary conserved . Selection of the principal isoform is based on protein structure , function and interspecies conservation of transcripts . As an alternative definition of principal isoform , we identified the transcript with a recurrent highest expression level across tissues as provided by [25] . We accounted for nonsense-mediated decay ( NMD ) following HAVANA annotation guidelines v . 20 ( 05/04/2012 ) ( http://www . sanger . ac . uk/research/projects/vertebrategenome/havana/assets/guidelines . pdf ) , Specifically , the NMD-target region of a transcript was defined as those positions more than 50 nucleotides upstream the 3′-most exon-exon junction . Transcripts bearing stop-gain variants at these regions are predicted to be degraded by NMD [13] . Geuvadis RNA sequencing data from 421 lymphoblastoid cell lines from the 1000 Genomes Project ( phase 1 version 3 of the 20110521 release , see above; [21] ) were obtained from Lappalainen et al . 2013 [22] . Gene expression quantifications of protein-coding genes were downloaded from EBI ArrayExpress accession E-GEUV-1 ( accessed 05/11/2013 ) . Analyses were independently performed on both RPKM and Peer-factor normalized RPKM values . As a measure of the impact of a variant on expression level , we calculated the average Z-score of the expression level in cells from individuals carrying the variant compared to all samples . We used a naïve Bayes classification scheme in order to derive a probability of pathogenicity for a given variant using the following sequence-based features: maximum transcript length affected , maximum percentage of domain truncation , number of isoforms and ratio of isoforms affected , truncation of the principal isoform and localization in an NMD-target region . Solely for the purpose of the classifier , missing values were imputed to zero for percentage of domain truncation and to the longest isoform for principal isoform annotation . We defined a matrix XN×K of K sequence-based features for N variants of a given type in the dataset and a binary vector cN×1 annotating variants as benign or pathogenic . A new variant , y1×K , is evaluated using maximum likelihood estimates for class-specific means from the annotated data , and a common intra-class variance vector ( except for binary features ) . We estimate the variance vector as ν = E[ ( xi - μci ) 2] , where xi is the ith row in matrix X and μci is the mean vector corresponding to the class indicated by ci , . We assigned a pathogenic class with 1 and benign class with 0 . Assuming a prior probability of pathogenicity , p1 , posterior probability of pathogenicity can be evaluated as:where p0 = 1-p1 is the prior probability of being benign and θ = {μ1 , μ2 , ν} is the set of model parameter vectors . The conditional likelihood of y for a given class is assumed to factorize as product of K likelihoods corresponding to the K sequence features available ( naïve Bayes assumption ) . We used normal , and Bernoulli likelihood functions to model continuous and binary features respectively . It is straightforward to show the ranking produced from this posterior probability does not depend on the prior probability p1 as long as it is larger than zero and it is equal for all the mutations under consideration . As reference throughout the work , and as a learning set for the predictive scores ( ROC analyses ) , we used a catalogue of pathogenic mutations from the Online Mendelian Inheritance in Man [37] database . Only genes with a cytogenetic location ( genemap2 . txt accessed 18/10/2013 at OMIM: ftp . omim . org ) and with a gene status of confirmed or provisional were kept . For each gene with an associated OMIM number , all allelic variants with a “live” status and a dbSNP identifier were obtained through the OMIM API server ( http://api . omim . org/ ) . We used Ensembl Variation [38] ( Ensembl release 71 , April 2013 , dataset Homo sapiens Short Variation , SNPs and indels , GRCh37 . p10 , accessed 25/10/2013 at http://apr2013 . archive . ensembl . org/biomart/martview/ ) to obtain the genomic coordinates for each dbSNP identifier together with the clinical significance of each specific allele as reported by ClinVar and dbSNP following OMIM guidelines ( http://www . ncbi . nlm . nih . gov/clinvar/docs/clinsig/ ) . Only variants with a dbSNP identifier annotatted as “pathogenic” and mapping to a unique genomic location were kept for further analysis . SnpEff Variant Analysis was then used to re-annotate the selected pathogenic variants as described above . We benchmarked three different pathogenicity scores using all stop-gain variants from the OMIM dataset as positive ( pathogenic ) , and all common variants ( MAF≥1% ) not present in OMIM dataset as negative ( benign ) variants . The sequence-based score is the posterior probability calculated from the naïve Bayes classification scheme described in previous section using an empirical prior for pathogenicity . We used two different gene-based scores: first the probability provided by MacArthur et al [19] for prioritization of variants derived from two gene-level features: conservation and protein interaction network proximity to genes associated with a recessive disease . And second the Residual Variation Intolerance Score ( RVIS ) [6] that provides a measure of the departure from the average number of common functional mutations in genes with a similar amount of mutational burden . RVIS pathogenic score was assessed as f ( -RVIS ) , where f ( . ) is the logistic function . The joint score was defined as the product of the sequence-based score and one of the two previously defined gene-based scores . This joint score can be interpreted as the joint probability of a pathogenic mutation in a gene assuming conditional independence of the two probability scores . The receiver operating characteristic ( ROC ) curve was derived using random subsampling validation iterations . In each iteration , we use 75% of the data to train the classifier and use the remaining 25% for validation . This was done 10000 times , to minimize the Monte Carlo error , and validation set scores were combined to calculate the ROC curve . The same procedure was applied to frameshift variants . Except for ROC analyses , sequence-based scores used throughout the work were derived from the learning set described above excluding both i ) OMIM pathogenic variants reported in ESP and 1000 Genomes Project and ii ) OMIM pathogenic variants affecting innate immunity genes and interferon stimulated genes . Genome-wide codon alignments of orthologous genes for nine primate species ( human , chimpanzee , gorilla , orangutan , macaque , marmoset , tarsier , bushbaby , and mouse lemur ) were collected from Ensembl v57 . We assessed dN/dS estimates using both Ensembl Compara's protein-based alignments , and DNA-based alignments of primate sequences generated from genomic DNA alignments . Sitewise Likelihood Ratio test [39] was used to calculate the overall dN/dS for a given gene based on a one-ratio model where all sites have the same dN/dS value . A representative list of 1503 human innate immunity genes [20] was used . Within this list , we further analyzed 387 interferon stimulated genes ( ISGs ) [26] . Additionally , we focused on those ISGs showing antiviral activity against 18 viruses ( including important human pathogens such as HIV-1 , hepatitis C virus , influenza virus and other respiratory viruses ) upon overexpression in in vitro cellular assays [26] , [27] . We first identified all ISGs carrying gene truncating variants , and then characterized the subset of those genes associated with more than 50% viral inhibition in the cellular assays .
There are well-characterized severe immunodeficiencies associated with loss-of-function variants in innate immunity genes . Genome sequencing projects identify rare stop-gain and frameshift variants in innate immunity genes whose phenotype is uncharacterized . Current methods to estimate the severity of rare stop-gains and frameshifts are based on evolutionary conservation of the gene , the likelihood for redundancy in its function or mutational burden . These parameters are not always applicable to innate immunity genes . We evaluated sequence-level characteristics of more than 30'000 stop-gains and frameshifts and prioritized variants according to their predicted functional consequences . Our scoring approach complements existing tools in the prediction of innate immunity OMIM disease variants and associates with functional readouts such as gene expression . In this framework , we show that many individuals do carry highly pathogenic variants in genes participating in antiviral defense . The clinical assessment of these variants is of significant interest .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "sequencing", "techniques", "sequence", "analysis", "mutation", "infectious", "diseases", "medicine", "and", "health", "sciences", "personalized", "medicine", "genetics", "biology", "and", "life", "sciences", "population", "genetics", "molecular", "biology", "techniques", "computational", "biology", "evolutionary", "biology", "viral", "diseases", "molecular", "biology", "clinical", "genetics" ]
2014
Analysis of Stop-Gain and Frameshift Variants in Human Innate Immunity Genes
Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world . Regulatory evolution , in which non-coding DNA is mutated to create new regulatory nodes , also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis . To survive in the host environment , Salmonella enterica uses a type III secretion system and effector proteins , which are activated by the SsrA-SsrB two-component system in response to the host environment . To better understand the phenomenon of regulatory evolution in S . enterica , we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes . Using ChIP-on-chip , cDNA hybridization , and comparative genomics analyses , we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes . Further , we used a genetic screen and computational analyses integrating experimental data from S . enterica and sequence data from an orthologous regulatory system in the insect endosymbiont , Sodalis glossinidius , to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB . Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB . These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host . Precise gene regulation is crucial to the successful activation and execution of virulence programs for all pathogenic organisms . The acquisition of genes through horizontal gene transfer , a widespread means of bacterial evolution [1] , requires a process to integrate new coding sequence into pre-existing regulatory circuitry . Silencing of horizontally-acquired genes by DNA binding proteins like H-NS is one way some incoming genes are initially controlled [2] , [3] , which can then be subject to regulatory evolution by mutating cis-regulatory operator regions to select for optional gene expression . The eventual promoter architecture selected to deploy virulence genes is often modular and should reflect a design that maximizes organismal fitness while limiting fitness trade-offs and antagonistic pleiotropy [4] . Both simulated [5] and functional experiments [6] , [7] show that mutation of cis-regulatory sequences can be rapid , and that plasticity - the degree to which regulatory mutation can perturb the larger gene network - can be well tolerated in bacterial systems . Promoter architectures that control quantitative traits such as bacterial virulence are , in fact , modular and evolvable [8] . For instance , Salmonella enterica has a multi-faceted pathogenic strategy fine-tuned by several transcriptional regulators . Intracellular survival and persistence of Salmonella requires a type III secretion system ( T3SS ) encoded in a horizontally-acquired genomic island called Salmonella Pathogenicity Island-2 ( SPI-2 ) [9] , [10] . T3SS are complex secretion machines that deliver bacterial effector proteins directly into host cells through an injectisome during infection [11] , [12] . Several ancestral regulators control the genes in the SPI-2 genomic island including the two-component systems EnvZ-OmpR and PhoQ-PhoP , and the regulatory protein SlyA [13] . SsrA-SsrB is another two-component regulatory system co-inherited by genetic linkage with the SPI-2 locus that is essential for gene expression in SPI-2 [14]–[16] . SsrA is a sensor kinase activated in the host environment that phosphorylates the SsrB response regulator to create an active transcription factor needed for spatiotemporal control of virulence genes [13] , [17] . In the Salmonella genus , the SPI-2 genomic island is found only in pathogenic serotypes of Salmonella enterica that infect warm-blooded animals and is absent from Salmonella bongori , which colonizes cold-blooded animals [18] . It is generally accepted that SPI-2 was acquired by Salmonella enterica after divergence from S . bongori , providing a useful pedigree to study regulatory evolution influenced by SsrB . We recently demonstrated the evolutionary significance of cis-regulatory mutations for pathoadaptation of Salmonella enterica serovar Typhimurium ( S . Typhimurium ) to an animal host [19] . Our focus was on SsrB because of its broad conservation among the pathogenic Salmonellae and its essentiality for animal infection , suggesting it coordinates fundamental aspects of Salmonella pathogenesis beyond the SPI-2 genomic island . In this study we investigated how regulatory evolution assimilates horizontally acquired and ancestral genes into the SsrB regulon on a genome-wide scale using an integrated set of experimental methods . Combining our data with previous biochemical work , along with comparative genomic analyses with an orthologous T3SS-encoding genomic island in the tsetse fly endosymbiont , Sodalis glossinidius , we reveal the flexible DNA palindrome that distributes SsrB in the genome to influence transcriptional activation of the SPI-2 T3SS and almost all of its accessory effector proteins . Our data uncovers the principal SsrB circuitry that appears to have been conserved to support multiple bacterial lifestyles , including parasitic and mutualist symbioses . To begin to understand regulatory evolution and network expansion of the SsrB response regulator , we profiled the transcriptome of an ssrB mutant and compared it to S . Typhimurium wild-type cells grown in an acidic minimal medium that activates the SsrA-SsrB two-component regulatory system [20] . We identified 133 genes that were significantly down-regulated in the ssrB mutant [z <−1 . 96] [21] ( Table 1 ) . This included almost all genes in the SPI-2 genomic island as well as effector genes encoded throughout the genome ( Dataset S1 ) . Next , we performed a Clusters of Orthologous Groups ( COG ) analysis [22] on the 118 genes that had an ortholog in the annotated genome of S . Typhimurium strain LT2 [23] . Among these , 45 genes lacked a functional COG assignment and the 73 remaining genes were distributed among 86 COGs ( Figure 1 ) . The majority of functions in the latter groups are in transport , secretion , and trafficking of cellular components in addition to protein and membrane modification . The SsrA-SsrB system was acquired by horizontal gene transfer into the S . enterica species after divergence from what is now extant S . bongori . As such , S . bongori has evolved in the absence of SsrA-SsrB and its regulatory architecture has not been influenced by it . Orthologous genes ancestral to both species but regulated by SsrB in S . enterica provide evidence for network expansion and regulatory evolution that we previously showed can be mapped to a single cis-input location by using functional and comparative genomics [19] . To expand on this , we used a reciprocal BLAST-based analysis and identified 47 orthologs in S . bongori among the 133 genes whose transcription was down-regulated in an ssrB mutant ( Table 1 ) . In ΔssrB cells , the mean fold-change of the orthologous genes ( −6 . 1-fold ) was subtler than for the S . enterica-specific gene set ( mean −21 . 2-fold ) , which included the T3SS and associated effector genes ( Dataset S1 ) . We also determined the distribution of down-regulated genes among genomic islands [24] , including prophages , pathogenicity islands ( SPI-islands ) and additional regions of difference ( ROD ) between S . enterica and S . bongori ( Dataset S2 ) . For this we used a BLAST-based comparison of genome-wide synteny between S . Typhimurium and S . bongori and identified 50 ROD that included 17 previously reported SPI-islands and prophages . Of the 133 down-regulated genes identified , 56 were present within genomic islands ( Table 1 ) , with a mean change in gene expression of −25 . 3-fold in ΔssrB cells . To examine SsrB allocation on the chromosome in vivo , we isolated functional SsrB-DNA interactions using chromatin immunoprecipitation and examined the bound DNA by chip analysis ( ChIP-on-chip ) using an S . Typhimurium SL1344 array containing 44 , 021 probes . With this method , we identified 256 significant interaction peaks distributed throughout the genome that were enriched under SsrB-activating conditions and with interaction scores three standard deviations greater than the mean probe score ( Figure 2A and Table 1 ) . Of these 256 peaks , 126 ( 49% ) occurred within coding regions of genes ( CDS ) and 130 ( 51% ) were in intergenic regions ( IGR ) . Given the strong influence of SsrB on horizontally acquired genes ( Table 1 ) , we plotted the ChIP-on-chip data against all genomic islands in S . Typhimurium SL1344 . From this analysis , 62 of 256 SsrB binding peaks ( 24 . 3% ) occurred within genomic islands ( Figure 2B ) . SsrB ChIP peaks were observed upstream of previously identified SsrB regulated genes indicating that our ChIP-on-chip data captured functional interactions ( Dataset S3 ) . To generate a consensus set of SsrB regulated genes , we performed an analysis to identify operons in the S . Typhimurium SL1344 genome that encoded at least one gene down-regulated in ΔssrB cells and that possessed an SsrB binding peak in the upstream regulatory region as defined by our ChIP-on-chip analysis . From this , the 133 down-regulated genes mapped to 86 operons , 49 of which had an SsrB interaction upstream or within the first gene of the operon ( Table 2 ) . This analysis captured all five reported operons in the SPI-2 genomic island in addition to ten operons outside of this island that encode SPI-2 translocated effectors . In order to rigorously evaluate our genome-wide functional genomics data , we compared it against traditional biochemical experiments describing SsrB-DNA interactions at the SPI-2 locus . Previous data reported SsrB footprints upstream of 6 genes in SPI-2: ssrA , ssrB , ssaB , sseA , ssaG , and ssaM [25] , [26] . Our ChIP-on-chip data showed discrete SsrB binding at all of these promoters except for the promoter reported to be between ssrA and ssrB [25] ( Figure 3 ) . We attempted to verify functional activity at this site , but could not using transcriptional fusions ( data not shown ) . Our data also identified three additional SsrB binding peaks upstream of sseA , within the CDS of ssaJ , and in the IGR upstream of ssaR ( Figure 3 ) . Functional interactions were confirmed for sseA and ssaR in subsequent reporter experiments described below . Previous attempts by others to identify a conserved SsrB DNA recognition motif have been unsuccessful . To overcome this , we employed a bacterial one-hybrid screen originally developed to define binding site preferences for eukaryotic transcription factors [27] . We fused the DNA binding domain of SsrB ( SsrBc ) to the α-subunit of RNA polymerase and screened a prey library of ∼108 DNA molecules previously counter-selected against self-activation ( Figure 4A ) . We used the PhoP response regulator from E . coli as a control because a DNA recognition sequence for it was known [28] . Bait-prey combinations surviving selection on medium lacking histidine were purified , and preys were sequenced and analyzed using the motif-finding program MEME [29] . From 189 unique sequences isolated for SsrBc , over 80% contained a degenerate consensus motif , mCCyTA ( Figure 4B ) . In control screens with the PhoP-αNTD fusion , the PhoP box sequence ( G/T ) GTTTA was identified in 11% of sequenced preys ( 12/109 , data not shown ) but this sequence was never captured by SsrB-αNTD and vice versa , demonstrating specificity of the bacterial one-hybrid system for prokaryotic regulatory proteins . Next , we examined our ChIP-on-chip data for the presence of a conserved regulatory motif . We extracted sequence data from the local maxima of the 256 binding peaks and analyzed the sequences with the computational program MDscan [30] . Using the highest-ranking probes to generate an initial prediction followed by lower-ranking probes for refinement , this analysis identified motifs that represented either the forward or the reverse complement of the consensus sequence ACmTTA , which shares consensus with the motif identified in the bacterial one-hybrid screen ( Figure 4B ) . We identified variations of this motif within footprinted regions of SsrB-regulated promoters [25] , , however sequence degeneracy made it difficult to precisely map the input functions . The analysis of regulatory evolution is particularly challenging because it is difficult to distinguish neutral stochastic change from functional divergence . To solve this problem in the context of mapping the SsrB binding element , we used comparative genomics to search for conserved promoter architecture in another organism with a similar genomic island to Salmonella SPI-2 . The tsetse fly endosymbiont Sodalis glossinidius contains the Sodalis Symbiosis Region-3 ( SSR-3 ) that is similar in content and synteny with the S . enterica SPI-2 locus [31] . Gene conservation includes the entire T3SS structural module extending to the regulatory genes ssrA-ssrB and all other genes except the effectors sseF and sseG , which are not present in Sodalis SSR-3 . We aligned the sequences of the five mapped promoters in SPI-2 with the orthologous SSR-3 regions to identify local conservation . Highly conserved sites within the promoters were restricted to regions previously footprinted by SsrB [25] , [26] , whereas adjacent sequence showed substantial drift ( Figure 4C ) . Within the conserved sites we identified a heptameric sequence in 7-4-7 tail-to-tail architecture that created an 18-bp degenerate palindrome . This palindrome was found in all SPI-2 and SSR-3 T3SS promoters with the exception of the sseA promoter that had only one reasonably well-conserved heptamer in the footprinted region ( Figure 4C and Figure S1 ) . Interestingly , two copies of the palindrome occur upstream of the ssrA-ssrB operon in S . Typhimurium within the same footprint , and the conservation of either site in Sodalis was weak . Evaluation of the heptamer motif in the palindrome showed high similarity to the motifs identified by the bacterial one-hybrid screen and the ChIP-on-chip experiments ( Figure 4B and 4D ) , giving us confidence that we had identified the major recognition module for transcriptional input by SsrB . In accord with a previous observation [26] , there was not a strict requirement in the spacing between the SsrB binding site and the downstream transcriptional start site . The presence of a conserved palindrome sequence in SPI-2 promoters and in related sequences from the endosymbiont S . glossinidius suggested that regulatory input by SsrB was through a palindrome sequence architecture . However , other lines of evidence suggested that the recognition site architecture was flexible in nature: ( i ) our bacterial one-hybrid screen isolated functional single hexamer sequences , ( ii ) the SsrB footprint at the naturally evolved sseA promoter within SPI-2 [26] contained only one reasonably well-conserved heptamer , and ( iii ) degenerate or non-ideal palindromes exist in the genome . In order to deconstruct this architecture , we designed a set of experiments to test the palindrome's tolerance to mutation . We chose the ssaG promoter for these experiments because 16 of 18 bases were identical between SPI-2 and SSR-3 from S . glossinidius , differing only in the 4-bp spacer between heptamers ( Figure 4C ) . We mutated the palindrome in a series of transcriptional reporters that were otherwise identical to the evolved ssaG promoter ( Figure 5A ) and promoter activity was compared to that of a wild-type palindrome sequence . Variants in which the first half-site ( 7′ ) or second half-site ( 7″ ) was deleted produced similar transcriptional activity to the wild-type palindrome , verifying that a single well-conserved heptamer is sufficient for transcriptional input under these experimental conditions ( Figure 5B ) . Deletion of the 4-bp spacer sequence between the heptamers - the most degenerate element of the palindrome - also generated wild-type promoter activity . However , the orientation of individual heptamers was essential for transcriptional input since rewiring the palindrome in any head-to-head orientation produced negligible promoter activity . However , if the two half sites were swapped front-to-back so that they maintained tail-to-tail orientation ( construct labelled “Reverse” in Figure 5 ) , wild-type promoter activity was restored . Precise deletion of the entire 18-bp palindrome lead to ∼10% residual activity in wild-type cells , which was reduced to less than 1% in an ssrB mutant ( Figure 5C ) . To determine whether the remaining 10% transcriptional activity was a result of an SsrB-dependent feed-forward mechanism or transcriptional read-through of our chromosomally integrated reporter , we constructed an ectopic deletion reporter . Assessment of reporter activity for this construct in addition to wild-type constructs in wild-type and ssrB mutant backgrounds showed a similar level of activity to the ssrB mutant ( Figure 5D ) . The results for the half-site deletion constructs , which retained activity similar to wild type , were unexpected . Therefore , we compared the sequences generated upon mutation against a consensus palindrome matrix generated from all SPI-2 and other identified putative elements . The 7′-4-X , X-4-7″ and 7′-X-7″ mutations introduced a number of base transitions and transversions never occurring in the matrix , however the modified 7 base pair heptamer retained 4–5 naturally-occurring bases along with the unchanged wild-type sequence in the other heptamer ( Figure S2 ) . The possibility existed that this modified heptamer , although now weaker in consensus , could still be sufficient for recruitment of a functional form of SsrB when paired with the other wild-type heptamer . To test this , we created an additional ectopic transcriptional fusion construct in which the left half ( 7′ ) of the palindrome was mutated to bases never occurring in the consensus matrix . When tested in promoter activity experiments , this reporter was unable to activate transcription and was identical to the X-X-X mutant construct ( Figure 5D ) . Salmonella SsrB and the Sodalis ortholog ( SG1279 ) are 69% identical and 81% similar at the amino acid level . All of the critical residues in the dimerization helix and HTH motif required for specific transcriptional activity by SsrB [32] are conserved in the Sodalis ortholog ( Figure S3 ) . To demonstrate a functional role for the palindrome identified in Sodalis , we engineered luciferase transcriptional reporters that either contained ( 7′-4-7″ ) or lacked ( X-X-X ) the identified palindrome from the Sodalis SG1292 promoter ( ssaG ortholog ) and transformed them into wild-type S . Typhimurium and an ssrB mutant . The transcriptional activity from a wild-type Sodalis palindrome sequence was high , but was completely abolished in an ssrB mutant and in experiments where only the palindrome sequence was precisely deleted ( Figure 5D ) . These experiments demonstrated a functional role for the conserved palindrome in Sodalis and the requirement for SsrB for transcriptional activation . The above results identified the conserved , yet flexible , palindrome sequence defining DNA recognition by SsrB . To examine the extent to which regulatory evolution has been selective for this genetic architecture , we created a position weight matrix ( PWM ) for the five strongest palindrome sites in SPI-2 and the orthologous sites in Sodalis SSR-3 . We then searched for representative candidates of this motif in the S . Typhimurium genome using the simple scoring algorithm MotifLocator [45] , [46] . This analysis recovered the motifs upstream of ssaB , ssaG , ssaM , and ssaR that were used to generate the PWM . The palindrome in the ssrA promoter was not used to create the PWM due to its weaker consensus in the left heptamer , however , it was recovered in the computational analysis in a second group of lower-scoring motifs ( Figure 6A ) . We identified 24 palindromes co-occurring with ChIP-on-chip peaks upstream of 24 different SsrB-regulated genes or operons . Applying a stringent threshold to the output allowed us to identify two groups - genes with high-scoring upstream palindromes ( ssaB , ssaG , ssaM , ssaR , sopD2 , sifA , sifB , sseK2 , sseK3 , sseL , sseA′ , steC , and srcA ) and those with medium-scoring palindromes ( 0 . 7–0 . 8 threshold; ssrA , STM1633 , sseI , slrP sspH2 , pipB , sseJ , pipB2 , srfN , sseA and steB ) ( Figure 6A and Dataset S4 ) ( sseA′ denotes the SsrB palindrome sequence upstream of sseA that falls within the ssaE CDS , while sseA refers to the SsrB-footprinted IGR site with only one conserved heptamer defined in Figure 4C ) . Remarkably , this accounted for 17 of 22 SL1344 genome-encoded effectors translocated by the SPI-2-encoded T3SS ( exceptions are chromosomal steA , gogB , and sseK , and plasmid-encoded spvB and spvC ) . These genes either lacked an upstream ChIP peak above our 3-standard deviation cut-off ( sseK ) or had such a peak but did not reach statistical significance in our transcriptional profiling experiments ( steA , gogB ) . Our ChIP-on-chip data revealed three additional strong SsrB binding peaks within SPI-2: one in the IGR directly upstream of ssaR , a second within the CDS for ssaJ , and a third within the CDS for ssaE that would be predicted to influence transcription of the downstream effector/chaperone operon beginning with sseA . The analysis described above recovered SsrB palindrome sequences at the sseA' and ssaR locations prompting further validation of these sites . No palindrome was identified for the ssaJ interaction peak and so further characterization was not pursued . For the IGR palindrome upstream of ssaR , we tested both a chromosome-integrated transcriptional fusion and an autonomous episomal reporter . In wild-type cells these reporters were as active as other SPI-2 promoters , whereas promoter activity was abrogated in ΔssrB cells , implicating this IGR as a functional promoter for ssaR ( Figure 6B and Figure S4 ) . We next tested the function of the intragenic palindrome within ssaE ( sseA' ) . For this , we constructed a single-copy transcriptional reporter that either contained ( WT PsseA ) or lacked ( PsseA del ) the single heptamer site in the sseA IGR and integrated this reporter into wild-type cells and mutants lacking either ssrB or the ssaE coding sequence that removed the high-scoring intragenic palindrome sseA' . These experiments showed that the sseA' sequence contributes approximately 75% of transcriptional output at the sseA promoter ( Figure 6C ) , since deleting the single heptamer in the sseA IGR had little effect on transcriptional output in any of the strain backgrounds . These reporter data are in line with the respective binding scores for the ChIP-on-chip interaction peaks ( Figure 3 ) and the sequence similarity for these elements with respect to the consensus palindrome ( Figure 6A and Figure 4D ) . Together , these data provide compelling evidence for the identity of the DNA recognition element that has been selected through evolution to co-regulate an SsrB-dependent gene program involved in adaptation to a host . Horizontal gene transfer is a well-recognized mechanism of bacterial evolution that gives rise to new phenotypes due to the coordinated expression of novel genetic components [1] . A good example of this is acquisition of type III secretion by mutualists and pathogenic bacteria enabling new colonization strategies within a host [33] , [34] . Evolved changes to regulatory circuitry can also give rise to phenotypic diversity at the species level [19] . In both cases , regulatory evolution is required to correctly deploy gene products during infection , yet the extent to which regulatory evolution contributes to pathogenic adaptation is only beginning to be realized [8] . The SsrA-SsrB two-component regulatory system in S . enterica has been the focus of our efforts to understand the significance of regulatory evolution for pathogenic adaptation . This regulatory system was co-acquired with a T3SS encoded in the SPI-2 pathogenicity island and likely contributed to immediate and gradual phenotypic diversity as new regulatory nodes were explored and acted upon by natural selection . Extensive work has been reported on the characterization of SsrB dependent genes , including functional evaluation of genes encoded within SPI-2 in addition to genome-wide transcriptional studies [14] , [15] . In this study we identified genes co-expressed under SsrB-inducing conditions and found those with strong levels of expression localized predominantly to mobile genetic elements , recently acquired genomic islands or other annotated islands . We also identified many weakly co-expressed genes , some of which may represent ancestral Salmonella genes recruited into the SsrB regulon like the previously reported srfN [18] . Some of these genes may not be directly regulated by SsrB and will require further experimental investigation . Direct profiling of SsrB-DNA interactions using ChIP-on-chip was used to identify SsrB binding sites in the genome . This analysis identified many interactions which have not been previously described and interaction sites within coding regions of genes which may represent non-canonical functions for SsrB . Other groups have reported the existence of similar numbers of ChIP-on-chip interactions within intragenic regions for other transcription factors [35] , [36] suggesting that this phenomenon is not restricted to SsrB . In light of the disparate number of microarray genes in comparison to ChIP-on-chip peaks we attempted to generate a more comprehensive picture of the SsrB regulon by combining these data sets at the operon level . In doing so we believe that the nineteen operons containing differentially expressed genes determined by microarray and containing a ChIP-on-chip peak three standard deviations above the mean captured by this analysis represent the genes directly activated by SsrB ( Table 2 ) . Those operons having a ChIP-on-chip peak directly upstream in the IGR region encompass the majority of known SsrB regulated genes while those possessing a ChIP peak within the CDS of the first gene may represent non-functional interactions that deserve follow-up experimental investigation . The ChIP-on-chip data not only provided information on the identities of SsrB-regulated genes but also gave insight as to the identity of the SsrB recognition element specified by the interaction site sequences . The regulatory architecture governing SsrB input has been elusive despite several SsrB footprints being defined biochemically [19] , [25] , [26] . Our ChIP-on-chip data further suggested that SsrB binding within SPI-2 was specific , with binding peaks overlapping precisely with regions of the DNA footprinted by SsrB [25] , [26] . By using a genetic screening strategy together with functional and comparative genomics , we were able to define the essential SsrB regulatory element as being an 18-bp palindrome with a conserved 7-4-7 internal organization . In support of the palindrome as the functional entity we showed the loss of SsrB dependence as a result of deletion of this element for the ssaG promoter . Evaluation of the 7-4-7 palindrome in the ssaG promoter revealed the minimal architecture and sequence orientation required for transcriptional input . Deletion of the entire palindrome resulted in less than 1% activity in wild-type cells , an equivalent level of activity to those lacking ssrB entirely . A search of the S . enterica genome for this palindromic motif revealed candidates upstream of the previously noted SsrB dependent genes , including two additional SPI-2 sites; one IGR site upstream of ssaR that until now had been cryptic , and one intragenic palindrome upstream of sseA in the ssaE CDS . In both cases these input sites were found to be functional . Although palindrome architecture was conserved upstream of SsrB-regulated genes , degenerate palindromes in which one half-site was more conserved were also functional . As a result of our mutational analyses we conclude that so long as the orientation of a single heptamer of the palindrome is conserved with respect to the downstream gene , SsrB is tolerant of degeneracy in the adjacent spacer and heptamer sequences . While we were able to identify a number of limited palindrome-like sequences from our bacterial one-hybrid screen , this tolerance in addition to the library size required to pull out an 18-bp palindrome in large numbers may explain why we isolated functional single heptamer sequences and why degenerate palindromes naturally exist in the genome . A recent report by Carroll et al , postulated that SsrB first interacts with DNA as a monomer , followed by dimerization [32] . Our findings also suggest that dimerization is likely required for transcriptional activation however strong recognition by one monomer may stabilize interaction of a second monomer with a less than ideal sequence . The finding that a flexible palindromic sequence can be selective for SsrB input raises many interesting questions around the nature of regulatory evolution . The ability to use a short functional half-site adjacent to an uncharacterized threshold level of tolerated bases would reduce the period of neutral evolution required to generate an inverted repeat sequence twice the length [37] , and would limit the loss of intermediate variations to drift while a more desirable palindrome is created by regulatory evolution . For bacteria that make use of horizontal gene transfer , this could increase the tempo with which new DNA is integrated into the regulatory circuitry of the cell . We showed that the SsrB regulatory palindrome is also present in the orthologous SSR-3 island of the endosymbiont Sodalis glossinidius and that the palindrome evolved in Sodalis can act as a cis regulatory input function in Salmonella . Thus , in addition to supporting a pathogenic lifestyle within a host in Salmonella , it seems probable that this common promoter architecture may direct the activation of the SSR-3 T3SS of S . glossinidius in its endosymbiotic relationship with the tsetse fly host , although we acknowledge this requires experimental validation . The SSR-3 region in S . glossinidius is fully conserved in gene synteny and content with that of SPI-2 [31] , with the exception of two effector genes missing in SSR-3 ( sseF and sseG ) that are required to localize vacuolar Salmonella to the perinuclear Golgi in host cells [38] , [39] . The SsrB ortholog in S . glossinidius is ∼30% divergent with SsrB at the protein level , initially leading us to think that they might have different binding site preferences . To the contrary , high local conservation in the promoters evolved in Salmonella and Sodalis was the crux in defining the functional SsrB input among stochastic noise . This analysis revealed strong palindrome sequence conservation in five promoters identified in SPI-2 and in the orthologous sequences in Sodalis SSR-3 . Among palindrome-containing promoters , the ssrA promoter is exceptional for two reasons: a lack of conservation between Salmonella and Sodalis , and the evolution of tandem palindromes in Salmonella . One possible interpretation of this divergent regulatory architecture in front of ssrA might relate to bacterial lifestyle . Salmonella may have retained or evolved SsrB input here to create a positive feedback loop on the regulatory system to rapidly adapt to the host environment during infection , similar to transcriptional surge described for the PhoP response regulator [40] . The endosymbiotic relationship of Sodalis with the tsetse fly - where long-term vertical transmission has ostensibly been formative in shaping regulatory circuitry at certain promoters - may obviate the need for rapid transcriptional surge , leading to regulatory drift or selection against positive feedback . With the structure of SsrB available [32] and its recognized sequence now identified , future studies will be able to build a picture of how SsrB interacts with both its target DNA , RNA polymerase and potentially other transcription factors including nucleoid associated proteins in order to direct transcription of its regulon . In summary , this work highlights the evolutionary significance of cis-regulatory mutation for the adaptation of Salmonella to a host animal . The DNA module that choreographs SsrB-mediated pathogenic behaviour in Salmonella appears to have been conserved for mutualism as well , thereby shedding new light on the significance of cis-regulatory mutations for bacteria evolving in different ecological settings . All experiments with animals were conducted according to guidelines set by the Canadian Council on Animal Care . The Animal Review Ethics Board at McMaster University approved all protocols developed for this work . The Salmonella strain used for microarray and ChIP-on-chip analysis was Salmonella enterica serovar Typhimurium strain SL1344 . Bacterial strains and plasmids used in this work are described in Table S1 . Primer sequences used to generate constructs are available upon request . Bacteria were grown in LB medium unless otherwise indicated . Low-phosphate , low magnesium ( LPM ) medium was used as bacterial growth medium for microarray , ChIP-on-chip , and transcriptional reporter experiments [20] . Liquid cultures were routinely grown at 37°C with shaking . Antibiotics were added to media as follows when necessary: ampicillin ( Amp , 100 µg/mL ) , chloramphenicol ( CM , 34 µg/mL ) kanamycin ( Kan , 30 or 50 µg/mL ) , and streptomycin ( SM , 50 µg/mL ) . NM medium was used in the bacterial one-hybrid experiments as described previously [27] . Microarray experiments were conducted and analyzed as described previously [16] . cDNA was synthesized from RNA harvested from wild-type cells and an ΔssrB mutant . cDNA from 2 replicate experiments was hybridized to InGen arrays and analyzed using ArrayPipe version 1 . 309 [21] . Probe signals underwent a foreground-background correction followed by a printTipLoess normalization by sub-grid . Duplicate spots were merged followed by averaging of the two replicates . Local intensity z scores were calculated for determination of significance . For operon analysis , S . Typhimurium SL1344 operons were defined as groups of genes encoded on the same strand with a maximum intergenic distance of 30-bp . Operons selected for further investigation were those possessing at least one significantly down-regulated gene from the cDNA microarray analysis of an ssrB mutant . A cDNA microarray score was assigned based on the average fold-change value of all genes within the operon . For ChIP-on-chip analysis , a top ChIP interaction score was defined as that of the highest scoring probe within the first gene or the intergenic region upstream of the first gene of the operon . For the analysis of regions of difference ( ROD ) between S . enterica serovar Typhimurium and Salmonella bongori , a reciprocal-best BLAST analysis was performed to identify orthologous genes between S . Typhimurium and S . bongori . Orthologs were defined as reciprocal best BLAST pairs with E-values less than 0 . 005 . Comparison of gene synteny between regions encoding orthologous genes was performed to identify regions of low conservation including gene deletions and insertions . The location and names of genes flanking the comprehensive list of genomic islands is provided in Dataset S2 and were compared to those predicted using IslandViewer [41] . The bacterial one-hybrid ( B1H ) experiments were conducted as outlined previously using a single-step selection procedure [27] . Full-length phoP from E . coli and the C-terminal domain of ssrB ( ssrBc ) from S . Typhimurium were cloned into pB1H1 to create a fusion to the αNTD of RNA polymerase . Each bait vector was transformed into E . coli ΔhisB ΔpyrF , purified , and then cells were transformed again with purified prey library that was previously counter-selected for self-activating preys using 5-fluoro-orotic acid . Transformants were recovered for 1 h in SOC medium , washed with NM medium supplemented with 0 . 1% histidine ( NM + his ) and allowed to grow for 2 h in this medium . Cells were washed four times with water , once with NM medium lacking histidine ( NM –his ) , then resuspended in NM –his and plated on 150×15 mm dishes containing NM –his media supplemented with either 1 mM ( for PhoP screen ) or 5 mM ( SsrBc screen ) 3-aminotriazole . Selection was for ∼48 hours at 37°C . Individual clones were selected from plates containing <600 colonies , the prey plasmids were isolated and sent for sequencing ( Macrogen USA ) . Sequences were parsed to extract the 18-bp prey sequence , then inputted into MEME ( version 4 . 1 . 1 ) for motif generation [29] . MEME was run with default parameters and included searching for motifs of length 5–17 bp in either forward or reverse direction and with no limit on the number of occurrences within an input string . Motif logos were generated using Weblogo , version 2 . 8 . 2 [42] . Chromatin immunoprecipitation-on-chip ( ChIP-on-chip ) was conducted as described previously using an SL1344 strain containing an ssrB-3xFLAG allele on the chromosome [19] . The primer sequences used to generate the DNA for recombination were: 5′GAG TTA CTT AAC TGT GCC CGA AGA ATG AGG TTA ATA GAG TAT GAC TAC AAA GAC CAT GAC GG3′ and 5′ATC AAA ATA TGA CCA ATG CTT AAT ACC ATC GGA CGC CCC TGG CAT ATG AAT ATC CTC CTT AG3′ . This strain was generated by an allelic replacement method described previously [43] and causes lethal infection of C57BL/6 mice similar to wild-type SL1344 ( Figure S5 ) . Immunoprecipitated DNA from three experiments under SsrB-inducing conditions ( LPM growth medium ) and one experiment under non-inducing conditions ( exponential growth in LB medium ) was hybridized to a single chip printed with four whole genome arrays designed on S . enterica serovar Typhimurium strain SL1344 ( Oxford Gene Technology , Oxford UK ) . Signals for each probe within an experiment were normalized to the median channel signal for the respective array . Signal ratios were obtained for both inducing and non-inducing conditions by calculating the ratio of the control probe value and experimental probe value . A final interaction score was obtained by taking the log2 value of the ratio between the non-inducing and inducing conditions for each probe to remove SsrB interactions that occur under non-inducing conditions . Parsing and data analyses were performed using the Python scripting language . Genome-wide ChIP-on-chip data was plotted using Circos v . 0 . 51 [44] . ChIP probes were ordered according to their position on the S . Typhimurium SL1344 genome and local maxima for ChIP interaction scores were defined as interaction peaks . Peaks with scores greater than three standard deviations from the mean probe signal were considered significant ChIP interaction peaks and were ranked in order of descending interaction score . The sequence of the top-scoring probe for each peak was exported to a text file and used for analysis by MDscan [30] . The background parameter was run with output generated by the included genomebg program from the S . Typhimurium SL1344 genome sequence . The initial motif was generated from sequences from the top ten SsrB interaction peaks and refined using the top 25 peak sequences . To identify instances of the palindrome motif in S . Typhimurium , ten 18-bp 7-4-7 palindromic motifs in the promoters of the SPI-2 genes ssrA , ssaB , ssaG , ssaM , ssaR and their orthologous SSR-3 genes were used as input for MDScan to identify a consensus motif and to determine the position specific scoring matrix ( PWM ) . This PWM was used with MotifLocator to identify instances of this motif in the S . Typhimurium SL1344 genome . A background file specific to SL1344 was generated using the associated script called CreateBackgroundModel . A stringent threshold value of 0 . 8 was used [45] , [46] . Transcriptional fusions to lacZ for the ssaG and sseA promoter palindrome analysis were generated using chemically synthesized double-stranded DNA ( Genscript Corp ) . Promoter DNA was ligated into pIVET5n , then the plasmid was subsequently conjugated into SL1344 to generate single-copy transcriptional fusions integrated on the chromosome as described previously [20] . Luciferase reporter constructs for the Sodalis glossinidius SG1292 and ssaR promoters were generated by PCR amplification of promoter regions from genomic DNA templates . The luciferase reporter construct for the PssaG scrambled substitution was created by PCR product splicing via overlap extension using the existing ssaG promoter cloning primers and two additional internal primers containing the desired mutation sequence ( DTM0061R , 5′CGC GAA AGC AAC GAT TAC TCC GGC GCA CG3′ and DTM0061 . 1F , 5′GAG TAA TCG TTG CTT TCG CGA TAC CGG ATG TTC ATT GCT TTC TA3′ ) . This DNA was ligated into pCS26 and transformed into SL1344 to generate plasmid-based reporters . Overnight cultures of Salmonella were sub-cultured into LPM medium and grown with shaking for 7 h . Samples were removed hourly to measure β-galactosidase activity via a chemiluminescence-based assay as described previously [20] or luminescence directly from cultures ( EnVision , Perkin-Elmer ) . Output was relative light units ( RLU ) normalized to OD600 . Each experiment was performed in triplicate then averaged . Reporter activity from mutant and rewired promoters was normalized to that from wild-type promoters . All ChIP-on-chip data can be retrieved from the NCBI Gene Expression Omnibus at http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE20192 . Data files for viewing in Artemis ( http://www . sanger . ac . uk/Software/Artemis/ ) are available upon request .
All organisms have a means to control gene expression ensuring correct spatiotemporal deployment of gene products . In bacteria , gene control presents a challenge because one species can reside in multiple niches , requiring them to coordinate gene expression with environmental sensing . Also , widespread acquisition of DNA by horizontal gene transfer demands a mechanism to integrate new genes into existing regulatory circuitry . The environmental awareness issue can be controlled using two-component regulatory systems that connect environmental cues to transcription factor activation , whereas the integration problem can be resolved using DNA regulatory evolution to create new regulatory connections between genes . The evolutionary significance of regulatory evolution for host adaptation is not fully known . We studied the convergence of environmental sensing and genetic networks by examining how the Salmonella enterica SsrA-SsrB two-component system , activated in response to host cues , has integrated ancestral and acquired genes into a common regulon . We identified a palindrome as the major element apportioning SsrB on the chromosome . SsrB binding sites have been selected to co-regulate a gene program involved in pathogenic adaptation of Salmonella to its host . In addition , our results indicate that promoter architecture emerging from SsrB-dependent regulatory evolution may support both mutualistic and parasitic bacteria-host relationships .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "genetics", "and", "genomics/microbial", "evolution", "and", "genomics", "genetics", "and", "genomics/gene", "discovery", "infectious", "diseases", "genetics", "and", "genomics/gene", "expression" ]
2010
Identification of the Regulatory Logic Controlling Salmonella Pathoadaptation by the SsrA-SsrB Two-Component System
North-west Ethiopia faces the highest burden world-wide of visceral leishmaniasis ( VL ) and HIV co-infection . VL-HIV co-infected patients have higher ( initial ) parasitological failure and relapse rates than HIV-negative VL patients . Whereas secondary prophylaxis reduces the relapse rate , parasitological failure rates remain high with the available antileishmanial drugs , especially when administered as monotherapy . We aimed to determine the initial effectiveness ( parasitologically-confirmed cure ) of a combination of liposomal amphotericin B ( AmBisome ) and miltefosine for treatment of VL in HIV co-infected patients . We conducted a retrospective cohort study at a Médecins Sans Frontières—supported health center in north-west Ethiopia . We included VL-HIV co-infected adults , treated for VL between January 2011 and August 2014 , with AmBisome infusion ( 30 mg/kg total dose ) and miltefosine orally for 28 days ( 100 mg/day ) . Proportions of initial treatment outcome categories were calculated . Predictors of initial parasitological failure and of death were determined using multivariable logistic regression . Of the 173 patients included , 170 ( 98 . 3% ) were male and the median age was 32 years . The proportion of patients with primary VL ( 48 . 0% ) and relapse VL ( 52 . 0% ) were similar . The majority had advanced HIV disease ( n = 111; 73 . 5% ) and were on antiretroviral therapy prior to VL diagnosis ( n = 106; 64 . 2% ) . Initial cure rate was 83 . 8% ( 95% confidence interval [CI] , 77 . 6–88 . 6 ) ; death rate 12 . 7% ( 95% CI , 8 . 5–18 . 5 ) and parasitological failure rate 3 . 5% ( 95% CI , 1 . 6–7 . 4 ) . Tuberculosis co-infection at VL diagnosis was predictive of parasitological failure ( adjusted odds ratio ( aOR ) , 8 . 14; p = 0 . 02 ) . Predictors of death were age >40 years ( aOR , 5 . 10; p = 0 . 009 ) , hemoglobin ≤6 . 5 g/dL ( aOR , 5 . 20; p = 0 . 002 ) and primary VL ( aOR , 8 . 33; p = 0 . 001 ) . Initial parasitological failure rates were very low with AmBisome and miltefosine combination therapy . This regimen seems a suitable treatment option . Knowledge of predictors of poor outcome may facilitate better management . These findings remain to be confirmed in clinical trials . Visceral leishmaniasis ( VL ) is a protozoan infection caused by the Leishmania donovani species complex [1] . In East Africa and the Indian subcontinent , it is caused by L . donovani , whereas in the Mediterranean region and South America , by L . infantum [2] . Ethiopia is among the top six high burden countries , with approximately 3 . 2 million people at risk and 3400–5000 VL cases occurring annually [3–5] . North-west Ethiopia faces the highest burden world-wide of VL-HIV co-infection , an estimated 20% of VL patients are HIV co-infected [6] . HIV infection influences the clinical course of VL: it reactivates latent Leishmania infection , increases VL severity , and negatively affects treatment outcomes [7] . VL in turn promotes the progression of HIV infection [7] . As to VL treatment outcomes , both higher ( initial ) parasitological failure rates and higher relapse rates have been described [7 , 8] . To reduce the relapse rate , secondary prophylaxis is the way to go [7 , 9–11] . We have recently documented the effectiveness , safety and feasibility of pentamidine secondary prophylaxis—started after parasitological cure was achieved—in Ethiopian VL-HIV co-infected adults [9 , 11] . However , achieving parasitological cure remains challenging , as co-infected patients have shown poor treatment response to all available antileishmanial drugs especially when administered as monotherapy [7] . Several studies have shown that pentavalent antimonials cause severe adverse events ( cardiotoxicity , nephrotoxicity , hepatotoxicity , pancreatitis ) resulting in high case fatality rates [7 , 12–18] . Antimonials have also been shown to stimulate HIV-1 replication in vitro [19] . In East Africa , high case fatality rates of 6 . 8% to 33 . 3% have been reported [14–16] . Due to the high case fatality rates , the World Health Organization ( WHO ) recommends that pentavalent antimonials should ideally not be used as a first line treatment for VL in HIV co-infected patients [20] . In comparison to antimonials , there is relatively limited clinical experience with miltefosine—a newer antileishmanial agent [7 , 15 , 20 , 21] . An Ethiopian study comparing miltefosine and the antimonial—sodium stibogluconate ( SSG ) , showed that miltefosine was safer ( lower death rates: 1 . 6% vs . 6 . 8% ) but had lower initial effectiveness ( higher initial parasitological failure rates: 17 . 5% vs . 2 . 3% ) [15] . These high parasitological failure rates increase the potential for the emergence of resistant parasites [21] . Because patients with parasitological failure are potential reservoirs of resistant parasites , they are a major public health concern , especially in East Africa where the main mode of transmission of Leishmania parasites is anthroponotic [21] . Furthermore , miltefosine has a long half-life of approximately one week , and can develop resistance with a single point mutation [22] . The most optimal way to use miltefosine would be in combination with another antilesihmanial agent [21 , 23] . Several studies from the L . infantum areas of the Mediterranean region , in small numbers of co-infected patients , showed that liposomal amphotericin B was safe and effective [7 , 20] . Based on these findings and absence of similar studies from other VL endemic areas , the WHO recommended liposomal amphotericin B as the first line treatment for VL in HIV co-infected patients [20] . However , liposomal amphotericin B ( AmBisome ) monotherapy at a total dose of 30 mg/kg also had limited effectiveness in Ethiopia , with initial parasitological failure rates of 32 . 8% [24] . Combination treatment has been used in tuberculosis , HIV and malaria with good outcome and is increasingly being used for VL [23 , 25] . We reasoned that , as both AmBisome and miltefosine had been found to be safe , but with high initial parasitological failures as monotherapy , the combination of the two drugs with different modes of action and non-overlapping toxicity might yield a safe regimen able to decrease the high initial parasitological failure rates [7 , 15 , 20 , 21 , 24 , 26] . In 2011 , Médecins Sans Frontières ( MSF ) introduced a compassionate treatment regimen of AmBisome and miltefosine combination as first line treatment for VL in HIV co-infected patients . In this study , we aimed to determine the initial effectiveness ( cure , death and parasitological failure rates ) of this regimen for treatment of VL in HIV co-infected patients in Ethiopia . The study was conducted at Abdurafi health center—an MSF supported health facility located in a remote town in Amhara region , in northwestern Ethiopia . The MSF support focuses on clinical management of VL , HIV and concomitant infections . It is a major VL treatment site in Ethiopia and medical services are free of charge . The majority ( >95% ) of VL patients treated at the health center , are young adult males working on the large-scale agricultural schemes in the northwestern lowlands . We conducted a retrospective cohort study using routine program data . In the main ( per-protocol ) analysis , we included all VL-HIV co-infected patients diagnosed between January 2011 and August 2014 , aged ≥18 years , treated with an initial VL treatment regimen composed of a combination of AmBisome and miltefosine . Patients that discontinued treatment , defaulted , were transferred-out or had a missing VL treatment outcome were excluded . We also conducted a sensitivity analysis that is similar to an intention to treat analysis . In this analysis , we also included patients that defaulted or were transferred-out , and considering that they probably had Leishmania parasites at exit , they were all classified as having parasitological failure . Patients with prolonged fever , splenomegaly and wasting were considered VL suspects and underwent further diagnostic evaluations [20] . Patients without prior VL treatment history ( primary VL ) were first screened using the rK39 rapid diagnostic test ( IT-Leish , Bio-Rad laboratories , USA ) [27] and a positive result confirmed VL . Those testing negative were screened with the leishmania direct agglutination test ( DAT , Royal Tropical Institute , Amsterdam , The Netherlands ) [28] and a high titer ( ≥1:3200 ) confirmed VL . Those with an intermediate DAT titer ( 1:800–1:1600 ) underwent tissue aspiration ( spleen , bone marrow or lymph node ) and a positive result confirmed VL . Patients with prior VL treatment history ( relapse VL ) underwent tissue aspiration and a positive result confirmed VL . A clinical diagnosis was made in patients [primary VL ( with negative rK39 test results and intermediate DAT results ) and relapse VL] who were contra-indicated for spleen aspirate ( i . e . spleen size ≤2 cm , bleeding tendency , pregnant , severely anemic , jaundiced or in a state of collapse ) or who declined a bone marrow aspirate and didn’t have palpable lymph nodes . Furthermore , a clinical diagnosis was also made in patients [primary VL ( with negative rK39 test results and intermediate DAT results ) and relapse VL] with negative bone marrow aspirate results but persistent strong VL clinical suspicion in the absence of differential diagnoses [24 , 29] . HIV positive status was defined by two positive results of serological tests performed in parallel {KHB ( Shanghai Kehua Bio-engineering Co-Ltd , Shanghai , China ) and STAT-PAK ( Chembio HIV1/2 , Medford , New York , USA ) } and confirmed by the ELISA test {ImmunoComb ( Orgenics ImmunoComb II , HIV 1&2 Combfirm ) } . Antiretroviral therapy ( ART ) prescription was according to national guidelines and tenofovir , lamivudine and efavirenz combination was the most common first line regimen [30] . The initial treatment regimen was a combination of liposomal amphotericin B ( AmBisome , Gilead Sciences ) at a total dose of 30 mg/kg , divided into 6 infusions of 5 mg/kg on alternate days and miltefosine ( Impavido , Paladin Labs , Montreal , Canada ) administered orally for 28 days ( 100 mg/day ) . Patients that showed a slow treatment response received a second course of the combination regimen at the same dosage ( treatment extension ) . Slow treatment response was defined as a substantial parasite reduction after finishing the treatment course ( day 29 ) as compared to baseline ( parasite decrease ≥2 log-grades but parasitology result was still positive ) [29 , 31] . Patients that showed no parasitological response to the combination treatment received sodium stibogluconate ( Albert David Ltd . , Kolkata ) at a dose of 20 mg/kg/day by intramuscular injection for a minimum of 30 days ( rescue therapy ) . No parasitological response was defined as no substantial parasite reduction at the end-of-treatment as compared to baseline ( parasite decrease ≤1 log-grade and parasitology result was still positive ) [29 , 31] . Our main outcome of interest was the initial treatment outcome which was defined as the treatment outcome after completion of the first VL treatment course . The categories of initial treatment outcome included: cure , death , parasitological failure , defaulter and transfer-out . Parasitological tests were performed at the end-of-treatment in all co-infected patients except for those without palpable spleen or lymph nodes and who refused bone marrow aspirate , or for those with a contraindication for spleen aspirate . For this category of patients , cure was assessed clinically . Patients with parasitological failure received additional treatment ( retreatment ) and the subsequent treatment outcome was classified as retreatment outcome . Treatment outcome at discharge was either the initial treatment outcome or where applicable the retreatment outcome . The categories of treatment outcome at discharge were as for the initial treatment outcome . Cure was defined as improvement in symptoms and signs of VL after treatment initiation ( i . e . absence of fever , decrease in spleen size , increase in hemoglobin , weight gain ) and a negative parasitological test at the end-of-treatment . Parasitological failure was defined as a positive parasitological test at the end-of-treatment . Death from all causes during VL treatment at the health center were documented . Defaulting was defined as absconding from treatment . Transfer-out was defined as referral to another hospital facility . Treatment discontinuation was defined as discontinuation of a VL treatment regimen prior to using less than 90% of the total recommended dosage . Since the program onset , clinical data were collected using standardized data collection tools and stored in electronic databases . The databases were updated on a daily basis by data managers . The data were collected at admission through history taking , clinical examination , laboratory and/or radiological investigations , and treatment prescriptions ( VL and ART regimens ) . The following variables were assessed from patient history: age ( years ) , sex , residential status [migrant worker ( an individual who seasonally relocates to another area in search of work ) ; settler ( an individual who has been relocated to another area by the state ) and resident ( an individual who has permanently lived within a specific area for a duration of 2 or more years ) ] , duration of illness ( months ) and VL treatment history ( primary , relapse ) . The following variables were assessed by clinical examination: weight ( kilograms ) , height ( meters ) /length ( centimeters ) , body mass index [BMI; weight in kilograms ÷ ( height in meters ) 2] , spleen size ( centimeters ) , the level of weakness , ascites , peripheral edema , bleeding and jaundice . The spleen size ( centimeters ) was measured from the junction of the anterior axillary line and the left coastal margin to the tip of the spleen . Weakness severity was defined according to MSF guidelines [29] as follows: [State of collapse: unable to sit up unaided and cannot drink unaided; severely weak: cannot walk 5 meters without assistance; other types of weakness were classified as “other”] . The following variables were assessed by laboratory and/or radiological investigations . The mode of diagnosis of HIV was defined above ( see HIV diagnosis ) . Using a microscope with a 10X eyepiece and 100X oil objective , tissue parasite grading were as follows: [0 ( 0 parasites/1000 fields ) ; 1+ ( 1–10 parasites/1000 fields ) ; 2+ ( 1–10 parasites/100 fields ) ; 3+ ( 1–10 parasites/10 fields ) ; 4+ ( 1–10 parasites/field ) ; 5+ ( 10–100 parasites/field ) ; 6+ ( >100 parasites/field ) ] ) [31] . Hemoglobin level was measured using a hematology analyzer—Beckman Coulter AcT diff , Beckman Coulter Inc . , 2003 , USA . CD4 count was measured at baseline and every six months after ART initiation using the FACS counter ( BD FACS Calibur flow cytometer , 2009 , USA ) . Tuberculosis diagnosis and WHO clinical staging were according to WHO guidelines [32 , 33] . The primary outcome was the initial treatment outcome ( cure , death or parasitological failure ) . The proportion of individuals with the different outcome categories ( excluding patients that defaulted or were transferred-out ) , were calculated with 95% Wilson confidence intervals ( CI ) . In secondary analysis , the association of initial treatment outcome with VL treatment history was assessed by the Chi-squared or Fisher’s exact test . Predictors of initial parasitological failure and predictors of death were determined . Predictors of parasitological failure were analyzed among patients with parasitological failure or cure , whereas predictors of death were analyzed among patients who died or stayed alive ( cured or parasitological failure ) . The choice of variables analyzed as predictors was based on literature review and consideration of variables available in the dataset . To overcome the problem of substantial missing baseline CD4 count results , we created a composite marker for advanced HIV disease , defined as having either additional WHO stage IV disease [33] or a CD4 count <50 cells/μL at VL diagnosis [34] . Continuous variables were categorized based on information from literature and a recent study on predictors of death [35] . The association between predictors and parasitological failure or death were first assessed with Chi-squared or Fisher’s exact test . When the p-value was <0 . 1 , the predictor was included in a multivariable logistic regression model . Non-significant variables ( p-value ≥0 . 05 ) were removed step by step until no more variables could be dropped . Lastly , a sensitivity analysis similar to an intention to treat analysis was performed . Defaulters and transfer-outs were included in this sensitivity analysis; and considering that they probably had Leishmania parasites at exit , they were all classified as having parasitological failure . All the statistical methods described above were then repeated . All statistical analyses were performed with Stata version 14 . Ethics approval was received from the Institutional Review Board of the Institute of Tropical Medicine , Antwerp , Belgium , and the Ethical Review Committee of the Institute of Public Health , Gondar University , Ethiopia . This research fulfilled the exemption criteria set by the MSF Ethical Review Board ( ERB ) for a posteriori analyses of routinely collected clinical data , and thus did not require MSF ERB review . It was conducted with permission from the Medical Director of the MSF Operational Centre Amsterdam . Most patients were male ( n = 170; 98 . 3% ) , residents ( n = 101; 59 . 1% ) and young ( median age of 32 years; interquartile range [IQR] 28–39 ) . The proportion of patients with primary VL ( n = 83; 48 . 0% ) and relapse VL ( n = 90; 52 . 0% ) were similar . Most patients had advanced HIV disease ( n = 111; 73 . 5% ) and were on ART prior to VL diagnosis ( n = 106; 64 . 2% ) ( Table 1 ) . Compared to relapse VL patients , a higher proportion of primary VL patients were aged 18–40 years ( 88 . 0% vs . 75 . 6% ) , had been ill for ≥2 months ( 46 . 2% vs . 27 . 9% ) and had not started ART prior to the VL episode ( 57 . 7% vs . 16 . 1% ) . Lastly , primary VL patients had a lower parasite load at admission ( median +4 vs . +5 ) and a lower proportion had cure confirmed by a parasitological test ( 43 . 1% vs . 65 . 0% ) ( Table 1 ) . The outcomes were: cured , 145/173 ( 83 . 8%; 95% CI , 77 . 6–88 . 6 ) ; died , 22/173 ( 12 . 7%; 95% CI , 8 . 5–18 . 5 ) and parasitological failure , 6/173 ( 3 . 5%; 95% CI , 1 . 6–7 . 4 ) . The outcome by VL treatment history was significantly different as shown in Table 2 . Of the 6 patients with initial parasitological failure ( Table 2 ) , 1 was retreated with AmBisome and miltefosine combination , 2 with AmBisome alone and 3 with SSG based regimen . One of the patients retreated with SSG based regimen died , all the rest were cured . The treatment outcomes at discharge were: cured , 150/173 ( 86 . 7% ) ; died , 23/173 ( 13 . 3% ) and no parasitological failure . Tuberculosis co-infection at VL diagnosis was predictive of initial parasitological failure ( adjusted odds ratio ( aOR ) , 8 . 14; 95% CI , 1 . 42–46 . 72; p = 0 . 02 ) . There was a statistically non-significant association between high tissue parasite load ( parasite grade 6+ ) at VL diagnosis and initial parasitological failure . In multivariable analysis , VL treatment history was not significantly associated with initial parasitological failure ( Table 3 ) . Independent predictors of death were age >40 years ( aOR , 5 . 10; 95% CI , 1 . 50–17 . 44; p = 0 . 009 ) , hemoglobin ≤6 . 5 g/dL ( aOR , 5 . 20; 95% CI , 1 . 83–14 . 79; p = 0 . 002 ) and primary VL ( aOR , 8 . 33; 95% CI , 2 . 27–30 . 63; p = 0 . 001 ) as shown in Table 4 . The initial treatment outcomes were similar to those from the main analysis as shown in S2 Table . As also reported in the main analysis , tuberculosis co-infection at VL diagnosis was predictive of initial parasitological failure . Additionally , BMI<16 kg/m2 ( severe malnutrition ) was also predictive of initial parasitological failure as shown in S3 Table . The independent predictors of death were similar to those from the main analysis as shown in S4 Table . VL-HIV co-infected patients are confronted with high ( initial ) parasitological failure rates and high relapse rates [7 , 8] . While we recently identified pentamidine secondary prophylaxis as a promising option to reduce the relapse rates [9 , 11] , achieving parasitological cure has been challenging . In this study , we determined the initial effectiveness ( cure , death and parasitological failure rates ) of a combination regimen of AmBisome and miltefosine for treatment of VL in HIV co-infected patients in Ethiopia . The initial cure rate was 83 . 8% , death rate 12 . 7% and parasitological failure rate 3 . 5% . Tuberculosis co-infection at VL diagnosis was predictive of initial parasitological failure . Age >40 years , hemoglobin level ≤6 . 5 g/dL and primary VL were predictive of death . Although it remains difficult to compare historical cohorts , the initial treatment outcomes with combination therapy compared with those for AmBisome monotherapy—the previous first line treatment at the MSF treatment site [24] , are as follows: parasitological failure rates were significantly lower ( 3 . 5% vs . 32 . 8%; p<0 . 001 ) , cure rates were significantly higher ( 83 . 8% vs . 60 . 4%; p<0 . 001 ) , and death rates were non-significantly higher ( 12 . 7% vs . 6 . 8%; p = 0 . 05 ) . None of the deaths are considered treatment-related . In the present study , we had a higher admission rate of late stage VL patients that were referred from other hospitals as compared to the previous AmBisome monotherapy study . We have recently shown that besides HIV serostatus , other important predictors of death were: age >40 years , hemoglobin ≤6 . 5 g/dL , bleeding , jaundice , edema , ascites and tuberculosis [35] . We also found that in the presence of major predictors of death , the predictive effect of treatment on outcome may be minimal [35 , 36] . If we are to consider initial parasitological failure and death as overall initial failure ( assuming that patients who died also had parasitological failure ) , then the overall initial failure rate with the combination regimen were also significantly lower than with AmBisome monotherapy ( 16 . 2% vs . 39 . 6%; p<0 . 001 ) [24] . In contrast to pentavalent antimonials that cause severe adverse events resulting in high case fatality rates [7 , 12–18] , AmBisome and miltefosine have been shown to be safe [7 , 15 , 20 , 21 , 24 , 26] . Therefore the higher case fatality rates reported here are more likely related to the patients clinical conditions ( late stage VL patients ) , than due to AmBisome and miltefosine toxicity [7 , 15 , 20 , 21 , 24 , 26] . Combination treatment may increase treatment efficacy and tolerance , reduce treatment duration and cost , and limit the emergence of drug resistance [23 , 25] . VL combination therapies have been successfully used and implemented in HIV-negative patients [37 , 38] . In vitro studies have demonstrated synergy between liposomal amphotericin B and miltefosine [39] . A combination of synergistic treatment regimens with different modes of action and mechanisms to develop resistance can also delay the emergence of drug-resistance [23] . AmBisome and miltefosine combination therapy was safe and effective in HIV-negative patients [38] . For co-infected patients , an Indian retrospective study on AmBisome and miltefosine combination therapy showed it was safe and effective , however , initial treatment outcomes were not reported [40] . Thanks to an agreement between Gilead and WHO , on a donation programme , WHO is providing AmBisome for treatment of visceral leishmaniasis for free to low income countries in East Africa and South Asia . This donation programme started in 2012 , and has been extended in 2017 for another five years , including middle income countries . This access to free AmBisome will enhance affordability of implementing AmBisome-based treatment regimens for VL-HIV [41–44] . Combining AmBisome and miltefosine may be crucial: with lower initial parasitological failure rates , fewer patients required retreatment and therefore treatment duration was shortened . This promotes patient compliance , reduces risk of adverse events , and patient and health facility costs [23] . AmBisome must be transported and stored at temperatures below 25° centigrade [26] . Miltefosine may be teratogenic , therefore it is contraindicated during pregnancy , women of reproductive age must use effective contraception during and for 3 months after treatment [21] . Miltefosine may also cause gastrointestinal symptoms ( nausea and vomiting ) [21] . In this study , there was no treatment discontinuation secondary to gastrointestinal symptoms . Good tolerance to miltefosine has also been reported in other studies [15 , 40] . Overall , similarly as in India , our findings are encouraging in terms of efficacy of combination therapy . Data from clinical trials are now needed to enhance the evidence base . Importantly , studies evaluating AmBisome and miltefosine combination therapy in HIV patients have been conducted in Ethiopia [45] and started in India [46] . The trial findings are to be published soon . We found that tuberculosis co-infection at VL diagnosis was predictive of initial parasitological failure . This is similar to findings from a study conducted in Sudan [47] . Tuberculosis causes immunosuppression which may inhibit parasite clearance , resulting in parasitological failure [47] . In another Ethiopian study , high tissue parasite load at VL diagnosis was shown to predict parasitological failure [16] . Possibly in the presence of underlying immunosuppression , a high parasite load on admission might be more difficult to clear . In our study , we also found an association between high tissue parasite load at VL diagnosis and initial parasitological failure , however , it was not statistically significant . This finding could be explained by the few outcomes observed in this study—only 6 patients with initial parasitological failure . In sensitivity analysis , BMI<16 kg/m2 ( severe malnutrition ) was predictive of initial parasitological failure . As with tuberculosis , severe malnutrition causes immunosuppression which may inhibit parasite clearance , resulting in parasitological failure . The predictors of death identified—age >40 years and hemoglobin level ≤6 . 5 g/dL—are similar to those reported from other studies [35 , 48 , 49] . Patients aged >40 years , may have underlying co-morbidities ( e . g . cardiovascular diseases ) , lower immunity and/or severe VL disease [48 , 50–53] , which increases their risk to die . Severe anemia may cause congestive heart failure [54] . In comparison with relapse VL patients , we found that primary VL patients were more likely to die . The exact reason for this is unknown . However , since VL-HIV coinfection is a severe illness [7] , and the risk of VL relapse is high ( 26% at one year ) [8] , it is probable that relapse VL patients may be more likely to be aware of the dangers of VL than primary VL patients , they may present to the health center with an earlier stage of illness in comparison with primary VL patients that may arrive with more end stage illness . Most of our patients are young adult males who get infected with leishmania while working in the agricultural fields within the VL endemic region . HIV infection is also more common in young adults than children . As shown in Table 1 , the lowest age in this VL-HIV cohort was 18 years old . However , if we were to treat a younger ( <18 years old ) VL-HIV co-infected patient cohort with this combination regimen , probably those <5 years old would have high case fatality rates , that would be comparable to those of patients aged >40 years in this cohort . This is because several studies have shown that younger HIV negative VL patients have higher risk of death [49 , 51 , 55] . AmBisome and miltefosine would still be the treatment of choice , however , an allometric dosing table for miltefosine should be used in children , as it might improve treatment outcomes [56] . There are some limitations to this study . Diagnosis and cure were not systematically confirmed by parasitological tests . Fifty-seven ( 88 . 0% ) of the patients whose cure was assessed clinically had non or barely palpable spleen at the end-of-treatment , inhibiting performing a spleen aspirate , they declined having a bone marrow aspirate because the procedure is painful and they didn’t have palpable lymph nodes . This occurs commonly in settings without non-invasive investigations to assess VL cure . We acknowledge that this could likely lead to some degree of underestimation of the failure rates . However , it is important to note that in this cohort of patients , the more ill patients at admission ( for instance with tuberculosis co-infection ) and those more likely to fail ( e . g . patients with a history of VL ) were more likely to get a parasitological test for confirmation of cure at the end of treatment . Furthermore , in a recent study from this setting , we found no difference in long term outcomes ( relapse or death ) among patients with treatment outcome at discharge of parasitological cure versus those with clinical cure [8] . In a worst-case scenario , assuming similar failure rates for those with clinical cure compared to those undergoing tissue aspiration , the overall failure rates would still only be 6 . 4% , clearly better as what has been reported with miltefosine and AmBisome monotherapy . While longer patient follow-up to report on the relapse rates would have been of interest , this was not done as some patients were included in the pentamidine secondary prophylaxis trial , which has been published recently [11] . Indeed , to prevent relapse , secondary prophylaxis is likely the most important intervention , and not the initial treatment [10] . Consequently , the focus of this paper was on the initial effectiveness of the combination regimen in achieving parasitological cure , which is a prerequisite before starting secondary prophylaxis . In this study , CD4 counts were missing for a significant proportion of patients . Working in a remote area with relatively limited capacity , we did not have the capacity to perform autopsies . However , basing on clinical experience , some of the underlying causes of death include: severe anemia , severe pneumonia , tuberculosis , hepatic failure and sepsis [35 , 57 , 58] . Also , as a retrospective study , we could only study predictors from the collected variables . In conclusion , we determined the initial effectiveness of a combination regimen of AmBisome and miltefosine for treatment of VL in HIV co-infected patients in Ethiopia . Initial parasitological failure rates were very low with AmBisome and miltefosine combination therapy when compared with the initial parasitological failure rates with either drug administered as monotherapy [15 , 24] . Therefore , this combination regimen seems a suitable VL treatment option in HIV patients . These findings remain to be confirmed in clinical trials . After achieving initial cure , those at high risk of VL relapse should be initiated on secondary prophylaxis .
North-west Ethiopia faces the highest burden world-wide of visceral leishmaniasis ( VL ) and HIV co-infection . VL treatment outcomes in HIV co-infected patients are associated with high initial treatment ( parasitological ) failure and recurrence rates after cure ( relapse ) . With secondary chemoprophylaxis , the risk of relapse can be reduced . However , with the current VL treatment regimens , the initial parasitological failure rates remain high . In this study , we aimed to determine the initial effectiveness of a combination of liposomal amphotericin B ( AmBisome ) and miltefosine for treatment of VL in HIV patients in Ethiopia . We conducted a retrospective study using routine program data from a Médecins Sans Frontières—supported health center in north-west Ethiopia . We included 173 adult VL-HIV co-infected patients treated for VL with a combination of AmBisome and miltefosine . Initial cure rate was 83 . 8% , death rate 12 . 7% and parasitological failure rate 3 . 5% . Tuberculosis co-infection at VL diagnosis was predictive of initial parasitological failure . Predictors of death were age >40 years , hemoglobin ≤6 . 5 g/dL and primary VL . Initial parasitological failure rates were very low with AmBisome and miltefosine combination therapy . This regimen seems a suitable treatment option . Knowledge of predictors of poor outcome may facilitate better management . These findings remain to be confirmed in other studies .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "kala-azar", "medicine", "and", "health", "sciences", "immune", "physiology", "pathology", "and", "laboratory", "medicine", "antiviral", "therapy", "pathogens", "spleen", "immunology", "tropical", "diseases", "microbiology", "parasitic", "diseases", "parasitology", "retroviruses", "viruses", "preventive", "medicine", "immunodeficiency", "viruses", "rna", "viruses", "antiretroviral", "therapy", "neglected", "tropical", "diseases", "vaccination", "and", "immunization", "public", "and", "occupational", "health", "infectious", "diseases", "zoonoses", "medical", "microbiology", "hiv", "microbial", "pathogens", "protozoan", "infections", "hiv", "diagnosis", "and", "management", "diagnostic", "medicine", "tuberculosis", "diagnosis", "and", "management", "viral", "pathogens", "leishmaniasis", "physiology", "biology", "and", "life", "sciences", "lentivirus", "organisms" ]
2018
The initial effectiveness of liposomal amphotericin B (AmBisome) and miltefosine combination for treatment of visceral leishmaniasis in HIV co-infected patients in Ethiopia: A retrospective cohort study
Rotaviruses ( RVs ) are the leading cause of severe gastroenteritis in young children , accounting for half a million deaths annually worldwide . RV encodes non-structural protein 1 ( NSP1 ) , a well-characterized interferon ( IFN ) antagonist , which facilitates virus replication by mediating the degradation of host antiviral factors including IRF3 and β-TrCP . Here , we utilized six human and animal RV NSP1s as baits and performed tandem-affinity purification coupled with high-resolution mass spectrometry to comprehensively characterize NSP1-host protein interaction network . Multiple Cullin-RING ubiquitin ligase ( CRL ) complexes were identified . Importantly , inhibition of cullin-3 ( Cul3 ) or RING-box protein 1 ( Rbx1 ) , by siRNA silencing or chemical perturbation , significantly impairs strain-specific NSP1-mediated β-TrCP degradation . Mechanistically , we demonstrate that NSP1 localizes to the Golgi with the host Cul3-Rbx1 CRL complex , which targets β-TrCP and NSP1 for co-destruction at the proteasome . Our study uncovers a novel mechanism that RV employs to promote β-TrCP turnover and provides molecular insights into virus-mediated innate immunity inhibition . β-transducin repeat-containing protein ( β-TrCP , encoded by BTRC ) is the core substrate recognition component of the Skp1-Cul1-F-box ( SCF ) β-TrCP E3 ubiquitin ligase complex , which plays essential roles in a variety of biological processes , including apoptosis , cell cycle , carcinogenesis and innate immunity [1–3] . β-TrCP was originally discovered as an HIV-1 accessory protein Vpu-interacting protein that the virus hijacks for CD4 degradation to prevent super-infection [4] . β-TrCP recognizes a specific phosphorylated DSGX ( 2+n ) S motif , known as a phosphodegron , present in its substrates such as β-catenin and IκBα , which are subsequently targeted for ubiquitin-mediated degradation [5 , 6] . In the canonical nuclear factor-κB ( NF-κB ) signaling cascade , pro-inflammatory cytokines or PRR ( pattern recognition receptor ) ligands stimulate rapid IκB phosphorylation , via the IKK complex , creating a phosphodegron recognized and ubiquitinated by the SCFβ-TrCP complex , and thus targeted for proteasomal degradation [7] . With the destruction of IκB , the otherwise sequestered NF-κB p65/p50 heterodimer is able to translocate from cytoplasm to the nucleus and activate a multitude of downstream genes , including chemokines and interferon ( IFN ) [8] . Therefore , β-TrCP is indispensable for an intact NF-κB signaling and optimal antiviral response . Despite its significance in modulating many biological processes , how β-TrCP itself is regulated remains largely unknown . The leading cause of severe dehydration and often life-threatening diarrhea in children , rotaviruses ( RVs ) are responsible for an annual death rate of over 215 , 000 people worldwide , particularly in underdeveloped countries where current vaccines are significantly less effective [9 , 10] . RV is highly infectious and well known for its extraordinary ability to counteract host innate immunity [11 , 12] , an effect primarily mediated by the non-structural protein 1 ( NSP1 ) both in vitro and in vivo [13–15] . Interestingly , the ability of individual NSP1s derived from different RV isolates to counteract the innate immune response is highly host range restricted and displays a profound functional divergence in their mode of assisting virus replication . While NSP1s from multiple human and porcine RVs mediate the degradation of β-TrCP to inhibit the NF-κB pathway , NSP1s from other animal RV strains preferentially degrade interferon regulatory factor ( IRF ) proteins ( i . e . IRF-3 , 5 , 7 , 9 ) to block IFN production [16–19] . Traditionally , NSP1 has been categorized as a viral E3 ligase due to the presence of an N-terminal RING-finger domain [11 , 20] . However , biochemical evidence to corroborate this hypothesis is lacking . Recently , a phosphodegron-like ( PDL ) motif was identified in NSP1 of human and porcine RVs and this motif is required for inhibition of NF-κB signaling [21] , potentially serving as a pseudo-substrate antagonist of β-TrCP [22] . The precise molecular mechanism by which NSP1’s targets are identified and degraded remains unclear . Systematic identification of protein-protein interactions ( PPIs ) has proven instrumental for understanding how viruses usurp the host machinery to manipulate and repurpose signal transduction pathways . Recently , multiple viral pathogens , including HIV , HCV , influenza , and KSHV , have been successfully interrogated using such mapping strategies [23–26] . Here , using a comparative proteomics approach to examine the NSP1 “interactome” , we report that components of host Cullin-RING ubiquitin ligase ( CRL ) complexes , in particular , the cullin-3 ( Cul3 ) CRL scaffold protein and the shared E3 ubiquitin ligase RING-box protein 1 ( Rbx1 ) , are essential for RV NSP1 mediated degradation of β-TrCP . NSP1 , via its COPII sorting motif , localizes to the Golgi apparatus during RV infection and mediates the interaction between Cul3 CRL and β-TrCP with its N- and C-terminal domains respectively . NSP1 along with its substrate β-TrCP are subsequently coordinately degraded at the proteasome . Blocking the activity of Cul3 or Rbx1 , by either small interfering RNA ( siRNA ) knockdown , chemical inhibition , or dominant-negative mutants , significantly impedes NSP1’s ability to down-regulate β-TrCP and is detrimental for RV replication . These findings demonstrate that RV NSP1 , through re-directing the host Cul3-CRL complex , launches a suicide attack on β-TrCP , block NF-κB activation and thereby provide a permissive cellular environment for efficient viral propagation . To systematically interrogate the complex molecular interactions between rotavirus and host , we recently employed a quantitative proteomics approach to construct a comprehensive interaction network map and identify host factors that interact with each of the twelve RV proteins . In this study , we focus specifically on the PPIs of NSP1 , the pivotal RV virulence gene that assists virus replication through inhibition of the IRF and NF-κB signaling cascades [15] . To directly compare the differences between NSP1s derived from various RV strains , we adopted the G-LAP-Flp strategy , previously devised for mammalian proteomics studies [27] , by fusing a LAP tag ( EGFP-TEV-S-peptide ) to the N-terminus of the selected NSP1 proteins and then generating doxycycline-inducible HEK293 stable cell lines expressing NSP1s from two human ( WA , ST3 ) and four animal RV strains ( two simian RRV , SA11-5S , one murine ETD and one bovine UK ) ( Fig 1A ) . Following tandem-affinity purification and TEV protease cleavage to remove the EGFP tag , we separated eluted proteins using SDS-PAGE and visualized both NSP1 itself and a multitude of bands corresponding to host proteins by silver staining ( Fig 1B ) . By means of liquid chromatography mass spectrometry ( LC-MS/MS ) and rigorous bioinformatics analysis , we identified hundreds of host factors for each NSP1 and constructed maps of high-confidence PPIs ( S1–S6 Tables and Fig 1C ) . The strength of the interactions was scored based on the absolute number of spectral counts observed and the percentage of peptide coverage ( S1A Fig ) . The PPI network revealed several interesting findings . First , we noted that the two best characterized NSP1 substrates for degradation , IRF3 and β-TrCP , bind strongly to NSP1 in a strain-specific manner ( Fig 1D ) . NSP1s from simian ( RRV ) and murine ( ETD ) RV strains exclusively bind to IRF3 while those from the two human ( Wa , ST3 ) strains bind to β-TrCP . Interestingly , the bovine ( UK ) strain NSP1 interacts with both substrates , likely representing an evolutionarily intermediate viral protein . Another simian RV strain ( SA11-5S ) encodes a naturally occurring defective NSP1 mutant due to a C-terminal 17 amino acid truncation and it serves as the negative control that binds to neither IRF3 nor β-TrCP . Importantly , using the HEK293 stable expression cell lines and a transient transfection strategy , we confirmed that the protein degradation pattern perfectly matched the interaction data ( Fig 1E and S1B Fig ) . Therefore , a functional dichotomy is present in human versus animal NSP1s’ ability in substrate binding and subsequent degradation of either IRF3 or β-TrCP . Notably , two other previously reported NSP1 substrates , MAVS and TRAF2 [28 , 29] , were not identified in our interaction data and not observed to be degraded upon doxycycline induction ( Fig 1E ) . Second , we observed interactions between NSP1 and a host of proteins belonging to the CRL complexes , including Cullins 1–7 , the shared E3 ligase subunit Rbx1 and other CRL-associated components and regulatory factors ( Fig 1D ) . Cul3 has been previously observed to interact with porcine OSU-NSP1 [30] and more recently with NSP1s from several human and animal RV strains [31] . Our proteomics data has allowed us to not only confirm the Cul3 binding of NSP1 but also expand to the breadth of the analysis to multiple other cullin members and associated proteins . Similar to β-TrCP , Cul1 and FBXW11 specifically interact with Wa , ST3 and UK NSP1s whereas other proteins , including Cul2 , 3 , 5 and Rbx1 are broadly reactive with all the NSP1s . CRLs are multi-protein complexes responsible for targeting many substrates for degradation both in yeast and higher eukaryotes [32] . It is precisely because of their significance that CRL complexes are frequently rewired by viral pathogens for immune evasion purposes [33] . Recently , HBV X protein was reported to hijack a Cul4-DDB1 CRL to target the Smc5/6 complex for degradation to allow productive HBV gene expression [34] . Therefore , we hypothesized that in the case of NSP1 , certain CRLs were being appropriated by specific RV strains to favor their replication in a host range restricted fashion . The expansive interaction of several NSP1s with Rbx1 raised an important question as to whether NSP1 , by itself , functions as the purported viral E3 ligase or may redirect CRLs towards specific targets . Third , our data provided quantitative profiling of host E2 ubiquitin-conjugating enzymes that co-precipitated with different NSP1s ( S1C Fig ) . Of note , the in vitro reconstitution of ubiquitin ligase activity using recombinant NSP1 has not been reported , which could be due to the lack of the proper E2 proteins . Several of these E2 enzymes are present at very low abundance [35] and might only be revealed by a large-scale proteomics survey such as this study . Finally , we detected several previously unreported NSP1-interacting host proteins ( S1–S6 Tables ) , exemplified by the CCT complex , which assists protein folding by acting as chaperone [36] , AIFM1 , an apoptosis-inducing factor [37] , and TRIM28 , a transcription factor that is also known as KAP1 and regulates the DNA damage response [38] . These newly identified NSP1 binding partners may unveil potentially novel regulatory functions of NSP1 other than modulating the innate immune response and will be examined in subsequent studies . Based on the NSP1 interactive networks , we next set out to mechanistically characterize one of the highly enriched interactions/biological pathways , the CRL complex . We first validated the initially observed interactions ( Fig 1D ) between NSP1 and Rbx1 , Cul1 , Cul3 and β-TrCP by co-immunoprecipitation ( IP ) of transiently overexpressed NSP1s , Rbx1 and Cul3 and in the context of virus infection ( Fig 2A–2C ) . Consistent with the high-throughput MS data , NSP1s from all RV strains co-purified with exogenously expressed Myc-tagged Cul3 and HA-tagged Rbx1 ( Fig 2A ) . In addition , in pull-down experiments using lysates from HEK293 cells stably expressing Wa-NSP1 , we observed that NSP1 co-precipitated with endogenous Cul1 , Cul3 , Rbx1 and β-TrCP ( Fig 2B ) . Importantly , during Wa RV infection , we demonstrated that the natively expressed untagged Wa-NSP1 also co-precipitated with endogenous Cul3 ( Fig 2C ) . It is noteworthy that Cul3 and β-TrCP only bound to one another during Wa RV infection , consistent with our previous knowledge of no reported interaction in the Wa-NSP1 network ( Fig 1C ) . After confirming the biochemical association between CRL components and NSP1 , we began to assess their functional role using targeted siRNA knockdown . Although silencing of Rbx1 , Skp1 and multiple Cullin members ( Cul1 , 2 , 3 , 5 ) did not affect IRF3 degradation by NSP1s derived from RRV and ETD strains ( Fig 2D and S2A Fig ) , depletion of Rbx1 , Cul1 or Cul3 by siRNA led to impaired β-TrCP degradation by Wa-NSP1 ( Fig 2E and S3A Fig ) . In contrast , despite Cul2 and Cul5 binding to Wa-NSP1 ( Fig 1D ) , specific siRNA against these two cullins , as well as those targeting Cul4A , 4B , 7 , and an irrelevant E3 ligase HECTD1 did not affect β-TrCP reduction by Wa-NSP1 ( Fig 2E , S2B and S2C Fig , and S3A and S3B Fig ) . These results highlight the specificity of Rbx1 , Cul1 , and Cul3 for regulating β-TrCP turnover . Moreover , we examined NSP1s from ST3 and UK strains , also capable of inducing β-TrCP degradation ( Fig 1E ) . The reduced β-TrCP levels were significantly restored in both Rbx1-knockdown and Cul3-knockdown cells ( Fig 2F ) , suggesting a common regulatory mechanism of β-TrCP . To exclude the possibility that our observation is cell type-dependent , we also tested the efficacy of Cul3 siRNA on preventing β-TrCP degradation in MA104 cells , an African green monkey cell line commonly used for RV propagation . Consistently , simian β-TrCP down-regulation induced by human RV Wa strain infection was counteracted by Cul3 depletion ( S2D Fig ) . In addition to siRNA silencing , we attempted to completely knock out Cul3 and Rbx1 in HEK293 cells via CRISPR-Cas9 genome editing . However , screening of several hundred colonies using three independent sgRNA sequences yielded only partial depletion of either gene , strongly suggesting the requirement of Cul3 and Rbx1 for cell survival , consistent with the reported phenotype of early embryonic lethality for both Cul3-/- and Rbx1-/- mice [39 , 40] and recently published gene essentiality list [41] . Nevertheless , even though Cul3 was not completely depleted , significant reduction in endogenous Cul3 levels led to pronounced inhibition of β-TrCP degradation mediated by Wa and ST3-NSP1 ( S2E Fig ) . As an alternative to confirm the function of Cul1 , Cul3 and Rbx1 in promoting β-TrCP degradation , we treated Wa-NSP1 expressing cells with MLN4924 , a small-molecule inhibitor that inactivates the NEDD8-activating enzyme , which is critical for the catalytic cycle of all known Cullins [42] . MLN4924 treatment efficiently blocked Wa/ST3-NSP1-mediated β-TrCP degradation at inhibitory concentrations ( Fig 2G ) , paralleling the results with siRNA knockdown of Rbx1 and Cul3 . The levels of Nrf2 , a well-defined substrate of Cul3/Keap1/Rbx1 complex [43] , also increased upon inhibitor treatment ( Fig 2G ) . Taken together , our results strongly support the conclusion that the participation of host proteins Cul1 , Cul3 , and Rbx1 is required for NSP1-mediated degradation of β-TrCP . In the canonical NF-κB pathway , RelA ( p65 ) and NF-κB1 ( p50 ) subunits are held inactive and cytoplasmically sequestered by IκB . Following stimulation by pro-inflammatory cytokines or virus infection , SCFβ-TrCP complex targets IκB for degradation , releasing the brake on the p65/p50 heterodimer , whose translocation into the nucleus drives the expression of IFN and chemokines [7 , 8] . We hypothesized that Cul3 siRNA silencing , which abrogates NSP1-mediated β-TrCP degradation , should restore the NF-κB signaling . In line with our previous findings , at steady state , induced Wa-NSP1 led to a marked decrease in β-TrCP levels ( Fig 3A , left ) . Cul1 and Rbx1 siRNA modestly rescued β-TrCP and Cul3 siRNA had the greatest effect ( Fig 3A , left ) . Post TNF-α stimulation , β-TrCP promoted the degradation of IκBα , the major isoform of the IκB , but was counteracted by NSP1 expression ( Fig 3A , right ) . Importantly , concurrent with Cul3 depletion , NSP1 was no longer able to induce β-TrCP degradation and IκBα degradation was restored ( Fig 3A , right ) . To determine whether restoring IκBα degradation by Cul3 inhibition would activate NF-κB , we next examined p65 nuclear translocation by immunofluorescence . In contrast to mock-treated cells , where we observed a significant amount of p65 nuclear staining in response to TNF-α or IL-1β treatment , p65 remained completely cytoplasmic in Wa-NSP1 expressing cells ( Fig 3B , left ) . Rbx1 is the key E3 ubiquitin ligase of the SCFβ-TrCP complex that mediates IκBα degradation and its knockdown also retained p65 in the cytoplasm similar to Wa-NSP1 ( Fig 3B , middle ) . Notably , Cul3 silencing up-regulated β-TrCP levels , resulting in IκBα degradation , and partially restored p65 translocation into the nucleus ( Fig 3B , right ) . We further measured downstream NF-κB target genes , whose expression was strongly suppressed by RV NSP1 . Wa-NSP1 significantly inhibited TNF-α-induced CXCL10 by down-regulation of β-TrCP without affecting its mRNA level ( Fig 3C , left and S3C Fig ) . Concomitant with efficient Cul3 depletion ( Fig 2E and S3A Fig ) , β-TrCP was no longer degraded and CXCL10 expression was restored to almost unperturbed levels ( Fig 3C , left ) . Similarly , poly ( I:C ) -induced chemokine was also blocked by Wa-NSP1 and rescued by Cul3 knockdown ( S3D Fig ) . The effect of Cul3 on the NF-κB pathway was specific since RSAD2 , an interferon-stimulated gene ( ISG ) , was not affected with IFN-β stimulation ( Fig 3C , right ) . Besides Wa-NSP1 , CXCL10 inhibition by UK-NSP1 was also lifted with Cul3 knockdown while having minimal effect on ISG expression ( Fig 3D ) . Thus , our results demonstrate that reduced Cul3 levels abolished β-TrCP degradation , which in turn led to the restoration of IκB degradation , re-introduction of p65 nuclear translocation , and induction of chemokine expression . Given the pivotal role of Cul3 in β-TrCP turnover , we further tested how its depletion and the resultant restoration of NF-κB signaling would affect RV growth . We measured both cell-associated viral RNA and extracellular virus titers for simian RRV and human Wa strains . Consistent with our prior findings , blocking Cul3 did not exert an inhibitory effect on RRV replication ( Fig 3E and 3F ) , since the RRV NSP1’s ability to induce IRF3 degradation was Cul3-independent ( Fig 2D ) . In marked contrast , both intracellular RNA genome copies and virus yield of Wa strain in the supernatant were negatively impacted by Cul3-CRL inhibition ( Fig 3E and 3F ) , highlighting the importance of β-TrCP degradation in promoting human RV replication and the virus dependence on host Cul3-CRL complex . Based on the knowledge that NSP1 might be repurposing the host Cul3-CRL complex to induce β-TrCP degradation , we next sought to delineate the underlying molecular mechanisms . Multiple host and pathogen proteins contain the orthodox COPII sorting motif , composed of a transmembrane ( TM ) domain , a tyrosine residue and a spaced diacidic signal ( S4A Fig ) . We noted two such motifs present in Wa-NSP1 , one within the N-terminal RING-finger domain and the other at the very C-terminus . A further examination of NSP1 sequences revealed evolutionary conservation of these motifs ( S4A Fig ) . The COPII coated vesicles are responsible for sorting and trafficking cargo out of the ER and into the Golgi apparatus [44] . Thus , we asked whether NSP1 localizes to the Golgi and whether this localization is necessary for its proper function . Since we did not have a good antibody that recognizes NSP1 by staining , we examined the localization of GFP-tagged NSP1 . Indeed , supporting our hypothesis , we observed at least two populations of Wa-NSP1 with distinct subcellular localizations; one subset with bright punctuate clusters co-localized with the Golgi marker GM130 and the other subset characterized by a more diffuse and weaker signal ( Fig 4A ) . In addition to GM130 , we also observed clear co-localization of NSP1 with two alternative Golgi markers , golgin-97 and giantin ( S4B Fig ) . We also examined NSP1 signal with Wa RV super-infection and were able to detect a similar Golgi localization pattern ( Fig 4B ) . Despite the bright NSP1 clusters , the general Golgi morphology remained unchanged during transfection and early virus infection ( Fig 4A and 4B ) . Additional staining further confirmed that NSP1 was not present at mitochondria ( S4C Fig ) . While Rbx1 is present in both nucleus and cytoplasm [45] , Cul3 is known to be Golgi-resident [39 , 46] . To complement the immunofluorescence analysis , we performed biochemical isolation of subcellular organelles based on their sedimentation coefficient , which also revealed that during Wa RV infection , NSP1 co-fractionated with GM130 and β-tubulin , indicative of Golgi and cytoskeleton respectively ( Fig 4C ) . Notably , in fractions 5 and 6 , with the strongest GM130 signal , there was a substantial amount of Wa-NSP1 , Cul3 , Rbx1 , and β-TrCP ( Fig 4C ) . Interestingly , NSP1s from RRV and UK strain , both with COPII sorting motifs , also localized to the Golgi with a similar speck-like pattern ( S4D Fig ) . Despite RRV-NSP1 localization to the Golgi and interaction with Cul3 , it does not induce β-TrCP degradation , suggesting that Golgi localization and Cul3 interaction are insufficient for β-TrCP degradation . To directly interrogate how the interactions of NSP1 , Cul3 , and β-TrCP take place at the Golgi and what role NSP1 plays in this multi-protein complex , we designed a series of NSP1 mutants based on previous knowledge of NSP1 domains ( Fig 5A ) . We examined their ability to: 1 ) localize to the Golgi; 2 ) interact with Cul3; and 3 ) cause β-TrCP degradation . Interestingly , M83* NSP1 , with the minimal RING-finger domain , displayed Golgi localization but did not overlap with the actin filament staining , in contrast to WT NSP1 accumulation on the cytoskeleton [47] . ( S5A and S5B Fig ) . The other mutants , N176* , C324* and A476* , which compared to M83* contains an additional cyto-binding domain , localized to Golgi and actin filaments similar to the WT protein ( S5A Fig ) . Not only did all the Wa-NSP1 deletion mutants retain their Golgi localization ( S5A Fig ) , they were also co-purified with endogenous Cul3 ( Fig 5B ) , suggesting that within NSP1 , the Cul3 binding domain also maps to the RING-finger domain . Strikingly , despite the unperturbed interaction with Cul3 and Golgi localization , none of these mutants were able to induce β-TrCP degradation as efficiently as the full-length Wa-NSP1 ( Fig 5C ) , reminiscent of the NSP1 derived from simian RRV strain ( Fig 1D and S4D Fig ) . Consistently , all the NSP1 deletion mutants failed to dampen the luciferase expression driven by the NF-κB signaling ( Fig 5D ) . To further examine how the Golgi localization of NSP1 might affect its degradative activity , we generated an NSP1 mutant with the N-terminal RING-finger domain removed . This mutant , which we named RINGless NSP1 , exhibited cytoplasmic staining and did not co-localize with the Golgi as did the WT protein ( S6A Fig ) . Importantly , RINGless NSP1 also completely lost its ability to mediate β-TrCP degradation and failed to inhibit TNF-α induced NF-κB activation ( S6B and S6C Fig ) . Altogether , these findings support our model that the Golgi localization and subsequent interaction with Cul3-CRL are necessary but not sufficient for β-TrCP degradation . The only difference between WT and A476* NSP1 lies in the last 11 amino acids ( Fig 5A ) , encompassing the reported PDL motif [21] . To pinpoint the precise residues underlying β-TrCP recognition , we introduced point mutations , producing a RING-finger domain mutant ( Rmut ) that disrupts both Zn2+ binding sites ( Fig 5A ) , a C-terminal domain mutant ( Cmut ) that destroys the degron , and a double-mutant defective in both regions . Indeed , Cmut was unable to induce β-TrCP degradation due to loss of ability to bind to the substrate ( Fig 5E and 5F ) , confirming the importance of degron in correctly locating β-TrCP [21] . This offers an explanation for why RRV-NSP1 and Cul3 deletion mutants had the capacity to localize to the Golgi , interact with Cul3 , but were unable to mediate β-TrCP degradation . We believe that for RV NSP1 protein , Cul3 interaction and substrate recognition are executed by its N-terminal and C-terminal domains respectively . Therefore , these events do not necessarily have to be coupled together , accounting for the fact that certain strains ( i . e . RRV ) localize to the Golgi and interact with Cul3 but do not induce β-TrCP degradation . However , in contrast to the reported RING mutant C42A [21] , Rmut that completely destroys the RING domain catalytic sites still retained the ability to degrade β-TrCP ( Fig 5F ) . These findings , together with strong Rbx1 binding , are inconsistent with the hypothesis that NSP1 is the viral E3 ligase . Rather , our results suggest that NSP1 interacts with Cul3 and β-TrCP using its N- and C-terminal domains respectively and it functions as an adaptor protein to mediate the interaction between the two at the Golgi . To better understand how the hijacked Cul3-CRL complex promotes β-TrCP turnover , we examined possible ubiquitin ( Ub ) modifications on β-TrCP . Only in the presence of Wa-NSP1 did we observe strong poly-Ub ladder pattern , from approximately 62 kD of the unconjugated protein all the way to the top of the gel ( Fig 6A ) . Importantly , the Ub pattern was potently inhibited with Cul3 silencing , indicating an important role of the CRL in marking β-TrCP for ubiquitination ( Fig 6A ) . We further confirmed this finding in the context of RV infection and β-TrCP was only Ub-modified during Wa infection , where NSP1 was expressed ( Fig 6B ) . Based on Ub modification and reduced β-TrCP levels , we speculated that β-TrCP might be shuttled to the proteasome for destruction . Indeed , none of the lysosome inhibitors blocked NSP1-mediated β-TrCP degradation ( S7A Fig ) . On the other hand , although MG-132 was minimally effective ( S7B Fig ) , lactacystin potently up-regulated β-TrCP levels ( S7C and S7D Fig ) . Lactacystin , unlike MG132 and bortezomib , inhibits the proteasome through non-reversible covalent bonds at the N-terminus threonine residue in the β-1 subunit of the 20S proteasome [48] , and this distinct mechanism of action could account for its efficacy . Carfilzomib , another irreversible inhibitor , was also effective at restoring β-TrCP levels ( S7D Fig ) . Taken together , these experiments demonstrate that NSP1 utilizes Cul3-CRL complex to mark β-TrCP for degradation through the ubiquitin-proteasome pathway . Surprisingly , concomitant with enhanced β-TrCP levels with proteasome or CRL inhibition , we observed a dose-dependent increase in Wa-NSP1 levels as well ( Fig 6C ) . This is consistent with the previously observed up-regulation of Wa and ST3 NSP1 levels with Cul3 CRISPR-mediated partial depletion ( S2E Fig , right panel ) , implying that besides β-TrCP , NSP1 itself was also regulated by the hijacked Cul3-CRL complex . We confirmed , in the context of wild type RV infection , that the stabilization of NSP1 by MLN4924 treatment was specific since the levels of Wa VP6 , an RV structural protein , were not affected under these conditions ( Fig 6D ) . We then postulated that other viral proteins that hijack host CRL complexes could also be employing the same mechanism for “co-destruction” with their substrates . To test this hypothesis , we examined the levels of HBV X protein ( HBx ) , HIV accessory protein Vif , and HPV oncoprotein E7 , which hijack Cul4 Cul5 , and Cul2-CRL to respectively target Smc5/6 complex , APOBEC3G , and retinoblastoma tumor suppressor protein ( Rb ) for degradation [34 , 49 , 50] . Strikingly , treatment with either MLN4924 or lactacystin led to a marked increase in the levels of all three of these viral proteins and their corresponding substrates ( Fig 6E ) . This is consistent with the previous report of poly-ubiquitination of HIV-Vif [51] and that all of these viral proteins invariably have a relative short half-life time: 30 min for HBx [52] , 46 min for HIV-Vif [53] , 55 min for HPV-E7 [54] and ~90 min for RV NSP1 [55] . Taken together , this data suggests a novel yet seemingly common strategy for viral non-structural proteins that utilize the host CRL complexes to attack selected host proteins to also “sacrifice” themselves in the process by undertaking a suicide mission that results in the co-degradation of the specific viral protein and its substrate , which in the case of RV are NSP1 and β-TrCP . Previous studies indicate that Cul3 requires substrate recognition modules known as BTB-box proteins to constitute the BTB-Cul3-Rbx1 CRL complex [56] . To test whether BTB-box proteins are needed for NSP1 function , we transfected Wa-NSP1 cells with Cul3 mutants and examined β-TrCP degradation . Two of these mutants , ΔN41 and H2M/H5M , with the N-terminal 41 residues and helices 2 , 5 removed respectively , are unable to make contact with BTB-box proteins [57] . We hypothesized that if NSP1 acts as the substrate recognition subunit of the multi-protein complex , there would be no necessity for BTB-box proteins . Indeed , ectopic expression of either ΔN41 or H2M/H5M Cul3 did not abolish β-TrCP degradation by NSP1 ( S7E Fig ) , suggesting that in this scenario , Cul3 functions differently from the traditional CRL complex . However , expression of another dominant-negative mutant Cul3 ΔC ( Cul3N418 ) , which is defective in Rbx1 binding [58] efficiently restored β-TrCP levels in Wa-NSP1 expressing cells ( S7E Fig ) , indicating that Rbx1 in association with Cul3 rather than Cul1-interacting Rbx1 primarily contributed to the E3 ligase activity . Since most of our experiments were conducted in cell culture , we next assessed whether or not inhibition of Cul3 CRL activity could also rescue β-TrCP from NSP1 degradation in a more physiologically relevant system . We took advantage of nontransformed , three-dimensional human intestinal epithelial cell ( IEC ) organoids , which are derived from subject biopsies , consist entirely of IECs , and can recapitulate the biological architecture of the small intestine epithelium ( Fig 7A ) [59] . The human IEC enteroids fully supported vigorous replication and propagation of human RVs ( Fig 7B ) . Importantly , consistent with our previous findings , MLN4924 treatment significantly up-regulated the levels of β-TrCP in human RV Wa-infected EpCAM+ IECs ( Fig 7C ) , further corroborating the positive roles of host CRL in β-TrCP degradation by human RVs . Rotavirus infection remains a global threat to public health , especially in underdeveloped countries where prophylactic vaccination has been only partially successful . This is due to many reasons including the inadequate understanding of several critical aspects of virus-host interactions . Although RV encodes only 11~12 proteins depending on the strain , assigning specific functions to individual RV proteins has been difficult in the absence of a tractable reverse-genetics system . In the present study , using an unbiased tandem AP-MS proteomics approach , we comprehensively investigate the host protein interaction network for six NSP1s ( two human and four animal RV strains ) , the viral protein central to the antagonism of innate immune responses and contributing to host range restriction in vivo . This work provides mechanistic insights into how RVs intervene with the innate immune response and specifically how certain NSP1s effectively block NF-κB signaling by facilitating β-TrCP degradation . Our work demonstrates , for the first time , that NSP1s from multiple RV strains strongly interact with the host CRL complex ( Fig 1D ) and that this interaction appears to take place at the Golgi ( Fig 4 ) . Co-localization of NSP1 and Golgi was demonstrated by immunofluorescence staining and gradient density co-sedimentation ( Fig 4 ) . In addition , deletion of a Golgi-localization signal containing region at the N-terminus of NSP1 eliminated Golgi localization and NSP1’s ability to degrade β-TrCP ( S6 Fig ) . Additionally , our work demonstrates blocking Cul3 function , either by siRNA , inhibitor or a dominant-negative mutant , reduces or eliminates NSP1’s ability to cause β-TrCP degradation ( Fig 2 ) and negatively impacts RV replication ( Fig 3E ) . Along with Cul3 depletion , we observe a profound decrease in β-TrCP poly-ubiquitination ( Fig 6A ) and an increase in endogenous β-TrCP levels , both in cell culture and during actual RV infection in human IEC organoids ( Fig 7C ) . Therefore , we have uncovered a novel mechanism that RV NSP1s utilize to degrade β-TrCP by rewiring the host Cul3-CRL complex . Although several viral proteins that interact with Cul3 have been previously reported [60–62] , RV is unique in that NSP1 acts upstream in the NF-κB cascades by directly mediating the degradation of β-TrCP and itself ( Fig 8 ) . Interestingly , this co-destruction seems to be a rather common mechanism utilized by multiple viral proteins ( Fig 6E ) . Vif , HBx , E7 and NSP1 are all , without exception , non-structural viral proteins , which might be more “expendable” after they have carried out their specific mission . Our current study is particularly important because it resolves a long-standing controversy in the rotavirus field as to whether or not NSP1 is a viral E3 ubiquitin ligase . Despite the presence of a RING-finger domain , previous examination of its putative E3 ligase activity by the “gold standard” in vitro ubiquitination assay had not been successful . This could be due to 1 ) lack of proper E2 ubiquitin-conjugating enzyme ( s ) , many of which are revealed in this proteome study ( S1C Fig ) , 2 ) lack of additional co-factors , or 3 ) the possibility that NSP1 is not an E3 ligase by itself and its function demands the assistance from one or multiple host E3 ligase ( s ) . Here , we present compelling experimental evidence that β-TrCP degradation is strictly dependent on Rbx1 ( Fig 2E ) . Moreover , NSP1s with the catalytic sites mutated are nonetheless capable of mediating β-TrCP degradation ( Fig 5F ) . Therefore , it appears that Wa-NSP1 does not function as an E3 ligase on its own but instead usurps the host CRL to degrade β-TrCP . It is noteworthy that RRV/ETD-NSP1s target IRF3 for degradation and this process is completely independent of Cul3 and Rbx1 ( Fig 2D ) , highlighting a major difference of NSP1 dependence on host CRL during RV evolution and emphasizing the versatility of various RV strains in identifying substrates . It is interesting to propose whether the NSP1 protein , in the cases of RRV or ETD , might actually function as a bona fide E3 ligase . Future biochemical studies will be needed to clarify this issue . Another interesting question is the rationale behind β-TrCP regulation by Cul3-CRL instead of its own Cul1-SCF complex . It is tempting to speculate the core E3 ligase Rbx1 in the SCFβ-TrCP complex might be spatially distant from β-TrCP ( Fig 8 ) . Possibly there exists steric hindrance for Cul1-asscoated Rbx1 to bend over and mark β-TrCP for poly-ubiquitination and the introduction of an “outsider” Cul3/Rbx1 helps to stabilize the complex and facilitate the addition of poly-Ub chains onto β-TrCP . Supporting this hypothesis , a Cul3 mutant that is unable to bind Rbx1 blocks β-TrCP degradation by NSP1 ( S7E Fig ) . Cul1 is also required ( Fig 2E ) since its presence might stabilize the multi-protein complex . To completely resolve this issue will require follow-up work using atomic level Cryo-Electron Microscopy , which will give mechanistic insights into the precise interactions between these proteins . It would also be important to pinpoint the exact lysine residue ( s ) within β-TrCP and NSP1 that are modified for ubiquitination , and give guidance to generating β-TrCP mutants that are resistant to NSP1-mediated degradation . During the revision of this manuscript , an independent study focusing on a similar topic was published by Lutz et al . [31] . A key finding of that study was that RV NSP1 interacts with host Cul1 and Cul3 in a strain-specific manner , which is completely consistent with our results . However , their second key conclusion was that Cul3 is not involved in the NSP1-mediated degradation of either IRF3 or β-TrCP . This finding is in clear contrast with our data . At this time , we cannot be certain as to the cause of the discrepancy . However , possible sources of the disparity in results might be due to the differences in methodology applied including: 1 ) doxycycline-inducible stable cell lines were used in our study as compared to a transient transfection approach in the Lutz paper; 2 ) we performed siRNA knockdown and inhibitor treatment in HEK293 cells as compared to MA104 cells in the Lutz paper; 3 ) NSP1 origins were not completely the same in the two studies ( Wa , ST3 etc . here versus OSU etc . in the Lutz paper ) . Nevertheless , we reached our conclusion that the host Cul3-Rbx1 E3 ligase complex does play a critical role in mediating β-TrCP degradation by NSP1 on the basis of the following findings presented above: 1 ) multiple experimental tools were utilized including siRNA knockdown , CRISPR , chemical inhibitors and dominant-negative mutants; 2 ) we validated our results in multiple cell types including a primary human enteroid culture system; 3 ) we demonstrated that inhibition of Cul3 not only blocked β-TrCP degradation but also functionally restored the NF-κB pathway and inhibited Wa replication ( Fig 3 ) . Although we have not assigned a role for the other cullins that co-precipitated with NSP1 , it is likely that they also assume important roles in different aspects of NSP1 biology . In summary , we have applied tandem AP-MS to create a global network of RV NSP1-host PPIs , and this approach has provided a new and deeper understanding into how NSP1 efficiently antagonizes the NF-κB signaling by hijacking the host Cul3-CRL complex . By linking individual NSP1s to specific host processes , our work , in conjunction with the ongoing development of an RV reverse genetics , will set the stage to test the functional role of NSP1 both in vitro and in vivo . Finally , this high-resolution comparative proteomics methodology has broad applicability to the study of viral pathogenesis in general and has the potential to uncover , in an unbiased manner , druggable cellular pathways that are required for efficient replication by various viruses . Human embryonic kidney HEK293 cells were obtained from American Type Culture Collection ( ATCC ) and cultured in DMEM supplemented with 10% FBS , 2 mM L-glutamine , 100 IU/ml of penicillin and 100 μg/ml of streptomycin . HEK293-NSP1 stable cell lines were generated from HEK293 cells and cultured in complete DMEM in the presence of puromycin ( 0 . 5 μg/ml ) . Expression of NSP1 was induced by doxycycline ( 1 μg/ml ) treatment for 24 hr . African Green Monkey kidney MA104 cells were obtained from ATCC and cultured in Medium 199 supplemented with 10% FBS , 2 mM L-glutamine , 100 IU/ml of penicillin and 100 μg/ml of streptomycin . Cells were stimulated with TNF-α ( 10 ng/ml ) , IL-1β ( 10 ng/ml ) , IFN-β ( 100 U/ml ) , poly ( I:C ) LMW/LyoVec ( 100 ng/ml ) for 15 min or 6 hr for either western blot/immunofluorescence or QPCR quantification , respectively . Cells were treated with either small-molecule proteasome inhibitors ( 10 μM ) for 12 hr: MG-132 , bortezomib , carfilzomib , VR23 , celastrol , curcumin from Selleckchem , lactacystin and epoxomicin from Enzo Life Sciences; or lysosome inhibitors ( 10 μM ) for 12 hr: chloroquine ( InvivoGen ) , concanamycin A ( Enzo ) , bafilomycin A ( Sigma ) . NEDD8 activating enzyme inhibitor MLN4924 ( Millipore ) was reconstituted in DMSO ( stock concentration: 20 mM ) and used at the range of 100 nM to 10 μM . To best optimize the LAP purification procedure and minimize the possibility of carryover , we have standardized the growth of cells , the preparation of extracts , and the method of tandem affinity purification [27] . Briefly , stable LAP cell lines were harvested using detergent . Lysates were clarified at 43 , 000 rpm and subjected to anti-GFP immunoprecipitation . Bound proteins were eluted from antibody beads using TEV protease , recaptured on S-protein agarose ( Novagen ) , and eluted in 2x NuPAGE sample buffer ( Invitrogen ) . Following purification , great care is taken to ensure a lack of contamination from both environmental sources and from other purified proteins . Each purified set of interacting proteins is separated on an individual 4–12% Bis-Tris polyacrylamide gel and stained with Coomassie brilliant blue . 293 cells samples were run into gels for 20-40mm and divided into 20–40 x1 mm slices . Each excised lane was reduced , propionamidated and digested with trypsin . Peptide identification of each digestion mixture was performed by microcapillary reversed-phase HPLC nanoelectrospray tandem mass spectrometry ( mLC-MS/MS ) on an LTQ-Orbitrap Elite or Fusion mass spectrometer ( ThermoFisher Scientific , Waltham , MA ) . The Orbitrap repetitively surveyed an m/z range from 395 to 1600 , while data-dependent MS/MS spectra on the twenty ( Velos ) or ten ( XL ) most abundant ions in each survey scan were acquired in the linear ion trap . MS/MS spectra were acquired with relative collision energy of 30% , 2 . 5-Da isolation width , and recurring ions dynamically excluded for 60 s . Peptide sequencing and protein inference was facilitated using Byonic following an initial quality control analysis using Preview ( Protein Metrics , San Carlos , CA ) . In a typical Byonic analysis , a 12 ppm mass tolerance for precursor ions and 0 . 4 Da mass tolerance for fragment ions against a species specific ( mouse or human ) . fasta file derived from the NCBI Genbank protein database with custom sequences added for specific tagged bait protein sequences . Fully specific tryptic peptides were accepted , with up to two missed cleavages , and allowing for various common modifications such as methionine oxidation and acetylation of protein N-termini , as well as modifications specific to the pathways investigated . Both protein- and peptide-level false discovery rates were held to an estimated false discovery rate ( FDR ) of <1% using a reverse decoy database strategy . For individual genes identified in each AP/MS sample , we assigned a normalized spectral abundance factor ( NSAF ) to each gene ( g ) [63] . The Sg for a gene is the number of peptides Pg divided by the total number of peptides observed from other genes in the dataset . This includes all peptides except those known to derive from the bait protein and those derived from known exogenous proteins . We exclude , for example , proteins commonly found in human skin and those added during sample preparation . We then divide this score by the mean length of NCBI reference protein isoforms from g ( Lg ) in amino acids . Using a set of eight negative control datasets , we systematically search for genes whose score in an experimental data set is highly unlikely . These filtered genes included in the attached Cytoscape ( http://www . cytoscape . org ) network file , and a manually curated , simplified subset of these are shown in Fig 1 . Human RV Wa strain and simian RV RRV strain were propagated in MA104 cells as previously described [64] . Viruses were activated by trypsin ( 5 μg/ml ) at 37°C for 20 min prior to infection . Cells were washed with serum-free medium ( SFM ) twice and incubated with RV at different MOIs at 37°C for 1 hr . After removal of RV inoculum , cells were washed once with SFM , cultured in either complete medium or SFM and harvested at different time points for QPCR , western blot analysis or plaque assay . pcDNA3-HA-Rbx1 ( #19897 ) , pcDNA3-Myc-Cul3 ( #19893 ) , Cul3-H2M/H5M ( #21591 ) , Cul3-deltaN41 ( #21590 ) , pcDNA3-DN-hCUL3-Flag ( #15820 ) , Flag-β-TrCP ( #10865 ) , HA-tagged Ubiquitin ( #17608 ) were obtained from Addgene . pcDNA3-HA-APOBEC3G was a kind gift from Dr . Reuben Harris ( University of Minnesota ) . pCMV6-Entry encoding HIV-1-Vif ( VC101719 ) , HBV X protein ( VC102194 ) , HPV E7 protein ( VC101903 ) were purchased from Origene . Point mutations and pre-mature stop codons in Wa-NSP1 were introduced into pENTR221 vector using QuikChange II Site-Directed Mutagenesis Kit ( Agilent ) and shuttled into pG-LAP6 destination vector using LR recombination reaction ( Thermo Fisher ) . DNA transfection on HEK293 cells was performed using Lipofectamine 3000 reagent ( Thermo ) at the lipid: DNA ratio of 3:1 [65] . siRNA transfection was performed using RNAiMAX ( Thermo ) according to the reverse transfection protocol . Briefly , 1 . 2 μl of 5 μM siRNA was mixed with 1 μl RNAiMAX in 100 μl OptiMEM and incubated in 24-well plate at RT for 20min . 5×104 HEK293 cells in 500 μl Ab-free DMEM were then added to each well . Further treatment was performed at least 48 hr post transfection . Different siRNA used in this study was listed in S7 Table . HEK293 cells were transiently transfected with pSpCas9 ( BB ) -2A-GFP ( PX458 ) , encoding an sgRNA targeting the 7th coding exon of Cul3 . Single GFP-positive cells were sorted to individual wells of six 96-well plates using a FACSAria II flow cytometer ( BD ) and genomic DNA extracted using the QuickExtract kit ( Epicentre ) . The targeted genomic region was amplified by specific PCR primers ( S7 Table ) using Phusion Hot Start II DNA polymerase ( NEB ) , cloned into Zero Blunt TOPO vector ( Thermo ) . Six independent colonies were extracted with Miniprep ( Qiagen ) and subject to Sanger sequencing . Total RNA was harvested and extracted using RNeasy Mini Kit ( Qiagen ) as previously described [66] . In brief , RNA was converted to cDNA using High Capacity cDNA Reverse Transcription Kit ( Applied Biosystems ) . QPCR was performed using the Stratagene Mx3005P ( Agilent ) with each reaction composed of cDNA reverse-transcribed from 50 ng of total RNA , 12 . 5 μl of Power SYBR Green master mix ( Applied Biosystems ) , and 200 nM both forward and reverse primers in a total volume of 25 μl [67] . SYBR Green primers used in this paper are listed in S7 Table . The Taqman assay for determining viral gene NSP5 expression using a Brilliant III UltraFast QPCR Master Mix kit ( Agilent Technologies ) was performed as previously described [68] . HEK293 cells in 24-well plates ( >90% confluency ) were co-transfected with 1 μg of pG-LAP6 plasmids , 0 . 4 μg of PRDII-Luc ( NF-κB-Luc ) , and 0 . 1 μg of pRL-TK . At 48 hr post transfection , cells were stimulated with TNF-α ( 10 ng/ml ) for 6 hr and lysed in 100 μl Passive Lysis Buffer for dual-luciferase measurement following the manufacturer’s protocol ( Promega ) . SDS-PAGE was performed as previously described [69] . In brief , protein lysates were harvested in RIPA buffer , mixed with 2×Laemmli Buffer , boiled at 95°C for 5 min , and separated on pre-cast SDS-PAGE gels ( Biorad ) . Silver Staining was performed using the Pierce Silver Stain Kit ( #24612 , Thermo ) according to the manufacturer’s instructions . Western blot was conducted with wet-transfer onto nitrocellulose membranes , blocked with TBST with 5% FBS or 5% milk , and incubated with primary antibodies against β-TrCP ( clone D13F10 , Cell Signaling Technology , hereon abbreviated as CST ) ; Cul1 ( #4995 , CST ) ; Cul2 ( A302-476A , Bethyl Lab ) ; Cul3 ( #2759 , CST ) ; Cul4A ( #2699 , CST ) ; Cul4B ( A303-863A , Bethyl Lab ) ; Cul5 ( A302-173A , Bethyl Lab ) ; Flag ( clone M2 , Sigma ) ; GAPDH ( clone poly6314 , Biolegend ) ; GFP ( #2555 , CST ) ; HA ( clone C29F4 , CST ) ; HECTD1 ( A302-908A , Bethyl Lab ) ; IκBα ( #9242 , CST ) ; IRF3 ( clone D6I4C , CST ) ; MAVS ( A310-243A , Bethyl Lab ) ; Myc ( clone 71D10 , CST ) ; Nrf2 ( clone D1Z9C , CST ) ; Rb ( clone 4H1 , CST ) ; Rbx1 ( #4397 , CST ) ; Smc5 ( A300-236A , Bethyl lab ) ; TRAF2 ( clone C192 , CST ) ; poly-Ub WT ( clone P4D1 , CST ) ; rabbit polyclonal antibody against Wa-NSP1 was a kind gift from the Patton lab ( University of Maryland ) ; Secondary incubation was performed with anti-rabbit ( #7074 ) , or anti-mouse ( #7076 ) IgG HRP-linked antibodies . Proteins were visualized using Clarity ECL substrate ( #170–5061 , Biorad ) , Amersham Hyperfilm ( GE Healthcare ) and STRUCTURIX X-ray film processor ( GE Healthcare ) . The intensity of bands in western blot was quantified by densitometry using ImageJ . Cells were rinsed with ice-cold PBS and protein lysates were harvested in 1×lysis buffer ( #9803 , CST ) supplemented with 1 mM PMSF . Lysates were first incubated with Pierce Protein A/G Magnetic beads ( #88802 , Thermo ) at 4°C for 1 hr . Pre-cleared lysates were collected for IP input control and the rest were then incubated with Normal Rabbit IgG Polyclonal Antibody control ( #12–370 , Millipore ) or primary antibodies against Cul3 ( A301-109A , Bethyl Lab ) ; Flag ( M2 affinity gel , A2220 , Sigma ) ; GFP ( ab290 , Abcam ) ; HA ( clone C29F4 , CST ) ; Myc ( clone 71D10 , CST ) at 4°C overnight . Antibody/lysates were further incubated with magnetic beads at RT for 30 min . The complex was washed with 1×lysis buffer for at least three times before added to elution buffer , which was prepared using 3×Blue Loading Buffer mixed with 30×DTT at 10:1 ratio ( #7722 , CST ) . Samples were boiled at 95°C for 5 min and supernatants were collected after centrifugation at 14 , 000 rpm at 4°C for 1 min . For western blot , mouse anti-rabbit Conformation Specific antibody ( clone L27A9 , CST ) was used instead of traditional secondary antibodies . 2×104 HEK293 cells were seeded into poly-D-lysine coated chamber slides ( Nunc , Sigma ) 2 days prior to experiments . Cells were cultured in the presence of MitoTracker Deep Red FM ( M22426 , Thermo ) or LysoTracker Red DND-99 ( L7528 , Thermo ) at 37°C for 30 min . RV-infected or plasmid transfected cells were rinsed with ice-cold PBS ( with addition of Ca2+ ) and fixated in 4% PFA at RT for 10min . Cells were then washed with PBS and incubated with primary antibodies against with α-Flag Alexa-555 ( #3768 , CST ) ; α-Myc Alexa-594 ( #9483 , CST ) ; α-HA Alexa-647 ( #3444 , CST ) ; GM130 ( clone D6B1 , CST ) ; p65 ( clone D14E12 , CST ) in IFA buffer ( 3% BSA , 1% saponin , 1% triton X-100 , and 0 . 02% sodium azide in water ) at RT for 1 hr . After washing with IFA buffer three times , secondary incubation was performed with chicken anti-rabbit-Alexa-594 ( A21442 , Thermo ) at RT for 30 min protected from light . Cells were again washed with IFA buffer three times and PBS three times before staining with phalloidin Alexa-555 ( #8953 , CST ) at RT for 15 min . Stained cells were washed with PBS , mounted with Antifade Mountant with DAPI ( P36962 , Thermo ) , and imaged with Zeiss LSM 710 Confocal Microscope . Micrographs were analyzed and co-localization co-efficient was determined by signal overlay based on the voxels and their intensities using Volocity software v5 . 3 . 2 ( PerkinElmer ) . Duodenal derived primary human intestinal enteroids were kindly provided by Dr . Calvin Kuo ( Stanford University ) . The methods for enteroid culture and RV infection were similar to previous publication [70] . Briefly , 3D culture of intestinal enteroids in matrigel ( Corning ) was maintained in growth media made of advanced DMEM-F/12 media supplemented with several growth factors including epidermal growth factor , Noggin , R-spondin , Wnt3A , nicotinamide , gastrin I , SB202190 , B27 supplement , N2 supplement and acetylcysteine . Two days prior to RV infection , enteroid was switched to differentiation media , which is growth media without Wnt3A , BS202190 , nicotinamide and 50% reduction of Noggin and R-spondin . The enteroids were then lightly treated with TrypLE ( Gibco ) to remove matrigel and infected with human RV Wa strain ( MOI = 1 ) for 1 hr at 37°C . After incubation , new matrigel was added to Wa-infected enteroids for 3D culture and the infected enteroids were cultured in differentiation media for a total of 24 hr at 37°C in 5% CO2 incubator . The enteroids were treated with TrypLE again to obtain single cell suspension before staining . Human intestinal enteroids were infected with Wa ( MOI = 1 ) and treated with MLN4924 ( 1 μM ) for 24 hr prior to harvest . Cells were stained with Live/Dead Aqua Kit ( L34957 , Thermo ) , and primary Ab against β-TrCP ( clone 2H2 , Novus Biologicals ) , secondary Ab goat-anti-mouse-APC ( poly4053 , Biolegend ) , and PE-conjugated anti-human CD326 ( EpCAM ) antibody ( #324206 , Biolegend ) . FITC-conjugated mouse monoclonal ( 1E11 ) antibody against VP6 was generated in our lab and previously characterized [14] . Fluorescence was measured with BD LSR II flow cytometer and data was analyzed with FlowJo Software v8 . 8 . 7 ( TreeStar ) . The results were shown as means ± SEM . Statistical significance was determined by Student's t test using Prism 6 ( GraphPad Software ) . Significant differences are indicated on figures ( *p≤0 . 05; **p≤0 . 01; ***p≤0 . 001 ) .
Rotaviruses ( RVs ) are the leading cause of diarrhea in young children and lead to over 215 , 000 deaths annually worldwide . For virtually every mammal , there are RV strains specifically adapted to replicate efficiently in that host species . The success of RV , to a large extent , derives from its extraordinary ability to suppress the host antiviral responses in a host range restricted manner . One viral protein , named NSP1 , is primarily responsible for this process . In this paper , using an unbiased approach , we discovered that NSP1’s ability to inhibit the host innate immune responses by promoting β-TrCP degradation is dependent on its specific interaction with a protein degradation machine called the Cullin-E3 ligase complex within the RV infected cell . Blocking this complex tremendously reduces NSP1’s ability to antagonize the host immune response and is detrimental for RV replication . Our study uncovers an unexpected role of Cullin-E3 complex in RV immune evasion and has broad implications for other viral pathogens .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "gene", "regulation", "enzymes", "protein", "interaction", "networks", "rna", "extraction", "enzymology", "cloning", "immunoprecipitation", "network", "analysis", "molecular", "biology", "techniques", "ligases", "extraction", "techniques", "research", "and", "analysis", "methods", "small", "interfering", "rnas", "computer", "and", "information", "sciences", "proteins", "gene", "expression", "proteomics", "pathogenesis", "molecular", "biology", "proteasomes", "precipitation", "techniques", "biochemistry", "rna", "protein", "complexes", "nucleic", "acids", "host-pathogen", "interactions", "genetics", "biology", "and", "life", "sciences", "non-coding", "rna" ]
2016
Comparative Proteomics Reveals Strain-Specific β-TrCP Degradation via Rotavirus NSP1 Hijacking a Host Cullin-3-Rbx1 Complex
Leishmaniasis remains a significant cause of morbidity and mortality in the tropics . Available therapies are problematic due to toxicity , treatment duration and emerging drug resistance . Mouse models of leishmaniasis have demonstrated that disease outcome depends critically on the balance between effector and regulatory CD4+ T cell responses , something mirrored in descriptive studies of human disease . Recombinant IL-2/diphtheria toxin fusion protein ( rIL-2/DTx ) , a drug that is FDA-approved for the treatment of cutaneous T cell lymphoma , has been reported to deplete regulatory CD4+ T cells . We investigated the potential efficacy of rIL-2/DTx as adjunctive therapy for experimental infection with Leishmania major . Treatment with rIL-2/DTx suppressed lesional regulatory T cell numbers and was associated with significantly increased antigen-specific IFN-γ production , enhanced lesion resolution and decreased parasite burden . Combined administration of rIL-2/DTx and sodium stibogluconate had additive biological and therapeutic effects , allowing for reduced duration or dose of sodium stibogluconate therapy . These data suggest that pharmacological suppression of immune counterregulation using a commercially available drug originally developed for cancer therapy may have practical therapeutic utility in leishmaniasis . Rational reinvestigation of the efficacy of drugs approved for other indications in experimental models of neglected tropical diseases has promise in providing new candidates to the drug discovery pipeline . Protozoa of the genus Leishmania cause a wide spectrum of human disease [1] . At the severe end of the spectrum , visceral leishmaniasis ( kala azar ) , due to disseminated parasitism of macrophages and dendritic cells , causes an annual mortality of approximately 50 , 000 , largely in India and Sudan [2] . Kala azar has also emerged as a significant problem in the setting of HIV/AIDS , visceral leishmaniasis being the second most common opportunistic tissue protozoal disease ( after toxoplasmosis ) in people infected with HIV [3] . Available therapies for kala azar , including pentavalent antimonials , some ( but not all [4] ) amphotericin B preparations , miltefosine and paromomycin , are problematic due to emerging drug resistance , toxicity , need for lengthy treatment and/or the development of post-kala azar dermal lesions [5] , [6] , [7] , [8] , [9] . There is thus a clear need for novel therapeutic approaches to this neglected tropical disease . Experimental mouse models of Leishmania infection have been used extensively to interrogate the immune system as well as the immunopathogenesis of leishmaniasis [10] , [11] , [12] , [13] . Inoculation of low numbers of L . major into the dermis of C57BL/6 mice is followed by the recruitment of antigen-specific effector CD4+ and CD8+ T cells , IFN-γ production at the site of infection , and activation of the microbicidal effector functions of parasitized macrophages , events manifested clinically by lesion development [13] . IL-10 production by CD4+ T cells is critical to immune counterregulation in this model . Balanced IFN-γ and IL-10 responses are essential for disease resolution and the establishment of life-long latent infection [14] . IFN-γ deficiency or neutralization leads to systemic parasite spread [15] , [16]; IL-10 deficiency or neutralization leads to sterile cure [17] , [18] . A similar balance between IFN-γ and IL-10 responses also appears to be a critical determinant of the outcome of human leishmaniasis [19] . Several relevant IL-10-producing CD4+ T cell subsets have been described , including natural and adaptive regulatory T cells ( Treg ) and Th1 cells that produce IL-10 in addition to IFN-γ [20] , [21] , [22] . Recent studies have emphasized the role played by the latter cells in immune counterregulation in experimental leishmaniasis [20] , [23] and human visceral leishmaniasis [24] . That said , monoclonal antibody-mediated depletion of CD25 ( IL-2R ) -expressing cells , a technique that depletes Treg cells , has been reported to facilitate parasite eradication in experimental leishmaniasis , in models of primary infection and superinfection , as well as in vaccination models [25] , [26] , [27] , [28] . Denileukin diftitox ( rIL-2/diphtheria toxin [DTx] ) , a recombinant fusion protein composed of the membrane-translocating and cytotoxic domains of diphtheria toxin ( Met1-Thr387 ) -His and human interleukin 2 ( Ala1-Thr133 ) , is FDA-approved for the treatment of cutaneous T cell lymphoma [29] . Internalization of rIL-2/DTx into cells expressing the high affinity IL-2 receptor leads to activation of the ADP-ribosyltransferase function of DTx in the endosome . Activated DTx is subsequently translocated into the cytosol where it inhibits protein synthesis and induces apoptosis [29] . rIL-2/DTx treatment leads to a significant reduction in peripheral blood CD4+CD25+Foxp3+ Treg populations in humans [30] . Furthermore , clinical treatment of patients with rIL-2/DTx has been reported to enhance immune responses [30] , [31] , [32] . Similarly , treatment of mice with rIL-2/DTx has been reported to decrease splenic , bone marrow and peripheral blood CD4+CD25+Foxp3+ Treg [33] . Such treatment has been shown to have benefit in experimental tumor models [34] and several experimental models of immune-mediated disease [35] , [36] , [37] , [38] , [39] . Given these data , we hypothesized that rIL-2/DTx treatment would enhance the resolution of experimental L . major infection . Treatment with rIL-2/DTx reduced Treg/CD4+ T cell ratios during experimental L . major infection , increasing antigen-specific IFN-γ production , enhancing lesion resolution and decreasing parasite burden . Furthermore , combined administration of rIL-2/DTx and sodium stibogluconate had additive biological and therapeutic effects , in both genetically resistant ( C57BL/6 ) and susceptible ( BALB/c ) mice . Female C57BL/6 and BALB/c mice were purchased from Jackson Laboratories . All animals were housed in a specific pathogen-free animal facility , in high-efficiency particulate-filtered laminar flow hoods with free access to food and water , at Cincinnati Children's Hospital Medical Center ( CCHMC ) . Animal care was provided in accordance with the procedures outlined in the Guide for the Care and Use of Laboratory Animals under animal study proposals approved by the CCHMC IACUC . L . major clone V1 ( MHOM/IL/80/Friedlin ) promastigotes were grown at 28°C in medium 199 ( Cellgro ) , supplemented with 20% fetal calf serum ( FCS ) [Hyclone] , 100 U/ml penicillin and 100 µg/ml streptomycin ( Cellgro ) , 25 mM HEPES ( Invitrogen ) , 2 mM L-glutamine , 0 . 1 mM adenine , 5 µg/ml hemin , and 2 µg/ml d-biotin ( all from Sigma ) , and passaged at least 3 times , but not more than 5 times , prior to infection . Ficoll gradient purification [40] was used to purify infectious phase metacyclic promastigotes from 5 d old stationary cultures . 8 week-old mice were infected in the dermis of the ear with 3×103 L . major metacyclic promastigotes in 10 µl FBS-free media . Lesion size was quantified with vernier calipers . All reagents used for in vivo infection were endotoxin-free to the limits of detection of the Limulus amebocyte lysate assay ( Bio-Whittaker ) . Mice were treated intraperitoneally with rIL-2/DTx ( Denileukin diftitox , ONTAK; Ligand Pharmaceuticals , Inc . ) , intramuscularly with sodium stibogluconate ( SSG; The Wellcome Foundation , Inc . , provided by the Centers for Disease Control and Prevention ) , and/or an equal volume of sterile , endotoxin-free saline ( Hospira Inc . ) via these same routes as a control . To quantify lesional parasite burden , the ventral and dorsal sheets of the infected ears were separated , deposited dermal side down into 24-well tissue culture plates containing RPMI ( Cellgro ) supplemented with 100 U/ml penicillin , 100 µg/ml streptomycin and 50 µg/ml liberase CI enzyme blend ( Roche ) , and incubated for 45 min at 37°C . Tissues were subsequently dissociated in RPMI containing 10% FCS and 0 . 05% DNAse I ( Sigma ) using a medimachine ( BD Biosciences ) , according to the manufacturer's protocol . Tissue homogenates were filtered using a 50 µm cell strainer ( Falcon Products Inc ) and serially diluted ( 1∶2 ) in 96-well flat bottom microtiter tissue culture plates containing 50 µl of Novy-MacNeal-Nicolle ( NNN ) medium with 20% defibrinated rabbit blood ( Hemostat Laboratories ) overlaid with 100 µl medium 199 supplemented with 20% FCS , 100 U/ml penicillin , 100 µg/ml streptomycin , 2 mM L-glutamine , 25 mM HEPES , 0 . 1 mM adenine , 5 µg/ml hemin , and 2 µg/ml d-biotin . After culture for 7 d at 28°C the number of viable parasites was quantified by limiting dilution analysis . The parasite burden in draining , retromaxillar lymph nodes , liver ( left lobe ) and spleen was quantified by limiting dilution analysis using similar procedures . All reagents used for cell culture and parasite titration were endotoxin-free to the limits of detection of the Limulus amebocyte lysate assay ( Bio-Whittaker ) . Single cell suspensions generated from lesional sites or draining lymph nodes , obtained as described above , were treated with FACS fix buffer for 15 min ( BD Biosciences ) . Cells were washed and co-incubated with anti-FcγIII/II ( CD16/32; e-Bioscience ) antibody for 30 min in PBS containing 0 . 1% BSA and 0 . 01% sodium azide . After a further wash , cells were incubated with directly-conjugated monoclonal antibodies to TCR-β-FITC ( H57-597 ) , CD4-PE-Cy7 ( RM4-5 ) or CD4-APC-Alexa Fluorochrome 750 ( RM4-5 ) , CD8-Pacific Blue ( 53-6 . 7 ) , CD25-PE ( PC61 ) , NK1 . 1-PerCp-Cy5 . 5 ( PK136 ) , CD49b-PE-Cy7 ( DX5 ) , F4/80-APC ( BM8 ) , CD11b-PerCp-Cy5 . 5 ( M1/70 ) , Gr-1-FITC ( RB6-8C5 ) , CD11c-Alexa Fluorochrome 700 ( N418 ) , B220-APC-Alexa Fluorochrome 750 ( RA3-6B2 ) , and/or CD19-PE ( 1D3 ) [all antibodies were from BD Biosciences and/or e-Bioscience] for 30 min . Quantification of Foxp3 expression was done using the Foxp3-APC ( FJK-16s ) staining kit ( e-Bioscience ) according to manufacturer's instructions , combined with directly-conjugated monoclonal antibodies TCR-β-FITC , CD4-APC-Alexa Fluorochrome 750 and CD25-PE ( BD Biosciences and/or e-Bioscience ) . Isotype control antibodies ( BD Biosciences and/or e-Bioscience ) were used in each analysis . Data were collected and analyzed using a combination of FACSCalibur flow cytometer and CellQuest software or LSRII flow cytometer and FACSDiva software ( BD Immunocytometry Systems ) . 96-well , EIA/RIA flat-bottom , plates ( Costar ) were coated with diphtheria toxin ( 1 µg/ml; Sigma ) in 50 mM carbonate/bicarbonate buffer pH 9 . 6 and incubated overnight at 4°C . Plates were washed ( 6× ) with wash buffer ( Tris-Buffer Saline pH 7 . 2 and 0 . 05% Tween 20 ) , serum samples , diluted in dilution buffer ( wash buffer supplemented with 10% SuperBlock [Pierce] ) , were added and incubated for 30 min at room temperature . Plates were washed , alkaline phosphatase-conjugated anti-mouse IgG1 antibody ( 1∶1000 in dilution buffer; BD Biosciences ) was added and plates were incubated for an additional 30 min at room temperature . After a further wash , pNPP ( 1 mg/ml; Calbiochem ) in TM Buffer ( Tris Base supplemented with 0 . 3 M MgCl2 , pH 9 . 8 ) was added and optical density ( 405 nm ) was quantified using kinetic microplate reader ( Molecular Devices ) . Draining lymph node cells were plated in 96-well tissue culture plates at 5×106 cells/ml and cultured for 96 h at 37°C in 5% CO2 in RPMI containing 100 U/ml penicillin , 100 µg/ml streptomycin , 10% fetal calf serum , 0 . 1 mM β-mercaptoethanol ( Invitrogen ) and soluble L . major antigens were generated as described [41] . Secreted IFN-γ , IL-10 and IL-4 were quantified by ELISA ( BD Biosciences ) . Kinetic lesion size data was first analyzed by MANOVA , to reject the null hypothesis of equal effects , followed by ANOVA ( plus Tukey's multiple comparison test ) or the unpaired Student's t test , as appropriate . In studies aimed at defining whether rIL-2/DTx treatment allowed for a reduction in the dose or duration of standard antimicrobial therapy , linear random effects ( time ) modeling was done to test the null hypothesis that all treatments had equal effects , as well as to sort the therapeutic efficacy of the diverse treatment regimens . Parasite numbers were log-transformed before analysis , and analyzed by ANOVA ( followed by Tukey's multiple comparison test ) or the unpaired Student's t test , or the non-parametric Kruskal-Wallis test ( followed by the Wilcoxon test ) , as appropriate . Given the robust expression of the high affinity IL-2 receptor by Foxp3-expressing Treg , it is not surprising that rIL-2/DTx treatment has been reported to deplete Treg in humans and mice [30] , [31] , [33] , [34] , [42] , [43] . To define the kinetics of rIL-2/DTx-mediated Treg depletion , we treated uninfected mice with a single injection of rIL-2/DTx ( or vehicle control ) and quantified splenic Treg numbers thereafter . As shown in Figure 1A , rIL-2/DTx injection led to a significant decrease in the percentage of splenic Treg quantified one week after treatment ( see Fig . S1 for flow cytometric gating strategy ) . However this reduction was not sustained; no alterations in Treg percentage were observed two or three weeks after administration of a single dose ( Figure 1A ) . A similar significant reduction in the percentage of splenic Treg was observed after four weekly doses of rIL-2/DTx ( Figure 1B ) . However , longer treatment ( 8 weekly doses ) failed to result in sustained Treg depletion ( Figure 1B ) . During the course of experimental cutaneous leishmaniasis , a dynamic process of Treg recruitment to and retention in lesional sites has been observed [41] . Short-term administration ( 3 weekly doses ) of rIL-2/DTx , 1 week after L . major infection , resulted in a significant reduction in lesional , draining lymph node and splenic Treg accumulation after 4 weeks of infection ( Figure 1C and data not shown ) . However , similar to findings in the spleens of uninfected mice , prolonged administration of rIL-2/DTx ( 7 weekly doses ) , 1 week after L . major infection , failed to result in sustained lesional Treg depletion; lesional Treg percentages were similar in treated and mock-treated mice 8 weeks after infection ( Figure 1C ) . It will be noted that , with lesional healing in these genetically resistant mice , lesional Treg numbers decrease in untreated mice over this time frame as well . As shown in Figure 1D , such prolonged administration of rIL-2/DTx led to the generation of robust titers of anti-DTx antibodies . To define the effectiveness of rIL-2/DTx administration on the resolution of an ongoing L . major infection , mice were treated with rIL-2/DTx , or vehicle as a control , beginning 30 d after infection . In light of the above kinetic data , the mice were given three doses of drug or vehicle , at 5 d intervals . As shown in Figure 2 , rIL-2/DTx treatment significantly enhanced lesion resolution ( Figure 2A ) and resulted in a significant decrease in lesional parasite burden ( Figure 2B ) . While not especially relevant to therapy of human disease , we also examined the effect of weekly therapy with rIL-2/DTx , beginning 1 week after infection , on experimental cutaneous leishmaniasis . This protocol also significantly enhanced lesion resolution compared to control therapy ( Figure 2C ) — something sustained from the onset of lesion resolution in rIL-2/DTx-treated mice through the rest of the 8-week time course of the experiment . However , while such therapy led to significantly decreased lesional parasite burden after 3 weekly doses of rIL-2/DTx ( Figure 2D ) , no significant enhancement ( or impairment ) of host control of parasite burden was observed after 7 weekly doses of rIL-2/DTx therapy , compared with mock therapy ( Figure 2D ) , something perhaps predictable both from the generation of antibodies to DTx observed with this protocol ( Figure 1D ) , as well as the baseline levels of host resistance observed in this model . We next examined the therapeutic effect of co-administration of rIL-2/DTx and pentavalent antimony ( sodium stibogluconate [SSG] ) on the resolution of L . major infection , again , beginning therapy 30 d after infection . Single agent therapy with either rIL-2/DTx or SSG led to significant improvement in lesion resolution and significant decreased parasite burden , compared to vehicle-treated animals ( Figure 3A and 3B ) . Further , combined therapy with rIL-2/DTx and SSG , regardless of the dose of rIL-2/DTx employed , resulted in significantly enhanced lesion resolution and decreased parasite burden compared to single agent therapy ( Figure 3A and 3B ) . As expected , rIL-2/DTx treatment led to a significant reduction in lesional Treg ( Figure 3C ) . The addition of SSG to rIL-2/DTx ( or vehicle ) treatment failed to alter lesional Treg ( data not shown ) . Based on this , we examined the effects of the addition of rIL-2/DTx to standard SSG therapy on a range of immune parameters important in controlling the course of experimental infection with L . major . Mice were treated with SSG , rIL-2/DTx and/or vehicle controls beginning 30 days after infection . In concert with significant effects on lesion size and lesional parasite burden ( Figure 4A and B ) , the addition of rIL-2/DTx to SSG led to a significant reduction in Treg in lesions and draining lymph nodes ( Figure 4C and D ) . Combined therapy with rIL-2/DTx and SSG also led to a significant increase in antigen-specific IFN-γ production by cells isolated from draining lymph nodes , compared with control or SSG treatment alone ( Figure 4E ) . No differences in antigen-specific IL-10 production were observed ( Figure 4F ) . We subsequently examined whether the addition of rIL-2/DTx allowed for a reduction in SSG dose or duration . Notably , as shown in Figure 5 , the added clinical benefit—reduction in lesion size and parasite burden—afforded by adjunct therapy with rIL-2/DTx allowed for at least a halving of the duration of SSG treatment needed: in terms of both lesion size and parasite burden , rIL-2/DTx+5d of SSG was more effective than the full 10d regimen of SSG alone . Such combination therapy with rIL-2/DTx also allowed for SSG dose sparing: rIL-2/DTx+SSG 25 mg/kg/d for 10d had equivalent effects on lesion size and parasite burden as SSG 250 mg/kg/d for 10d alone ( Fig . 5 ) . To define the effect of rIL-2/DTx therapy on leishmaniasis in the face of genetic susceptibility , we turned to BALB/c mice , mice that fail to heal L . major infection . Of interest , additive therapeutic and biological efficacy was seen even in this highly susceptible strain . Whereas short-term therapy with either SSG or rIL-2/DTx restrained lesion expansion , short-term combined therapy led to a significant reduction in lesion size ( Fig . 6A ) . Such combined therapy also led to: ( i ) a significant reduction in parasite burden in lesions , draining lymph nodes , and liver ( along with a trend towards a decrease in splenic parasite burden ) ( Fig . 6 B–E ) ; ( ii ) modest if significant suppression of Treg in draining lymph nodes and spleen ( Fig . 6 F and G ) ; and ( iii ) significant augmentation antigen-specific IFN-γ production ( in the absence of significant effects on IL-10 and IL-4 production ) by cells isolated from draining lymph nodes ( Fig . 6 H–J ) . Considerable data suggest likely benefit for immunomodulatory approaches to therapy in leishmaniasis , a neglected tropical infection that continues to cause a great burden of morbidity and mortality in the tropics . Our data confirm that rIL-2/DTx administration leads to transient depletion of TCRβ+CD4+CD25+Foxp3+ Treg , demonstrating that this depletion is limited by development of antibodies to DTx after multiple doses . Our data further suggest potential therapeutic promise for rIL-2/DTx in cutaneous leishmaniasis . rIL-2/DTx-mediated Treg suppression was associated with increased antigen-specific IFN-γ production , enhanced lesion resolution and decreased parasite burden during experimental L . major infection ( in the absence of any obvious qualitative differences in lesion histology [data not shown] ) . Combined administration of rIL-2/DTx and sodium stibogluconate had additive therapeutic effects , allowing for a shortening of the needed duration or dose of SSG therapy . It should be remarked that , whereas these data have potential therapeutic implications for human cutaneous leishmaniasis , the implications are less clear for visceral leishmaniasis . Treg have not been definitively been implicated as providing a key source of immune counter-regulation in either experimental or human visceral leishmaniasis , settings in which it is likely that IL-10 production by other T cells is more important [19] , [24] , [44] . The ability of rIL-2/DTx to deplete Treg has been somewhat controversial . Studies in humans and African green monkeys that quantified Treg by analyzing Foxp3 mRNA expression in peripheral blood CD4+ T cells or bulk peripheral blood mononuclear cells , or via enumeration of CD25-expressing CD4+ T cells within peripheral blood , suggested that rIL-2/DTx administration failed to significantly deplete Treg [37] , [45] , [46] . However , direct flow cytometric quantification of Foxp3-expressing CD4+ T cells has indicated that rIL-2/DTx treatment leads to Treg depletion in humans [30] , [31] , [43] , something that has been replicated in mouse models [33] , [34] . Our data provide insight into the kinetics of such treatment . A single dose of rIL-2/DTx leads to significant depletion of splenic Treg in mice , although such depletion is reversed as early as two weeks after rIL-2/DTx administration . Further , these data show that repetitive administration of rIL-2/DTx leads to sustained reduction of splenic Treg for up to four weeks of treatment in mice , something observed in humans as well [30] , [45] . However , long-term repetitive administration of rIL-2/DTx appears to be limited by the generation of antibodies to DTx . This indicates that the efficacy of rIL-2/DTx immunomodulation is likely to be temporally limited . This narrow temporal window , along with the partial depletion of Treg numbers achieved , may actually be beneficial in limiting potential deleterious over-activation of immune responses with sustained Treg depletion . Monoclonal antibody-mediated depletion of CD25-expressing cells has been reported to facilitate parasite eradication in experimental leishmaniasis [25] , [26] , [27] , [28] . Further , it should be noted that , prior to recognition of regulatory T cells , IL-2 was shown to be necessary for disease progression during experimental L . major infection of susceptible murine hosts [25] , [47] , [48] ( although the effects of IL-2 manipulation on the course of experimental infection with L . donovani appears to be more complicated , suggesting the need for caution in extrapolating these findings to visceral leishmaniasis [49] , [50] ) . While the effects of IL-2 on L . major infection have remained mechanistically undefined , one of the principal non-redundant functions of IL-2 appears to be regulation of Treg numbers [51] . Our finding that rIL-2/DTx-mediated blunting of Treg numbers is associated with increased immune-mediated clearance of L . major is thus not unexpected . It is acknowledged that the mechanism underlying the beneficial effects of rIL-2/DTx therapy in experimental leishmaniasis remains mechanistically under-defined . In particular , it may well be that rIL-2/DTx administration results , as well , either directly or indirectly , in biologically important changes in other cellular subsets that modulate anti-leishmanial immune responses . Of note in this regard , long-term depletion of CD25-expressing cells with declizumab has been shown to increase regulatory NK cell numbers , as well as decrease Treg numbers , in humans with multiple sclerosis— with regulatory NK cell changes correlating with disease suppression in this autoimmune disease [52] , [53] . Further , the fate of IL-10 producing Th1 cells [20] , [23] , [54] following rIL-2/DTx administration remains unclear . However , the lack of significant differences in antigen-driven IL-10 production following in vitro re-stimulation suggests that rIL-2/DTx administration may not directly alter the function or the numbers of such cells . There are many possible ways to therapeutically target Treg numbers and/or function , including direct targeting through CD25 , blockade of IL-10 , inhibition of CTLA-4 or TGF-β , engagement of GITR , and/or activation of dendritic cells ( e . g . , through LPS or CD40 ) [55] . The first two of these methods have already shown clear efficacy in mouse models of cutaneous leishmaniasis [14] , [17] . There are also , of course , theoretical reasons for caution: therapeutic targeting of Treg has the potential for promoting the development or expression of autoimmune disease in susceptible hosts , and for upregulating potentially deleterious immune responses to the infecting pathogen or to co-infecting pathogens . Although there are similar concerns with other immunological approaches , these considerations suggest that , for safety , Treg targeting should be as narrow as possible . Thus , if IL-10 blockade and CD25+ T cell targeting are both efficacious , the latter would be preferable as IL-10 is produced by many cells other than Treg . Similarly , while sustained targeting of Treg alone eradicates L . major in mouse models , brief targeting of Treg , along with antimicrobial therapy would likely be preferable . There may also be benefit to Treg targeting in concert with therapeutic vaccination . It should also be noted that the use of biologicals to inhibit immunological pathways ( e . g . , cytokine inhibition ) has , in general , been easier and fraught with fewer side effects than the use of biologicals to activate immunological pathways ( e . g . , cytokine therapy ) . Thus , inhibition of inhibitory pathways ( e . g . , targeting of CD25+ ) cells may be preferable to direct immune stimulation ( e . g . , of dendritic cells ) . Together , these considerations suggest practical therapeutic utility for direct targeting of CD25+ cells in leishmaniasis and other chronic infections in which Treg play an important biological role in hindering host-mediated immune clearance . More broadly , the current data suggest that rational reinvestigation of the efficacy of drugs approved for other indications in experimental models of neglected tropical diseases has promise in providing needed new candidates to the drug discovery pipeline .
Leishmaniasis is an infectious disease that causes a large burden of morbidity and mortality in the tropics . Caused by protozoan parasites of the genus Leishmania that are transmitted by sandflies , leishmaniasis causes a wide spectrum of human disease . The severe end of the spectrum , visceral leishmaniasis , causes an annual mortality of approximately 50 , 000 , largely in India and Sudan . Available therapies for leishmaniasis are problematic due to emerging drug resistance , toxicity and/or the need for lengthy courses of treatment . There is thus an urgent need for novel therapeutic approaches to this neglected tropical disease . To address this problem , the authors examined whether a commercially available drug developed for cancer therapy ( Ontak ) , reported to have immunological activity of relevance to the immunobiology of Leishmania infection , exhibited efficacy in mouse models of leishmaniasis . The study found therapeutic efficacy for the drug alone in these models , as well as additive therapeutic efficacy in combination with standard antimicrobial therapy . Rational reinvestigation of the efficacy of already approved drugs in experimental models of neglected tropical diseases has promise in providing needed new candidates to the drug discovery pipeline .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "medicine", "immunology", "microbiology", "host-pathogen", "interaction", "parasitic", "diseases", "parastic", "protozoans", "leishmania", "global", "health", "neglected", "tropical", "diseases", "immunoregulation", "immunomodulation", "immunotherapy", "infectious", "diseases", "biology", "immune", "response", "immunity", "leishmaniasis", "protozoology" ]
2011
Therapeutic Enhancement of Protective Immunity during Experimental Leishmaniasis
ARID is a DNA-binding domain involved in several transcriptional regulatory processes , including cell-cycle regulation and embryonic development . ARID domains are also targets of the Human Cancer Protein Interaction Network . Little is known about the molecular mechanisms related to conformational changes in the family of ARID domains . Thus , we have examined their structural dynamics to enrich the knowledge on this important family of regulatory proteins . In particular , we used an approach that integrates atomistic simulations and methods inspired by graph theory . To relate these properties to protein function we studied both the free and DNA-bound forms . The interaction with DNA not only stabilizes the conformations of the DNA-binding loops , but also strengthens pre-existing paths in the native ARID ensemble for long-range communication to those loops . Residues in helix 5 are identified as critical mediators for intramolecular communication to the DNA-binding regions . In particular , we identified a distal tyrosine that plays a key role in long-range communication to the DNA-binding loops and that is experimentally known to impair DNA-binding . Mutations at this tyrosine and in other residues of helix 5 are also demonstrated , by our approach , to affect the paths of communication to the DNA-binding loops and alter their native dynamics . Overall , our results are in agreement with a scenario in which ARID domains exist as an ensemble of substates , which are shifted by external perturbation , such as the interaction with DNA . Conformational changes at the DNA-binding loops are transmitted long-range by intramolecular paths , which have their heart in helix 5 . ARID3A is a member of the ARID ( AT-rich interactive domain ) family of transcription factors and is also known as “dead ringer-like protein 1” ( Dril1 ) , “B-cell regulator of IgH transcription” ( Bright ) and “E2F-binding protein 1” ( E2FBP1 ) . The ARID family is a family of DNA-binding proteins with a wide range of cellular functions and participates in different regulatory processes , including embryonic development , gene expression during cell growth , differentiation and development as well as cell cycle control and chromatin remodeling [1]–[4] . Human ARID3A is also one of the targets of the broad Human Cancer Protein Interaction Network ( HCPIN ) database , which aims to provide structure-function annotations of key proteins related to cancer diseases and developmental biology [5] . ARID domains have been identified in the genomes of higher eukaryotes and feature a common all-α structural domain of about 100 residues or longer [1] . ARID proteins bind to the major groove in the DNA using a modified helix-turn-helix motif [1] , [2] . Human ARID3A belongs , together with ARID3B and 3C , to the third mammalian ARID subfamily , which is generally characterized by a core ARID domain with both additional N- and C-terminal extensions [1] , [2] . ARID3A , B and C are the closest paralogs ( more than 75% of sequence identity ) of the Drosophila “dead ringer” protein Dri [1] . The structures of the free ARID3A [6] and of both the free and DNA-bound Drosophila paralog [7] , [8] were recently solved by NMR spectroscopy and X-ray crystallography . Indeed , despite their biological importance ARID domains are still relatively poorly characterized from the structural and dynamical point of view . Considering their importance for DNA interaction and the involvement in a large range of biological functions , ARID domains are suitable targets for Molecular Dynamics ( MD ) investigations with attention to both dynamic fingerprints and structural communication mechanisms . In addition to providing basic information on the dynamics of ARID proteins such analyses may shed light on the structural effects induced by mutations . Here , we have studied intramolecular communication in two members of the ARID family , both in the free and DNA-bound states , with particular attention to the effects induced by distal residues on the DNA-binding loops . We used an approach that integrates atomistic , explicit solvent simulations , prediction of the effects induced by mutations on protein stability and methods inspired by graph theory . In particular , we found that the interaction with the DNA strengthens pre-existing paths from distal sites in helix α5 to the DNA-binding loops . In addition to the residues directly involved in the DNA binding , a distal tyrosine ( Y119 ) was identified . This residue affects DNA-binding as attested by experimental mutagenesis and a Electrophoretic Mobility Shift Assay ( EMSA ) [9] . We here show that Y119 plays a key role in promoting long-range communication to the loops at the interface with DNA . Other residues , mostly in helix α5 , are also identified with a key role in intramolecular communication and we show that their mutations can impair the native paths to the DNA-binding regions . The surroundings of Y119 are also predicted as hotspots for protein-protein interaction , suggesting that paths identified in our study may also be an important element to propagate effects long-range from the DNA-binding site to a region for the recruitment of other biological partners , or vice versa . A short description of the target proteins is reported in the following ( Figure 1 ) . The ARID domain of ARID3A and Dri consists of eight α-helices ( α0–α7 ) and a very short β-harpin . We here refer to the numbering of ARID3A NMR structure ( 2KK0 ) in the Protein Data Bank ( PDB ) for sake of clarity . A sequence alignment is also provided with the corresponding numbering in ARID3A and Dri , ( Figure S1 ) . Loop L2 and the β-harpin Loop L1 of Dri interact with the DNA major groove and regions outside the major groove , respectively [1] , [7] . These residues are also conserved in ARID3A , suggesting a common binding mode to the DNA [6] . The results are also in agreement with the recent experimental finding that L1 of human JARID1B ARID domain is crucial for DNA binding [10] . Therefore , we here used the X-ray structure of Dri bound to DNA as a reference for the DNA-bound ARID domains . The MD simulations collected in this study are summarized in Table 1 . At first , we carried out ten independent simulations for ARID3AFREE and DRIFREE of 100 ns each to assess the reproducibility of the results . One of the DRIFREE simulations was also extended up to one microsecond ( DriFREE-1 µs ) . The Dri DNA-bound conformation ( PDB entry 1KQQ ) was employed as starting structure for four 100-ns MD replicates of Dri in complex with DNA ( DriDNA ) . All the simulations have been performed with CHARMM22* , a new generation force field , which was validated against NMR data [11] . To verify that our simulations do not encounter issues related to force-field deterioration or low stability of the sampled structures , chemical shift predictions of backbone and Cβ atoms were calculated by PPM [12] and compared to the experimental values ( Table 2 , Figure S2 ) . Indeed , we need to sample conformations that do not deviate from the experimental data to avoid artifact arising from the analyses of the MD ensemble . The average root mean square deviation ( rmsd ) between experimental and predicted chemical shifts was then calculated for the MD ensemble [12] and compared to the results obtained for the starting experimental structures ( Table 2 ) . The data obtained for all the five chemical shift classes show that the rmsd values are within or near the expected deviations recorded for the protein test sets and substantially lower than the rmsd values calculated on the starting structures ( PDB entries 2KK0 and 1C20 ) . Moreover , the time-evolution of the backbone and Cβ chemical shifts was evaluated for DriFREE-1 µs ( Figure S2 ) . The one-µs trajectory has rmsd values comparable to the single 100-ns replicates ( Table 2 ) . Further , the evolution of the chemical shift rmsd over the simulation time ( Figure S2 ) reveals a stabilization or improvement of those values after the first 100 ns of simulation . Overall , these results indicate that the trajectories analyzed are stable and with rmsd values substantially lower than those calculated from the PDB starting structure ( green lines in Figure S2 ) when at least 100 ns of MD ensemble are collected . Moreover , a ten-fold increase of the simulation time does not lead to a concrete improvement of the rmsd values suggesting that 100 ns is an adequate timeframe for our analysis . We can thus post-process the MD ensembles by methods inspired by graph theory to derive paths of communications , other important properties of the network ( as for example hub residues ) and to investigate how ( and if ) those paths are affected by the interaction with DNA and by mutations . The availability of one µs simulation for DriFREE also allowed us to assess the influence , on the PSN description , of simulating the system over a longer timescale . We here employed a method inspired by graph-theory , the so-called Protein Structure Network ( PSN ) -MD approach [13]–[15] to detect the paths of communication in the MD ensembles of ARID3A and Dri . This method is based on the observation that structural effects can be transmitted at distal sites through communication paths involving side-chain contacts between residues that feature correlated motions [13]–[15] . The PSN calculation is thus integrated to metrics that estimate coupled motions from the MD ensemble . We here employed Linear Mutual Information ( LMI ) [16] as a metrics of correlated motions . To assess the consistency of the results , we compared LMI matrices from each independent replicate . In particular , LMI matrices were calculated as average matrices over time-windows of five ns ( Figure S3 ) . The correlated motions are similarly and consistently described . The maximum differences observed for the LMI matrices are always below 0 . 35 and are generally restricted to the N- and C-terminal residues . To better quantify the differences among LMI matrices of the same system , we also calculated the Frobenius norm between them ( Figure 2 ) . If the description of the correlated motions is similar in all the replicates , we expect low values of Frobenius norm when they are compared pairwise . The wild-type LMI matrices of ARID3AFREE and DriFREE simulations were also compared to the LMI matrices calculated from 100-ns unfolding simulations at 500 K of the same proteins . Indeed , if the different LMI matrices of the wild-type protein are really consistent in describing the correlated motions of the protein , the Frobenius norm obtained from their pairwise comparison should be at least lower than the ones achieved when each of the wild-type LMI matrices is compared to the LMI matrix from the unfolding simulation , in which the native structure is not preserved . All the replicates of the same system feature lower Frobenius norm values when compared each other than when compared to the corresponding unfolding simulation ( illustrated in Figure 2 for DriFREE ) and they are always within the range of values of the LMI Frobenius norm calculated between the two halves of the same target trajectory ( average value of 6 . 80 , bottom insert in Figure 2 ) . Indeed , as expected , the LMI matrix from the unfolding simulation largely deviates from the LMI of the folded proteins ( average Frobenius norm of 22 . 13 ) . In summary , LMI matrices calculated from the different replicates of the same system and averaged over different time-windows consistently describe the same pattern of correlated motions and can thus be used , coupled to network analysis , to disclose paths of long-range communication in the MD ensembles . We then calculated the PSN from each MD replicate . In this network the residues are the nodes of the graph and are connected by edges weighted according to a defined Interaction strength ( I ) value [17] . In the PSNs , the calculated edges are retained only if their I is greater than a defined cut-off value ( minimum Interaction Strength , Imin ) . Generally , a PSN at the so-called Icrit value is calculated for further analysis , where the Icrit is the Imin corresponding to the main transition in the size of the largest cluster ( cluster 1 ) of the network [17] . Both to define the Icrit value for the analysis and to verify the congruency of the results from our simulations , we calculated the evolution of the size of cluster 1 as a function of different Imin values . We thus calculated several PSNs for each replicate , varying the Imin value from 0 to 40 by steps of 0 . 2 ( Figure 3 ) . Independently of the system ( ARID3A or Dri ) , presence of mutations , DNA and differences in the timescales , all the MD ensembles feature similar profiles with a first very sharp transition in a narrow range of Imin values . It was previously observed that in PSNs of experimental protein structures collected from the PDB , this transition occurs in the same range of Imin for proteins of different size and fold [17] . Our simulations confirm this finding also for protein structures simulated within a classical force-field description , even if the Icrit ( ∼7 in our study ) is shifted to slightly larger values than what observed in the previous study on single PDB structures [17] . We can thus employ a common Icrit value for all the systems and we here shown the robustness of PSN Icrit even in MD ensembles of not identical proteins . Hubs of a PSN are highly connected residues in the network , i . e . nodes connected by more than three edges . They can play a role in protein structural stability , function or allow a proper flux of information to distal sites [17]–[20] . We calculated the PSN hubs for free and DNA-bound ARID domains ( Figure 4 and S4 ) . In particular , we calculated the node degree ( i . e . the number of edges in which the hub is involved ) of each hub for each simulation . Overall , both the hub localization on the structure and their connectivity degree in the network are very similar for the different replicates of the same system even if the PSN is calculated on a longer timescale ( i . e . one µs ) . Interaction with DNA promotes higher connections not only in the DNA-binding loops , but also for the nodes that are not in direct contact with the DNA ( Figure 4 and S4 ) . In particular , the connectivity degree of each hub and the hub number itself increase in the central helix α5 of the ARID domain upon DNA interaction . These are sites that may play a role in long-range communication to distal sites , as detailed in the next Sections . Hubs in ARID3AFREE and DriFREE are generally placed at identical positions and most of them are also strictly conserved in terms of primary sequence , enforcing the notion of common dynamic patterns in these two proteins . Y119 is conserved as a hub residue in most of ARID3AFREE and Dri simulations independently of the presence or absence of DNA , but DNA interaction increases its connectivity degree ( Figure 4 , S4 ) . The Y119 in ARID3A ( Y109 in Dri ) is known to affect DNA binding capability when mutated to alanine [9] even if according to the 3D structure Y119 is not in direct contact with the DNA molecule . It is indeed placed at the C-terminal region of α5 more than 20 Å of distance from the DNA binding site ( Figure S5 ) . In the same study , the authors identified , by alanine scanning mutagenesis , three other residues that are crucial for DNA binding: P57 , W88 and F106 ( Figure S5 , P47 , W78 and F96 in Dri ) . F106/F96 has a minor interest for our work since it is in direct contact with the DNA and is not conserved in all the ARID family members , as attested by a low conservation score of this position in a multiple sequence alignment of 100 sequences homologous to ARID3A by CCRXP server [21] . Both P57/P47 and W88/W78 hub-properties are also modulated by the DNA interaction , as observed for Y119 ( Figure 4 , S4 ) . Another interesting hub of α5 is Q111/Q101 . It is placed in a position suitable as “mediator” for communication paths and it is a hub residue with higher connectivity upon DNA interaction ( Figure S4 ) . We then evaluated by using Fold-X [22] the effects that the experimentally investigated mutations [9] , as well as R109A and Q111A or Q111N mutations ( see below ) , may have on the structural stability . All these mutations ( Y119A , F106A , R109A , Q111A and Q111N ) have only modest effects on protein stability ( average ΔΔG values between −0 . 2 and 0 . 6 kcal/mol ) with the exception of W88A and P57A mutations that have more destabilizing effects ( average ΔΔG values of 4 . 4 and 2 . 5 kcal/mol , respectively ) . These two residues ( P57 and W88 ) are also conserved in the multiple sequence alignment of ARID homologs carried out by the CCRXP server [21] , with conservation scores of 0 . 889 and 0 . 850 , respectively . In our MD simulations , most of the experimental mutation sites ( P57 , Y119 and W88 ) [9] act as hubs with or without the DNA and their connectivity within the graph is modulated by the DNA . This observation alone might suggest a central role exerted by these residues that are not in direct contact with the DNA in mediating long-range communication to the DNA-binding interface . Nevertheless , in the case of P57 and W88 , the alanine mutations by Fold-X are predicted to remarkably affect protein stability of the ARID domains . In this scenario we can conclude that the effects observed in the experiments upon P57A and W88A mutations are more likely to be related to a destabilization of the protein fold rather than due to distal communication to the L1 and L2 DNA-binding loops . P57 is indeed a residue with a structural role devoted to maintain the local conformation of the L1 β-hairpin and the correct position of K61 for DNA interaction [7] . Y119 instead appears as an important mediator for distal communication and its mutation should not compromise structural stability of the ARID domains . To better investigate the long-range communication from distal sites of ARID domains to the DNA-binding loops L1 and L2 , we then employed a PSN/LMI approach [15] , [23]–[24] . In particular , we calculated the shortest paths of long-range communication from each protein residue to the DNA-binding loops L1 and L2 . Indeed , the shortest paths of communication are likely to be the paths that more efficiently transmit a “signal” over long distances within the protein structure [20] . The paths were then ranked according to their probability of occurrence and length . The shortest paths with highest occurrence probability that connected two end-residues by a series of non-covalent interactions with highly correlated motions were selected . Particular attention was devoted to the pairs of residues connected by a path with a probability of occurrence higher than 15% to discard paths that are too poorly populated in the conformational ensemble and may thus increase the noise of the analysis . Moreover , to focus our attention on long-range communication , only the paths of length greater than three were analyzed in details . Comparing the DriFREE and DriDNA simulations ( dark green vs . gray histograms in Figure 5 , upper panel ) , we noticed that long-range paths ( from 7 to 10 residues in length ) are increased by the DNA interaction , whereas the shorter-range paths ( 4–5 residues ) are decreased . The presence of DNA not only promotes longer paths of communications to L1 and L2 ( Figure 5 , lower panel ) . Indeed , if we used the same PSN/LMI approach to calculate the shortest paths from each residue to other protein sites , with the exception of the DNA binding loops , we observed a 28% decrease of long-range paths directed to sites different from the DNA-binding region . The two results together suggest that DNA promotes a well-channeled long-range communication from specific distal sites to the L1 and L2 binding loops and weakens other communication routes of the unbound protein . The long-range paths of length higher than 8 were compared in DriDNA and DriFREE simulations and the differences between them mapped on the 3D structure ( Figure 5 upper panel ) . We noticed that the presence of DNA promotes a larger number of long-range paths to L2 and L1 . Among those paths , Y119 ( Y109 in Dri ) plays a crucial role being involved in one of the major route of communication to the DNA-binding loops , along with L116 ( L106 in Dri ) . In fact , they belong to the paths from K113 to both L56 at the base of L1 and L87-I91-P88 in L2 ( Figure 5 , lower panel ) . In DriFREE , some of the paths of length higher than 8 and that link the C-terminal helix or its surroundings to other protein regions distal to the DNA-binding sites are instead lost in DriDNA simulations ( blue lines in Figure 5 , lower panel ) . These data further enforce the notion that the presence of DNA promotes a more channeled communication toward the DNA-binding sites . For each system , all the paths to L1 and L2 identified above were joined in one single graph . Then , the nodes belonging to this graph were connected by edges whose thickness is proportional to the probability to find in the graph the same connection in different communication paths , providing the final graphs reported in Figure 6 for ARID3A and Dri . The analysis provides an overview of the residues and the connections that are more represented in the paths from distal sites of ARID domains to the DNA-binding loops . We found that the residues that were experimentally investigated [9] and for which alanine mutations have a direct or indirect effects on DNA-binding capabilities ( i . e . Y119 , P57 and W88 ) are highly represented in the paths of communication , as well as R109 and Q111 . There are also other residues interested by highly abundant edges as M59 , L66 , L108 and L116 in suitable positions to be mediator of the communication . Most of these residues are located in helix α5 . M59A , L66A , L108A and L116A mutations are also predicted as destabilizing the 3D structure ( ΔΔG values in the range of 3 . 24–4 . 17 kcal/mol ) by Fold-X , as the W88A mutation discussed above . Thus , they are likely to be not only important residues for long-range communication but also in maintaining the correct 3D architecture . In summary , Y119 and Q111 are suggested as important hubs for structural communication within the ARID domains . They can be modulated by DNA-interaction and are also among the most represented nodes in the long-range paths from protein distal sites to the DNA-binding loops , and alanine mutations of these residues are also predicted not to affect the protein stability . They are thus suitable candidate to verify their role as important mediators of communication to the DNA-binding loops . Experimental mutagenesis pointed out that Y119A mutation can affect DNA-binding capability of ARID3A [9] . Y119 is not in direct contact with the DNA molecule since it is more than 20 Å far from the DNA-binding interface and partially solvent exposed ( average solvent accessibility of the side chain in the simulations higher than 15% ) . It has therefore to exert its effect long-range . It thus represents a good candidate to further investigate the communication to the DNA-binding loops , as well as to probe if the paths identified by the PSN/LMI approaches can modulate long-range the conformation and dynamics of the DNA-binding loops . In particular , we compared the wild type MD simulations of ARID3A and Dri with simulations of Y119A/Y109A mutants ( ARID3AY119A , DriFREE-Y109A and DriDNA-Y109A ) with the same approaches described in the previous Sections . We also include mutations in Q111/Q101 , which can also be a mediator of long-range communication to the DNA interface and for which mutations to Asn or Ala are predicted to have neutral effects on protein stability by FoldX . In particular , we included Q111N mutation as a control in our simulations since it is a conservative mutation that we did not expect to affect the overall dynamics . Moreover , since the only relevant difference between Asn and Gln residues is the side-chain length , we can also use this mutant to verify if even subtle changes in the side chains of crucial nodes for structural communication can affect the communication paths . We thus compare wild-type ARID domain dynamics to the different mutant variants by Full Correlation Analysis ( FCA ) analysis of L1 and L2 loops in a common reference subspace . FCA analysis of the L1 and L2 loops only shows that those mutations affect the dynamic properties of the DNA-binding loops when compared to the wt ( Figure 7 upper panels ) . In particular , Y119A has the most prominent effects on the native dynamics of both the DNA-binding loops , whereas Q111A and Q111N have a major effect mainly on L1 and more native-like patterns for L2 . It can be argued that the effects induced upon these mutations are less detrimental if DNA is present . Therefore , to further verify that the effects induced by those mutations can be identified also in DNA-bound form , we carried out also MD simulations of DriDNA mutant variants at the position corresponding to the ARID3A mutation sites ( i . e . Q101A , Q101N and Y109A ) . The FCA analysis of L1 and L2 was carried out also for wild-type DriDNA and its mutant variant confirming the picture described above for Y119A mutant ( Figure 7 bottom panels ) . On the contrary , mutations at the 101 site in Dri ( Q111 in ARID3A ) feature less detrimental effects on the native dynamics in presence of the DNA . This result suggests that the DNA can partially rescue the structural effects induced by Q111 mutations . To investigate the role of those residues in the communication routes to the DNA-binding loops , all the shortest paths with occurrence probability higher than 15% identified by PSN-LMI , which starts by Y119 ( Figure 8 left panel ) or Q111 ( Figure 9 left panel ) and are directed toward other residues are considered with respect to their location on the 3D structure of ARID3AFREE and compared to the ones identified for the same residues in the mutants Y119A ( Figure 8 right panel ) , Q111N ( Figure 9 middle panel ) and Q111A ( Figure 9 right panel ) . In the wt dynamics , it turns out that part of the paths from Y119 and Q111 are directed toward L1 and L2 and other regions close to the interface for DNA interaction , including the highly interconnected intermediate node L64 ( showed as a yellow sphere in Figures 8 and 9 ) . Alanine mutations at both 119 and 111 sites dramatically affect the communication in ARID3A . Indeed , the mutations perturb the long-range paths , especially the ones of length greater than 7 . They either decrease the probability of occurrence of the paths or they weaken the communication so that the paths are preserved but shorter in length and they cannot successfully reach the DNA-binding loops . Moreover , there are cases in which the mutations cause a major perturbation in the native paths , re-directing the communication toward other regions of the protein ( Figure 8 and 9 ) and in particular affecting L1 . The Q111N mutation is more similar to the wild type ( Figure 9 middle panel ) . Nevertheless , even the subtle replacement of the Gln with a shorter side-chain residue ( as Asn ) decreases the probability of occurrence of some of the paths directed to the DNA-binding loops . The mutation indeed causes a weakening of the communication to L1 . Methods inspired to graph theory are widely used to study protein structure-function relationships [13]–[15] , [17]–[19] , [24]–[25] and they have also been applied to the study of complex biological phenomena such as long-range intra- and intermolecular communication [13]–[15] , [17]–[19] , [24]–[32] . Here , we integrated graph theory and MD simulations to describe the structural dynamics and intramolecular communication in the ARID family of DNA-binding domains , which have been so far poorly structurally characterized . Our simulated ensembles were also first evaluated for consistency with the available experimental information from NMR . The crucial cutoffs for PSN analyses have been evaluated comparing different replicates for each system , along with simulations of different lengths . We have then examined how dynamical properties of ARID domains are influenced by the interaction with DNA or by mutations at critical sites in the communication paths to the DNA-binding loops . We are aware that our approach is mainly protein-centered , even if simulations are carried out in explicit solvent and thus the dynamics we are describing and the related paths are ultimately influenced by the solvent dynamics too . A network description of the clusters of water molecules around the protein surface or in protein cavities , as recently investigated by other techniques [33]–[36] may complement the PSN information and it can be consider for future applications . The PSN/MD approaches here employed provide also a global description of the dynamical communication within the ARID domain , which might be difficult to obtain by other means . More generally , we thus hope that these approaches can be an useful starting point in cases where little experimental information is available to guide further experimental characterization . The definition of the nodes and their edges that more frequently populate the paths of long-range communication in the PSN/LMI approach can also be a complementary tool for the identification of important residues in the dynamic networks , i . e . they for example complement the information from hub detection in PSN . This technique can be employed to identify hot-spot residues for protein function and stability , as we here showed integrating them with Fold-X calculations of mutations in the hubs . Indeed , the edges with high occurrence probability in the communication paths have the potential to act as fundamental signal transmitters to allow the information flow throughout the protein structure . On the biological side , our results show that structural communication in ARID domains can pass through a subset of conserved hubs , among which Y119 and W88 are found . Y119 and W88 were also experimentally investigated in ARID3A and are known to affect the protein function and interaction with DNA [9] . Other relevant residues to provide the native communication flow are suggested to be Q111 , L116 , L108 , L66 and M59 . We also evaluated in our MD framework Y119A , Q111A and Q111N mutations that turned out to affect the communication routes of the native protein to the DNA-binding loops at different extent . Most of those residues are located in the helix α5 that we thus found to be a central region for the long-range communication to the DNA binding loops . In our MD ensembles , pre-existing communication paths in the DNA-unbound states are directed toward L1 and L2 at the DNA-binding interface in the free proteins and they are strengthened by the interaction with DNA . Y119 , Q111 and the other residues mentioned above turned out to be critical nodes for the long-range communication to the DNA-binding loop . Interestingly , the region including Y119 and its surrounding ( F38 , F67 , M68 , Y70 , V71 , L72 and T74 ) is predicted as a hotspot for protein-protein interaction by InterProtSurf [37] . Our results can thus boost future research in the field of ARID domains to characterize protein-protein interaction mapping at this region and modulated by DNA-binding . It appears that the ARID domains may exist as an ensemble of substates in solution , which can be shifted by external perturbation , such as the interaction with DNA in our study . L1 and L2 DNA-binding loops play an important role in determining the conformational changes between the different ARID substates and their dynamical properties are directly influenced by DNA interaction , but the effect can also be transmitted long-range by intramolecular paths , which have their heart in the helix α5 . The known NMR structures of human ARID3A ( ARID3AFREE , PDB entry 2KK0 , [6] ) and Drosophila melanogaster Dri ( DriFREE PDB entry 1C20 , [8] ) domains free in solution were used as starting structures for MD simulations ( Table 1 ) . In particular , from the PDB entry 2KK0 only the atomic coordinates referred to the ARID3A protein were considered , excluding the N-terminal His-tag construct and the residues belonging to the disordered N-terminal tail . Several 100-ns independent simulations of ARID3AFREE ( four replicates ) and DriFREE ( six replicates ) were carried out using as initial structure the first conformer observed by NMR spectroscopy . One of the DriFREE simulations was extended to 1 µs . Simulations ( four replicates ) were also carried out for Dri in complex with the DNA ( DriDNA ) , starting from the first NMR conformer in the PDB entry 1KQQ [7] ) ( Table 1 ) . The availability of independent simulations of the two homologous proteins and over different timescales allowed a better assessment of the reproducibility of the results and the robustness of the PSN-MD approach . Two replicates for each mutant ( Y119A , Q111A and Q111N ) ARID3A and Dri variants , with and without DNA , were also carried out upon in-silico mutagenesis with Pymol ( www . pymol . org ) . Unfolding simulations at 500 K of 100 ns were also performed for both DriFREE and ARID3AFREE to employ as a control in the evaluation of the correlated motions . Explicit solvent MD simulations were performed using the 4 . 5 . 3 version of the GROMACS software [38] with the CHARMM22* force field [11] . The initial structures were embedded in a dodecahedral box of TIP3P water molecules [39] . Periodic boundary conditions were employed . All the protein atoms were at a distance equal or greater than 1 . 0 nm from the box edges . To neutralize the overall charge of the system , a number of water molecules equal to the protein net charge were replaced by counter-ions . Each system was initially relaxed by 10000 steps of energy minimization by the steepest descent method . The optimization step was followed by 50 ps of solvent equilibration at 300K , while restraining the protein atomic positions using a harmonic potential . Each system was then slowly equilibrated to the target temperature ( 300 K ) and pressure ( 1 bar ) through thermalization and a series of pressurization simulations of 100 ps each . Productive MD simulations were performed in the isothermal-isobaric ( NPT ) ensemble at 300K and 1 bar , using an external Berendsen bath with thermal and pressure coupling of 0 . 1 and 1 ps respectively . The LINCS algorithm [40] was used to constrain heavy-atom bonds , allowing for a 2 fs time-step . Long-range electrostatic interactions were calculated using the Particle-Mesh Ewald ( PME ) summation scheme [41] . Van der Waals and short-range Coulomb interactions were truncated at 0 . 9 nm . The non-bonded pair list was updated every 10 steps and conformations were stored every 4 ps . The main chain root mean square deviation ( rmsd ) , which is a parameter used to evaluate the stability of MD trajectories , was computed using the corresponding NMR structure as a reference . The first 10 ns of each trajectory were discarded as initial equilibration for each simulation . Indeed , upon 10 ns the trajectories were generally characterized by average main chain rmsd lower than 0 . 29±0 . 07 nm . FCA is based on the calculation of Mutual Information ( MI ) , which quantifies any kind of correlations including linear , non-linear or higher-order contributions . It has been showed that FCA lead to better-resolved conformational substates or modes than classical Principal Component Analysis ( PCA ) [42]–[44] and that these are more often aligned with the actual transition pathways in the structural ensembles [45] Here , the FCA analyses were carried out for the Cα atoms only and using the first 25 eigenvectors from Cα PCA , as suggested in ref . [45] . LMI was employed to quantify correlated motions from MD simulations since it has the advantage of not depending on the relative orientations of the fluctuations [16] , making it possible to identify correlated motions unregard of the difference between their orientations in space . LMI can range from 0 ( uncorrelated motions ) to 1 ( fully correlated motions ) . LMI matrices including the correlated motion between pairs of residues were obtained computing Cα LMI using non over-lapping averaging windows of five ns ( Figure S3 ) . A cutoff of 0 . 5 was selected to reduce noise and to identify significant correlations , aiming to exclude from the analyses the pairs of residues that are poorly communicating with each other and likely to be characterized by almost uncoupled motions . To identify a suitable cutoff for significant correlation , differences between average LMI matrices calculated with one-ns and five-ns averaging windows for the same MD run , as well as between average LMI matrices calculated for the different replicates of the same protein ( i . e . different force-field descriptions or different starting structures ) were calculated . The probability density function for the difference values was then calculated , along with the maximum value of the difference and the pairs of residues , which were interested by the highest differences for each protein . In particular , no differences were identified higher than 0 . 35 and related to just few pairs involving the C- and N-terminal residues . Moreover , the Forbenius norm between the different LMI matrices have been calculated to quantify the similarity between the LMI matrices from different replicates of the same system . In particular , given two matrices of the same size , it is possible to evaluate their degree of similarity by calculating the Frobenius norm of the difference between them . The Frobenius norm for two given LMI square matrices of order m , LMIA and LMIB , was calculated as followswhere aij and bij are elements of respectively LMIA and LMIB and the matrix order m is equal to the number of residues of the target protein . The PSN approach was integrated to the LMI matrices of correlated motions ( PSN/LMI ) [13]–[15] to identify the most relevant communication paths in ARID3A and Dri simulations . The PSN method employs the graph formalism to define a network of interacting residues in a given protein from the number of non-covalent interacting atoms , using a calculated Iij interaction strength value as the edge weight , where i and j are residue identifiers . This value is calculated on the basis of the number of distinct atom pairs ( nij ) between residues i and j within a distance cutoff of 0 . 45 nmwhere Ni and Nj are normalization values for residues i and j obtained from a statistically significant protein dataset [17] , [46] . Nodes are connected to edges when Iij>Imin , where Imin is a defined cutoff value . The residues that have zero edges are termed as orphans , whereas those that are involved in more than four edges are referred as hubs at a specific Imin value . The node inter-connectivity is used to highlight the cluster-forming nodes , where a cluster is a set of connected residues in the graph . The node clustering procedure is such that nodes were iteratively assigned to a cluster if they could establish a link with at least one node in the cluster . A node not linkable to existing clusters initiates a new cluster in an iterative procedure until the node list is completed . Cluster size , defined as the number of nodes , is known to vary as a function of the selected Imin and the size of the largest cluster is used to calculate the Icrit value . At Imin = Icrit , the weak node interactions are generally discarded . Therefore , in our calculation Imin was set equal to Icrit , where Icrit is the value of Imin at which the size of the largest clusters in the graph significantly changes [17] , [46] . In particular , an Icrit value of 7 was obtained for all the MD runs under investigation . To obtain a single PSN for each MD trajectory , a PSN was calculated for each frame and only edges present in at least half of the simulation frames were considered . For each pair of nodes in the PSN graph , the Floyd-Warshall algorithm was employed to identify the shortest path of communication . The distance between directly connected residues in the graph was considered to be 1 , and the shortest path was identified as the path in which the two residues were non-covalently connected by the smallest number of intermediate nodes . Only the shortest paths in which at least one identified node featured a significant correlation value ( 0 . 5 ) with one of the residues of the select pair were retained . The correlation values were evaluated by the LMI analyses described above . All the PSN , LMI and PSN-LMI calculations were performed using the WORDOM MD trajectories analysis suite [23] and in-house available Python scripts for analyses of WORDOM outputs . The plot of the paths on the 3D structures were carried out using the xPyder [47] plugin for PyMOL . To predict the effects induced by ARID3A mutations on protein stability , we used the ARID3A NMR structure ( first conformer in the PDB entry 2KK0 ) that was repaired by the Repair module of Fold-X . To assess the effects of the mutations , we then use the BuildModel module of Fold-X v . 3 . 0 [22] and we carried out 5 independent run for each mutations .
Regulation of DNA transcription is a key element for the cell to finely regulate its physiological processes . This is acquired by the use of a special class of proteins that bind to DNA and function as transcriptional regulators . ARID domains are responsible for many of these DNA-protein interactions in proteins involved in important physiological functions , including cell-cycle regulation and embryonic development . Nevertheless , the structural effects and the conformational changes induced by DNA-binding on the ARID structure have been poorly characterized so far . Here , we provide the first characterization of long-range effects induced by DNA-binding on ARID domains . In particular , we identified routes of communications from DNA-binding loops to distal residues in helix-5 . These routes pre-exist in the free protein and are strengthened by DNA interaction . We also investigated mutations that experimentally impair DNA-binding . Our results show that these mutations perturb wild-type routes of communication , allowing to link their effect on structure and dynamics to function . We have also found a region that might be used for recruitment of biological partners . We predicted the effects induced by mutations at other crucial sites for ARID dynamics . Our results are thus likely to boost the future experimental and structural research on ARID domains .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biochemistry", "proteins", "protein", "structure", "biology", "and", "life", "sciences", "dna-binding", "proteins", "computational", "biology", "biophysics", "biophysical", "simulations" ]
2014
Communication Routes in ARID Domains between Distal Residues in Helix 5 and the DNA-Binding Loops
Influenza A virus ( IAV ) triggers a contagious and potentially lethal respiratory disease . A protective IL-1β response is mediated by innate receptors in macrophages and lung epithelial cells . NLRP3 is crucial in macrophages; however , which sensors elicit IL-1β secretion in lung epithelial cells remains undetermined . Here , we describe for the first time the relative roles of the host innate receptors RIG-I ( DDX58 ) , TLR3 , and NLRP3 in the IL-1β response to IAV in primary lung epithelial cells . To activate IL-1β secretion , these cells employ partially redundant recognition mechanisms that differ from those described in macrophages . RIG-I had the strongest effect through a MAVS/TRIM25/Riplet–dependent type I IFN signaling pathway upstream of TLR3 and NLRP3 . Notably , RIG-I also activated the inflammasome through interaction with caspase 1 and ASC in primary lung epithelial cells . Thus , NS1 , an influenza virulence factor that inhibits the RIG-I/type I IFN pathway , strongly modulated the IL-1β response in lung epithelial cells and in ferrets . The NS1 protein derived from a highly pathogenic strain resulted in increased interaction with RIG-I and inhibited type I IFN and IL-1β responses compared to the least pathogenic virus strains . These findings demonstrate that in IAV-infected lung epithelial cells RIG-I activates the inflammasome both directly and through a type I IFN positive feedback loop . Influenza A virus ( IAV ) is the etiological agent of a contagious acute respiratory disease . Its seasonal and , more rarely , pandemic strains – such as the deadly 1918 H1N1 virus , are responsible for severe illness and considerable mortality worldwide [1] , [2] . The outcome of IAV infections is largely determined by complex interactions between the virus and the innate immune system; therefore , a detailed understanding of the molecular mechanisms involved in innate immune recognition and response can provide a valuable framework for therapeutic development . A protective interleukin 1β ( IL-1β ) response primarily mediated by macrophages and lung epithelial cells is a key component of the innate immune response to influenza infection [3] . At least four pattern recognition receptors ( PRR ) that sense IAV infection may be involved: toll-like receptor 3 ( TLR3 ) ; TLR7; retinoic acid-inducible gene-I ( RIG-I , also known as DDX58 ) ; and NOD-like receptor family , pyrin domain containing 3 ( NLRP3 ) . Lung epithelial cells that line the respiratory tract are the primary targets of influenza infection [4]–[9] . However , the mechanisms of IL-1β secretion in lung epithelial cells remain unresolved . In macrophages and dendritic cells , genomic IAV RNA is detected by TLR7 , leading to the stimulation of interferon-α ( IFN-α ) production [10] and the synthesis of the immature ( “pro” ) form of IL-1β ) [11] . This upregulation of biologically inactive pro-IL-1β is the first signal needed to produce a mature , bioactive form of IL-1β via the formation of an NLRP3 inflammasome . To this end , NLRP3 , in complex with the adaptor protein ASC ( also known as PYCARD ) , first induces proteolytic activation of caspase 1 . In turn , activated caspase 1 cleaves pro-IL-1β and promotes secretion of mature IL-1β through a nonconventional pathway [11] . Several mechanisms have been proposed to explain NLRP3 inflammasome activation in IAV-infected macrophages , including lysosomal maturation , release of reactive oxygen species [3] , and perturbation of ionic concentrations through IAV-encoded M2 ion channels expressed in the trans Golgi network [11] . In macrophages , type I IFNs have also been shown to negatively regulate IL-1β production through poorly understood mechanisms [12] . In lung epithelial cells , both TLR3 and RIG-I play a critical role in IAV pathology , and against this infection [4] , [13] , [14] . TLR3 primarily elicits a pro-inflammatory response upon binding to double-stranded RNA species produced during IAV infection [4] . By contrast , RIG-I recognizes cytosolic single-stranded RNA genomes [15] , [16] . By interacting with the mitochondrial adaptor MAVS/IPS-1/cardif/VISA , it elicits both pro-inflammatory and antiviral responses through the transcription factors NF-κB and IRF-3 , respectively [4] . Further underscoring their relevance in the host response [17] , RIG-I responses are tightly regulated , either positively by TRIM25 [18] and Riplet [19] , or negatively by the suppressor of cytokine signaling ( SOCS ) 1 and SOCS3 [5] . On the virus side , the nonstructural protein 1 ( NS1 ) is the main IAV IFN antagonist [2] , [18] , [20]–[23] . NS1 interacts with RIG-I and its co-activator TRIM25 , impairing the activation of the transcription factors that drive IFN-β expression [18] , [21] . In addition , in macrophages , NS1 also inhibits caspase 1 activation and IL-1β production [24] . To clarify the host–virus interactions that shape the IL-1β response in human lung epithelial cells , we first examined the relative roles of host innate receptors RIG-I , TLR3 , and NLRP3 in the IL-1β response in primary cells . We then analyzed the impact of IAV NS1 on this response in association with virulence in ferrets . We provide evidence that IL-1β secretion is controlled by parallel pathways involving RIG-I/TLR3/NLRP3-dependent inflammasome activation , with RIG-I at the most upstream position . Furthermore , we show that type I IFNs are required for inflammasome activation and that these cytokines mediate RIG-I–dependent regulation of TLR3 and NLRP3 expression . We also demonstrate that RIG-I directly activates the inflammasome by binding to ASC and caspase 1 in primary lung epithelial cells . In support of a role for RIG-I-dependent type I IFN signaling in lung epithelial cells , we show that NS1 modulates IL-1β secretion . Indeed , recombinant viruses carrying NS1 from the highly pathogenic 1918 strain inhibited IL-1β secretion , as they induced a decrease in type I IFN signaling and RIG-I protein expression; this could result from an increased interaction between 1918 NS1 and RIG-I , as opposed to NS1 from other strains . Furthermore , 1918 NS1–dependent virulence correlated with inhibition of both type I IFN and IL-1β expression in IAV-infected ferrets . Altogether , our findings demonstrate that RIG-I is pivotal to the activation of the IL-1β response in lung epithelial cells , which involves a type I IFN–positive feedback loop . To examine inflammasome activation in response to IAV infection in lung epithelial cells , we measured IL-1β production in normal , human primary bronchial epithelial cells ( NHBE ) derived from five donors ( Table S1 ) following infection with the H1N1 viruses A/Puerto Rico/8/34 ( PR8 ) and seasonal A/USSR/90/77 ( USSR ) . Dose-response studies indicated that both virus strains induced IL-1β production in NHBE cells to similar levels ( Figure 1A ) . Next , to study caspase 1 function in the IL-1β response to IAV in these primary cells , we knocked-down caspase 1 expression with specific siRNAs . As shown by western-blot for pro-caspase 1 ( Figure 1B ) and by ELISA quantification of p20 caspase 1 ( Figure 1C ) , siRNA against caspase 1 almost abrogated pro-caspase 1 expression in IAV-infected and uninfected cells ( Figure 1B ) , as well as p20 caspase 1 secretion in the cell supernatant of IAV-infected cells ( Figure 1C ) . Consequently , we observed that the IL-1β response to IAV infection was dramatically decreased in cells transfected with siRNA against caspase 1 in comparison to cells transfected with control siRNA ( Figure 1D ) . However , despite an efficient caspase 1 knockdown ( Figures 1B and 1C ) , the remaining IL-1β secretion observed in response to IAV could suggest caspase 1-independent IL-1β production . These results demonstrate that caspase 1 has a critical role in the IL-1β response to IAV infection in NHBE primary cells . RIG-I , TLR3 and NLRP3 are expressed in lung epithelial cells [3] , [4] . To characterize the mechanism underlying the IL-1β response in NHBE cells , we measured receptor transcript levels; we also assessed the efficiency of specific knockdowns of TLR3 , RIG-I , and NLRP3 in primary NHBE cells at 13 h post-infection ( time of peak transcriptional response to IAV ) . As expected , primary NHBE cells expressed the three PRRs , of which RIG-I showed the highest up-regulation in response to IAV infection ( Figure 1E ) . Moreover , siRNA inhibition specifically and significantly reduced receptor transcript expression ( Figure 1E ) and RIG-I protein levels ( Figure 1F ) , as well as the secretion of the active form of IL-1β ( p17 ) into the supernatant ( Figures 1F and G ) . When we measured NS1 protein levels on the same immunoblots , we did not detect a decrease in intracellular or supernatant NS1 levels of cells treated with specific siRNAs compared to those treated with control siRNA ( Figure 1F ) . This demonstrates that siRNA treatment did not prevent or attenuate infection . The results were confirmed in USSR- and PR8-infected cells from 3–5 donors ( Figures 2A and B and S1 ) , further indicating that the observed changes in IL-1β secretion were PRR-dependent . We then examined in more detail the function of individual PRRs in NHBE cells . Among the PRRs tested , RIG-I downregulation had the strongest effect , resulting in a 3 . 1-fold and a 3 . 7-fold greater inhibition of IL-1β secretion than TLR3 and NLRP3 siRNA treatments , respectively , in both USSR- and PR8-infected primary NHBE cells ( Figures 1F and G; 2B; and S1A , S1C and S1D; p<0 . 0001 ) . The role of RIG-I was further studied using siRNAs to knock down the expression of its signaling partners: MAVS , TRIM25 [18] and Riplet [19] . Downregulation of each of these transcripts resulted in a significant inhibition of the secretion of cleaved IL-1β upon IAV infection ( Figures 1F and G ) . Altogether , these data indicate that IAV infection triggers a potent IL-1β response in human primary lung epithelial cells . This response involves RIG-I , TLR3 , and NLRP3; RIG-I appeared to have the strongest effect , through a MAVS/TRIM25/Riplet–dependent signaling pathway . To further investigate the mechanisms underlying the IL-1β response to IAV infection in primary lung epithelial cells , we studied the contribution of each PRR to the levels of intracellular or activated forms of IL-1β , ASC , and caspase 1 . During IAV infection , the siRNA transfection procedure does not affect the pro-IL-1β protein level: untransfected cells and those transfected with control siRNA display similar levels of the protein ( Figure S2A ) . Furthermore , intracellular pro-IL-1β protein levels in epithelial cell samples treated with either experimental or control siRNAs were not notably different between mock-treated and IAV-infected cells ( Figure 1F ) . However , the level of activated caspase 1 ( p20 ) in the supernatant ( Figure 3A ) and the percentage of IL-1β secretion , which corresponds to secreted IL-1β normalized with respect to both intracellular and secreted IL-1β ( Figure 3B , see Tables S2 and S3 for measured concentrations ) , were significantly reduced by downregulation of RIG-I; TLR3; NLRP3; or the RIG-I-signaling partners MAVS , TRIM25 , and Riplet . The stable pro-caspase 1 observed in all samples ( Figures 3C and S2B ) illustrates that these siRNAs specifically inhibited caspase 1 activation . ASC expression was similar in all experimental conditions ( Figure 1F ) , which indicates that the effect of siRNA on caspase 1 activation is ASC-independent . To rule out cell death as the cause for the observed differences in IL-1β secretion , we determined the levels of caspase 3 cleavage , a common marker of apoptosis , by immunoblot and quantified the proportion of living cells by LDH assay , a measurement of cell membrane integrity . We did not observe any differences in cleaved caspase 3 levels ( Figure 3C ) , LDH activity ( Figure 3D ) , or cell count ( Figure S2C ) between IAV-infected samples treated with either control or experimental siRNAs . Taken together , these results indicate that TLR3 and NLRP3 , as well as RIG-I and its downstream signaling partners MAVS , Riplet , and TRIM25 , elicit inflammasome activation in response to IAV infection by regulating caspase 1 activation and , consequently , IL-1β secretion in a manner independent of cell death . In support of our findings that TLR3 and NLRP3 play a role in inflammasome activation , we found that stimulation of NHBE cells with specific agonists – the synthetic dsRNAs poly ( I:C ) and poly ( A:U ) for TLR3 , and the pore-forming microbial toxin nigericin for NLRP3 – resulted in significant IL-1β secretion ( Figure 3E ) . To better characterize the role of RIG-I in the caspase 1–dependent IL-1β response to IAV infection , we developed a HEK 293T reporter cell assay in which the different components required for IL-1β activation ( ASC , pro-caspase 1 , and pro-IL-1β ) are produced from expression vectors in the presence or absence ( empty vector–transfected cells ) of wild-type ( WT ) RIG-I protein . As a negative control , we used S183I , a loss-of-function variant of RIG-I that is unable to trigger antiviral and pro-inflammatory responses to IAV [25] . S183I affects the second CARD domain of the RIG-I protein . We previously used a combination of biochemical , functional and structural modeling analyses to establish that the single nucleotide polymorphism ( SNP ) S183I inhibits RIG-I-dependent signaling by stabilizing hydrophobic-interaction between CARD domains [25] . Here we observed that , in the presence of WT RIG-I protein , there was a significant upregulation of the IL-1β response to IAV PR8 ( Figure 3F; similar results were obtained upon USSR infection , data not shown ) compared to cells transfected with the empty vector . This IL-1β response was significantly inhibited in the absence of pro-caspase 1 ( Figure 3F ) or in the presence of S183I ( Figure 3F ) relative to control cells and WT RIG-I transfected cells . To confirm that RIG-I can directly activate the inflammasome through its binding to caspase 1 and ASC , we performed coimmunoprecipitation assays of either caspase 1 or ASC with RIG-I in primary lung epithelial cells . Notably , while the levels of expressed and immunoprecipitated ASC protein were similar in mock-treated and IAV-infected NHBE cells ( Figure 3G , WCL and IP ASC ) , RIG-I/ASC complexes were detectable only in IAV-infected cells ( Figure 3G , IP ASC ) . Endogenous RIG-I also interacts with caspase 1 . Indeed , caspase 1 coimmunoprecipitated with RIG-I , when either RIG-I ( IP RIG-I ) or caspase 1 ( IP caspase 1 ) were immunoprecipitated , but not when we used a control antibody ( IP IgG ) ( Figure 3G ) . By contrast with ASC , caspase 1 interacted with RIG-I in both uninfected and IAV-infected cells; the number of complexes was correlated with RIG-I expression , with the highest amount of complexes in IAV-infected cells . These results demonstrate that a functional RIG-I receptor is required for caspase 1–dependent inflammasome activation in response to IAV infection of lung epithelial cells . In response to IAV infection , RIG-I interacts with ASC , and the number of RIG-I/caspase 1 complexes is increased . Thus RIG-I could directly activate the ASC/caspase 1 inflammasome in primary lung epithelial cells . Finally , to investigate possible cross-regulation between PRRs during IAV infection , we evaluated RIG-I , TLR3 , and NLRP3 transcript expression in IAV-infected primary human lung epithelial cells treated with siRNAs against each PRR ( Figure 3H ) . In the context of IAV infection , RIG-I expression was not affected by TLR3 or NLRP3 downregulation , while TLR3 and NLRP3 expression were significantly inhibited in RIG-I knockdown cells ( Figure 3H ) . In contrast , overexpression of RIG-I significantly increased NLRP3 and TLR3 expression in both NHBE primary cells and HEK 293T cells ( Figure S3 ) . RIG-I overexpression also potentiated TLR3 up-regulation in response to IAV infection ( Figure S3 ) . These results indicate that TLR3 and NLRP3 transcript expression is RIG-I–dependent in lung epithelial cells . Furthermore , optimal IL-1β production in primary lung epithelial cells requires RIG-I–mediated TLR3 and NLRP3 upregulation . During IAV infection , RIG-I is a critical regulator of type I IFNs in lung epithelial cells [4] , [5]; its expression is amplified by a positive feedback loop via type I IFNs [4] . In primary NHBE cells , knockdown of RIG-I , but not of TLR3 or NLRP3 , almost completely abrogated the IFN-β response at both the mRNA and the protein level ( more than 75% of inhibition , Figure 4A ) ; this confirms the pivotal role of RIG-I in the type I IFN response to IAV in these cells . The NLRP3 promoter sequence contains predicted binding sites for IFN regulatory elements ( data not shown ) , suggesting that type I IFNs regulate the expression of this receptor , as reported for RIG-I and TLR3 in lung epithelial cells [4] , [5] , [26] . To address this possibility , we used specific siRNAs to knock down the expression of RIG-I , IFN-β , and the type I IFN receptor 1 alpha chain ( IFNAR1 ) in NHBE cells . These siRNA treatments successfully abrogated IFN-β and IFNAR1 transcript expression ( Figure 4B ) . They also severely reduced transcript levels of RIG-I , TLR3 , and NLRP3 ( Figure 4C ) and significantly decreased RIG-I and IFN-β protein levels ( Figures 4D–E and S4A ) , as compared to cells transfected with control siRNA . By contrast , ASC and caspase 1 expression were not affected in the same samples ( Figures 4C and S4B in Text S1 ) . Concomitant with these changes , we observed increased NS1 protein ( Figures 4D and S4C ) levels when IFN-β and IFNAR1 expression were completely inhibited , indicating uncontrolled IAV replication , as expected in the absence of type I IFN responses ( Figure 4B ) . In contrast , the NS1 level was not significantly different between RIG-I and control knockdown cells which could be due to the remaining IFN-β signaling in these cells ( Figure 4B ) . Importantly , inhibition of the type I IFN axis also resulted in a >95% reduction of IL-1β and cleaved caspase 1 secretion in response to IAV infection ( Figures 4F and G ) . To confirm the role of type I IFN in inflammasome activation , NHBE cells were pretreated with recombinant IFN-β before being challenged with the ligands of either TLR3 ( poly ( I:C ) , Figure 4H ) or NLRP3 ( nigericin , Figure 4I ) . We observed that IFN-β pretreatment enhanced the IL-1β response to poly ( I:C ) and nigericin challenge ( Figures 4H and I ) in a dose-dependent manner , indicating that RIG-I–dependent type I IFN induces inflammasome activation by increasing RIG-I , TLR3 , and NLRP3 expression in IAV-infected primary lung epithelial cells . Since RIG-I plays a pivotal role in IFN-β expression , it thus regulates TLR3 and NLRP3 expression . This positive feedback loop could play a critical role in RIG-I-dependent inflammasome activation . As described above , RIG-I directly interacts with ASC and caspase 1 . To functionally address RIG-I-dependent , but type I IFN-independent , inflammasome activation , RIG-I expression was either inhibited or not ( control ) by siRNA transfection in primary NHBE cells . Cells were mock-treated or infected with IAV 8 h before treatment with exogenous IFN-β . Notably , when RIG-I was knocked-down , IFN-β treatment significantly increased IL-1β and p20 caspase 1 secretion in the context of IAV infection ( p<0 . 0001 , Figures 4J and 4K ) . However , as expected if RIG-I has a direct effect on inflammasome activation , IFN-β treatment was not able to restore complete IL-1β secretion and caspase 1 activation in RIG-I knockdown cells ( p<0 . 0001 , Figures 4J and 4K ) . Hence , these data demonstrate the critical role of RIG-I in a type I IFN positive feedback loop that regulates RIG-I , TLR3 , and NLRP3 up-regulation . Moreover these results support the hypothesis of a functional role for RIG-I in direct inflammasome activation in IAV infected cells , as suggested by ASC and caspase 1 interaction with RIG-I shown in Figure 3G . NS1 is the main IAV IFN antagonist [2] , [18] , [20]–[23] . Our finding that type I IFN is a positive regulator of IL-1β in lung epithelial cells led us to investigate the impact of NS1 on the IL-1β host response . In a previous study using reassortant USSR viruses bearing the NS1 protein of either moderately virulent USSR ( WT rUSSR ) , attenuated PR8 ( rUSSR-NS PR8 ) , or highly virulent 1918 ( rUSSR-NS1 1918 ) H1N1 strains , we observed that NS1-mediated inhibition of IFN induction correlates with the virulence of the respective virus in ferrets [20] . rUSSR-NS PR8 was used instead of rUSSR-NS1 PR8 , since replication of the latter virus was impaired in vitro in an earlier study [20] . To examine the relationship between NS1-mediated inhibition of type I IFN and IL-1β responses in vivo , we quantified IL-1β and IFN-β transcript levels in nasal wash cells from ferrets infected with the different viruses in the context of an earlier study [20] . The most severe clinical signs - which are represented by the sum of scores attributed to upper and lower respiratory signs , breathing rate , activity and endurance , as well as lung pathology - were observed for rUSSR-NS1 1918 , followed by WT rUSSR , while rUSSR-NS PR8 caused the mildest disease ( [20] and Figure 5A ) . Here , we observed an increase in IL-1β expression , although with significant inter-virus differences , in which rUSSR-NS1 1918 induced the lowest IL-1β response ( Figure 5B ) . Notably , at days 1 to 3 , rUSSR-NS1 1918 infection resulted in a significantly lower IL-1β response than rUSSR-NS PR8 infection ( Figure 5C ) , even though viral load was similar between the two groups of infected ferrets ( Figure 5C ) . At day 3 , viral load was also similar in WT rUSSR- and rUSSR-NS1 1918-infected ferrets ( Figure 5C ) ; yet rUSSR-NS1 1918 infection resulted in a significantly lower IL-1β response than WT rUSSR infection ( Figure 5B ) . These data suggest that the 1918 NS1 protein results in the most potent inhibition of the ferret IL-1β response in vivo . Furthermore , consistent with the association of type I IFN and IL-1β responses described above , in these experiments , reduced IL-1β expression levels were positively correlated with reduced IFN-β expression levels at days 1 and 2 post-infection ( Figures 5B and 5D , day 1: r = 0 . 56 , p = 0 . 0063; day 2: r = 0 . 47 and p = 0 . 0235 ) . By contrast to rUSSR-NS PR8 , which was not detectable at day 2 and 4 post-infection in the lungs , USSR and 1918 NS1 protein inhibition of type I IFN and IL-1β responses were associated with sustained replication and spread to the lungs ( [20] and Figures 5B and 5D ) . In mice , increased IL-1β production in response to IAV infection was associated with reduced histopathology [27] . Here we noted that rUSSR-NS PR8 infection , which resulted in the highest IL-1β expression ( Figure 5B ) , produced the least tissue damage [20] . This suggests that IL-1β protein expression is proportional to its mRNA expression pattern , at least for rUSSR-NS PR8-infected ferrets as compared to WT rUSSR and rUSSR-NS1 1918 infected ferrets . Due to the lack of IL-1β assay in ferrets we were unable to further investigate NS1 impact on IL-1β response in vivo or ex vivo in ferrets . However , the well described inhibitory effect of NS1 on the type I IFN response [2] , [18] , [20]–[23] , together with our ex vivo results with primary NHBE cells showing that IFN-β is critical to IL-1β response , led us to study NS1 impact on RIG-I/type I IFN/IL-1β signaling in correlation with the known virulence in vivo in ferret . To investigate if NS1 proteins from different strains vary in their interference with the IL-1β response observed in lung epithelial cells , we quantified IL-1β secretion in NHBE cells ( from five different donors ) after infection with different multiplicities of infection ( MOI ) of the NS1 recombinant and parental viruses . Infection with recombinant rUSSR-NS1 1918 resulted in the lowest IL-1β levels in NHBE cells compared to infection with parental WT rUSSR , PR8 , and rUSSR-NS PR8 ( Figure 6A ) . The extent of IL-1β secretion did not correlate with viral growth , which was not different at a low MOI ( MOI 0 . 1 ) and significantly higher for rUSSR-NS1 1918 than for parental WT rUSSR and PR8 in NHBE cells infected at an MOI of 0 . 5 and 1 ( Figure 6B ) . Kinetics analyses of infection with rUSSR-NS1 1918 and WT rUSSR M2 RNA in a human lung epithelial cell line ( NCI-H292 ) indicated that the differences in viral growth observed at a high MOI do not seem to be due to differences in virus infection level . Indeed , M2 RNA derived from both viruses are similarly expressed at early time-points post-infection ( 3 h , 6 h , and 9 h , Figure S5 ) . By contrast , rUSSR-NS1 1918 infection resulted in significantly higher levels of virus M2 RNA at later time-points ( 13 h and 18 h , Figure S5 ) . Because 1918 NS1 inhibited IL-1β secretion , we focused on rUSSR-NS1 1918 and WT rUSSR strains to specifically study the impact of NS1 on the IL-1β response in lung epithelial cells . The differential IL-1β response was correlated with cell viability ( r = −0 . 903 , p<0 . 0001 ) but seems only slightly dependent on cell death , since a less than 11% difference in live cells was observed in NHBE cells infected with WT rUSSR or rUSSR-NS1 1918 ( Figure 6C ) . More importantly , as observed earlier , the amount of secreted IL-1β correlated with the significantly lower levels of type I IFN ( Figure 6D , r = 0 . 885 , p<0 . 0001 ) and RIG-I ( transcript r = 0 . 593 , p = 0 . 0327 , Figure 6E; protein , Figure 6F and G ) expressed during infection with rUSSR-NS1 1918 compared to rUSSR . Moreover , this correlation was also independent of viral replication and thus of NS1 protein expression at a low MOI ( MOI 0 . 1 , Figure 6B , F and H ) . Finally , coimmunoprecipitation experiments , performed at a low MOI , when NS1 protein levels are similar , suggested that 1918 NS1 formed more prominent complexes with RIG-I than USSR NS1 ( Figure 6I ) . As NS1 binding to RIG-I has been shown to inhibit RIG-I-dependent signaling [21] , increased binding of 1918 NS1 may contribute to its potent inhibition of type I IFN signaling and RIG-I expression . However , NS1 is a multi-functional protein that interacts with multiple cellular factors to inhibit the host type I IFN response [2] , [18] , [20]–[23] . Thus the inhibitory impact of 1918 NS1 could be due to its impact on RIG-I activity , through direct protein-protein interactions or indirectly by regulating the type I IFN signaling downstream of RIG-I thereby interfering with the type I IFN-dependent RIG-I upregulation . Furthermore the higher replication of 1918 NS1 at a MOI more than 0 . 1 ( Figure 6B ) is associated with higher expression of 1918 NS1 protein ( Figure 6J ) , which may amplify the inhibitory activity of 1918 NS1 . In support to this hypothesis , the type I IFN response , which is RIG-I-dependent , was significantly lower at MOIs of 0 . 5 and 1 ( Figure 6D ) . The lower type I IFN response could be due to the increased inhibitory effect of NS1 on RIG-I or other type I IFN signaling components downstream of RIG-I and may explain the higher viral replication observed in these conditions ( Figure 6B ) . These results indicate that the IL-1β response to IAV infection in lung epithelial cells is regulated by NS1 , probably through its inhibitory action on the type I IFN positive feedback loop required for RIG-I upregulation; they also confirm the potent inhibitory activity of 1918 NS1 . Thus , NS1 from the highly pathogenic human pandemic virus 1918 , which most strongly binds to RIG-I and thus results in the strongest inhibition of type I IFN signaling in NHBE cells , also induces the strongest inhibition of IL-1β in NHBE cells , and of the IL-1β and type I IFN responses in ferrets . As IAV-triggered immunopathogenesis in ferrets is very closed to that in humans , one could speculate that the high virulence of rUSSR-NS1 1918 , associated with the lowest type I IFN expression in ferrets , could be due to inhibitory impact of NS1 on RIG-I/type I IFN/IL-1β signaling as we demonstrated in human primary lung epithelial cells . IL-1β plays a beneficial role in the in vivo innate immune response to IAV infection [3] , [27] , [28] . Our findings reveal a novel regulation of the inflammasome in lung epithelial cells , which are both the primary target of IAV infection in vivo and major players in the outcome of infection [4]–[9] . In IAV-infected macrophages , IL-1β secretion is NLRP3- , ASC- , and caspase 1-dependent; it has also been suggested to be RIG-I-independent [3] , [11] . Conversely , in primary human lung epithelial cells , RIG-I , TLR3 , and NLRP3 are partially redundant for IL-1β activation through a caspase 1–dependent mechanism . Several lines of evidence support our conclusion that RIG-I is a pivotal inflammasome activator in IAV-infected human lung epithelial cells . First , although there was significant inhibition in TLR3 and NLRP3 knockdown cells , knockdown of RIG-I had the most dramatic effect on caspase 1 activation and IL-1β secretion , independent of the donor and of the viral strain used . Second , inhibition of the RIG-I signaling partners MAVS , TRIM25 , and Riplet also resulted in significant inhibition of caspase 1 activation and IL-1β secretion . Third , WT RIG-I overexpression resulted in a significant upregulation of IL-1β secretion in response to IAV infection in reconstituted inflammasome experiments . In contrast , the S183I loss-of-function variant of RIG-I [25] resulted in inhibition of IL-1β secretion . Fourth , TLR3 and NLRP3 upregulation in IAV-infected NHBE cells is RIG-I dependent , as demonstrated both by RIG-I knockdown experiments and RIG-I overexpression assays . Thus , RIG-I operates upstream of TLR3- and NLRP3-dependent inflammasome activation . Fifth , stimulation of RIG-I is the major inducer of type I IFN responses in lung epithelial cells , as described here and previously [4] , [5]; also type I IFN precedes and induces the IL-1β response and caspase 1 activation , as demonstrated by knockdown of IFN-β and IFNAR1 expression . Sixth , the functional demonstration that RIG-I directly activates the inflammasome in addition to its effect on the type I IFN response was provided by treatment of primary cells with IFN-β , which partially rescued the knockdown effect of RIG-I on the IL-1β response and cleaved caspase 1 secretion . These results mirror our observation with IFNAR1 and IFN-β knockdowns and support our hypothesis that RIG-I is critical for IFN-β-dependent IL-1β response , as IFN-β significantly increased inflammasome activation . It also supports the functional role of RIG-I per se in inflammasome activation , as IFN-β had only a partial rescue effect . Moreover , we observed that , in primary human lung epithelial cells , RIG-I directly interacted with caspase 1 and that IAV infection induces RIG-I binding to ASC , as shown in the context of VSV in a human cell line [29] . Thus , our data demonstrate that RIG-I directly promotes caspase 1 inflammasome activation in IAV-infected primary human lung epithelial cells and amplifies the IL-1β response through a type I IFN positive feed-back loop as shown in Figure 7 . To further validate the cross-talk between RIG-I , type I IFN , and IL-1β during IAV infection , we investigated the impact of influenza NS1 variants with a known effect on virulence and on the type I IFN response in ferrets [20] . It is of note that the virus carrying NS1 from the highly pathogenic 1918 influenza strain significantly inhibited the IL-1β response in ferrets and in human primary lung epithelial cells , as compared to NS1 from a seasonal IAV with moderate virulence [20] , [30] . At least in primary lung epithelial cells , the 1918 NS1 also inhibited both type I IFN and RIG-I upregulation in response to IAV infection , suggesting that its effect on IFN induction contributes to inhibition of the IL-1β response . Furthermore , at a low MOI 1918 NS1 and USSR NS1 are similarly expressed in primary lung epithelial cells , but 1918 NS1 forms more prominent complexes with RIG-I than USSR NS1 . This suggests that 1918 NS1 could induce a stronger inhibition of RIG-I activity than USSR NS1 , which explains its inhibitory effect on the type I IFN and IL-1β responses . At a high MOI , 1918 NS1 was more abundant than USSR NS1 , which may also contribute to its increased inhibitory effect . NS1 has been shown to inhibit type I IFN secretion by interacting with TRIM25 [18] , an ubiquitin ligase critical for RIG-I function; as we show here , TRIM25 is essential for IL-1β secretion . However , the mechanism underlying the differences in inhibition observed for NS1 from the 1918 and USSR viral strains remains unclear , since the previously identified TRIM25-inhibiting residues E96 , E97 , R38 , and K41 are conserved [18] , [20] . In addition , NS1 is a multi-functional protein that interferes with the type I IFN response at several levels [2] , [18] , [20]–[23] . Similar to the regulation of RIG-I and type I IFN expression that we observed , macaques infected with the reconstructed 1918 pandemic virus showed considerably lower induction of these genes at day 3 post-infection in comparison with macaques infected with seasonal H1N1 [31] . Thus , we cannot exclude that the inhibitory effect associated with the 1918 NS1 protein could be , at least in part , due to the impact of NS1 on other cellular components involved in type I IFN signaling [22] , [23] . Further studies involving NS1 site directed mutagenesis and reassortant viruses are necessary to determine whether the 1918 NS1 inhibits TRIM25-dependent RIG-I activation or other cellular components to limit antiviral and inflammasome responses , and which amino acid residues are involved in this function . Altogether , our data on 1918 NS1 raise new questions about the involved mechanism ( s ) , but also demonstrate for the first time the impact of this negative regulator of type I IFN signaling on the lung epithelial cells IL-1β response ( Figure 7 ) . Furthermore , the data support our demonstration of a positive effect of type I IFN on the IL-1β response of lung epithelial cells with an approach using modified virus complementary to the specific targeting of host proteins with siRNA . The influenza virus M2 protein triggers NLRP3-dependent , but likely RIG-I–independent , inflammasome activation in macrophages [11] . Conversely , in lung epithelial cells , NS1 inhibits RIG-I–dependent inflammasomes activation . These results underscore the complexity and specificity of virus interactions with different types of cells during pathogenesis . This suggests that the involvement of different PRRs in inflammasome activation in different cell types and their partial redundancy may play an important role in counteracting viral immune interference , for instance , through NS1 in lung epithelial cells . In line with this idea , 1918 NS1 strongly inhibited IL-1β secretion in lung epithelial cells , which is primarily RIG-I dependent , but did not affect the IL-1β response in macrophages , which is NLRP3 dependent ( data not shown ) . One could hypothesize that the RIG-I–independent inflammasome response of macrophages confers resistance to viruses with an NS1 similar to 1918 NS1 , which inhibits the IL-1β response in lung epithelial cells , but not in cells of myeloid origin . In myeloid cells and in a mouse model of Candida albicans infection , the presence of type I IFNs inhibits the IL-1β response regulated by the activation of the NLRP3 inflammasome and increases mouse susceptibility to C . albicans infection [12] . These results are consistent with reported type I IFN anti-inflammatory effects , which could be due to inhibition of IL-1β production in some autoimmune diseases [32] , [33] . Our results indicate an entirely different paradigm and suggest that conversely such treatment would be deleterious for diseases implicating the lung epithelium , including COPD or asthma [34] , [35] . However , type I IFN is required for activation of the inflammasome in macrophages in response to cytosolic Francisella novicida and Listeria monocytogenes , but not vacuole-localized Salmonella typhimurium [36] . The type I IFN response to these cytosolic bacteria induces inflammasome-mediated cell death in macrophages [36] . Thus , the action of type I IFNs on IL-1β may be dependent on cell type and on the pathogen . Further IAV infection experiments in different cell types , including peripheral blood mononuclear cells and dendritic cells , will be important in determining whether the RIG-I–mediated type I IFN production that we observed is part of the general host response to IAV , or whether it is specific to lung epithelial cells . It is conceivable that the differential regulation of IL-1β by type I IFNs in non-immune versus immune cells reflects the different functions of type I IFNs , which are both antiviral and regulatory during the early infection of lung epithelial cells . At this time-point , it is important both to control virus growth rapidly and to produce sufficient IL-1β to promote cell recruitment [3] , [27] , [28] . However , at the point at which the macrophages become infected , the immunoregulatory role of type I IFNs may become predominant , to prevent potentially deleterious overproduction of IL-1β by macrophages or dendritic cells . Further studies of the cross-regulation of type I IFN and inflammasome responses are required to determine and contrast the beneficial and deleterious roles of type I IFN in inflammasome activation for virus control and clearance from the host . Additional experiments are also required to examine whether our results can be generalized to the native epithelium . One approach would be to use cells cultured in an air-liquid interface , which produces polarized pseudostratified mucociliary cells resembling natural airway epithelial cells . Under these culture conditions , well-differentiated epithelial cells produce a reduced inflammatory response and are more resistant to rhinovirus infection than undifferentiated cells [37] . The enhanced resistance to IAV infection of these differentiated cells could contribute to the control of the inflammatory response of epithelial cells . Furthermore , it has been shown that cytokine secretion in response to IAV infection is polarized towards the apical and basolateral membranes , whereas IFNAR expression is restricted to the basolateral membrane [9] , [38] . The localization of IFNAR limits its stimulation by type I IFN to the basolateral side , which could further reduce the extent of the positive-feed back loop acting on IL-1β secretion in differentiated epithelial cells . However , yet another scenario is conceivable: in vivo , epithelial cells are in close proximity to dendritic cells , which usually reside near the basolateral membrane . In response to virus infection , dendritic cells produce large amounts of type I IFNs , which could act in a paracrine manner to efficiently amplify the production of IL-1β by the airway epithelium . Of note , however , upon IAV infection IFNAR-deficient or STAT1-deficient differentiated mouse epithelial cells show a significant reduction of IL-1β production compared to wild-type controls [9] . Thus , although the extent of the IL-1β response in differentiated epithelial cells infected with IAV cells remains to be established in vivo , the available data indicate that , at least in mouse cells , IL-1β and type I IFN production are positively correlated in differentiated epithelial cells , in a similar fashion to what we have observed in undifferentiated primary human epithelial cells . Our results showing that type I IFN controls inflammasome activation and production of bioactive IL-1β add to our knowledge of how airway epithelial cells respond to infection and regulate lung innate and adaptive immunity [8] , [9] , [39] . Whereas a large body of evidence supports the critical role of IFNAR/STAT1 axis for both lung epithelial immunity as well as the subsequent adaptive immunity [8] , [9] , the mechanisms that mediate these responses are yet not entirely clear . IL-1β is central in the communication between epithelial cells and monocytes during the initiation of inflammation and development of the adaptive response . However , IL-1β can also act in an autocrine manner on epithelial cells infected with rhinovirus to elicit secretion of CXCL8 , a potent neutrophil attractant , and control of viral replication [40] . In addition to long-range signals , epithelial cell IL-1β may have a role in regulating the local homeostasis of the lung epithelium . Epithelial cells express and secrete a battery of immune modulators the role of which is to limit innate inflammation in this environmentally exposed site , including surfactant proteins A and D and mucin 1 , which suppress the activity of alveolar macrophages [41] . Furthermore , alveolar macrophages display a unique response to PRR agonists , characterized by a strong inflammatory response but lacking autocrine/paracrine IFN-β secretion and STAT-1 activation [42] . Thus , it is tempting to speculate that lung epithelial cells , which display a distinctive RIG-I–mediated type I IFN antiviral responses and inflammasome activation , actively participate in the orchestration of lung immune response by providing simultaneously IFN-β and IL-1β paracrine stimulation to alveolar macrophages . Such epithelial responses to infection could provide rapid and robust local immunity to rapidly curb viral load , stimulate immune cells neighboring the affected site while limiting inflammation to the local environment . To clarify these mechanisms conditional or cell type-specific knock-out mice of IL-1β will be required . The targeting of RIG-I–like receptors ( RLR ) with specific agonists has been proposed as a prophylaxis and treatment for IAV , as it may increase antiviral innate and adaptive immunity , leading to more rapid elimination of the virus [43] , [44] . Our results suggest that these therapeutic strategies will not only initiate a powerful antiviral response , but also trigger a potent IL-1β response via RIG-I . Further studies of the tissue specificity of the RIG-I–dependent inflammasome may be useful to determine if other epithelial tissues share the same specificity that we observed in respiratory epithelial cells . This will improve our understanding of whether RLR agonists may be a useful addition to our antiviral therapeutic arsenal , and if they may be instrumental in the next generation of vaccine adjuvants . This study was carried in strict accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of the INRS-Institut Armand-Frappier and the Canadian Council on Animal Care ( protocol # 0911-02 ) . In accordance with current US regulations governing tissue banking in the Code of Federal Regulations , 21 CFR Part 1271 , human tissue was acquired by Lonza through donor programs that perform tissue recovery and donor informed consent following processes approved by an Institutional Review Board . Male ferrets ( Mustela putorius furo ) were infected intranasally as described previously [20] . The H1N1 viruses , PR8 and USSR , were described previously [30] . NS PR8 , NS1 1918 , and WT recombinant USSR ( rUSSR ) viruses were generated from cloned cDNA as described previously [20] . All viruses were propagated in MDCK cells ( ATCC CCL-34 ) in F-12K medium with 2 µg/ml trypsin ( TRTPCK Worthington ) . IAV titers were obtained by standard plaque assay on confluent monolayers of MDCK cells and expressed as pfu/ml . Primary NHBE cells ( CC-2541 , Lonza ) from five male donors ( three of Caucasian origin [111011 , 75008 , 4F1289J] and two of African-American ancestry [118008 , 7F4120]; see Table S1 ) were grown in complete Clonetics BEGM BulletKit ( Lonza ) according to the manufacturer's instructions . NHBE cells were seeded at 8 , 750 cells/well 9 days before infection . All cells were seeded in 24-well plates and washed twice with 200 µl/well OptiMEM medium ( Invitrogen ) before infection with IAV or stimulation with poly ( I:C ) ( 1 or 5 µg/ml , SIGMA ) , poly ( A:U ) ( 100 µg/ml , InvivoGen ) , or nigericin ( 10 µM , InvivoGen ) diluted in OptiMEM ( 200 µl/well ) . In IFN-β pretreatment experiments , NHBE cells were pretreated with human IFN-β ( 8–1 , 000 IU/ml , PBL InterferonSource ) before challenge with poly ( I:C ) or nigericin . In IFN-β treatment experiments of siRNA transfected NHBE cells , cells were mock treated or infected with IAV ( MOI 1 ) 48 h after siRNA transfection ( as described below ) . 8 h later post-infection cells were treated for 16 h with 200 IU/ml of human IFN-β . NHBE cells were seeded as described above 7 days before transfection with siRNAs ( 10 nM ) in 3 µl/well of HiPerfect transfection reagent ( Qiagen ) according to the manufacturer's instructions . Nontargeting siRNAs were used as controls in all experiments . Target sequences of the siRNAs are provided in Table S5 . Cells were mock treated or infected with IAV ( MOI 1 ) 48 h after siRNA transfection . NHBE cells were mock treated or infected with either USSR or rUSSR-NS1 1918 for 18 h . Cells were directly disrupted into the well by adding 1% Triton X-100 , 10 mM of dithiothreitol , and a protease inhibitor cocktail . Samples were further processed as described previously [25] , and coimmunoprecipitation was performed in a 600 µl volume on 2400 µg of cell lysate with 50 µl of protein G sepharose ( BioVision ) and 10 µg of either anti-RIG-I ( ALX-804-849; Enzo Life Science ) , anti-ASC ( ALX-210-905; Enzo Life Science ) , anti-procaspase 1 ( #2225; Cell Signaling Technology ) or the control IgG ( anti-FLAG , M2 , SIGMA ) antibody; protein complexes were analyzed by immunoblotting as described previously [25] with antibodies against RIG-I , ASC or pro-caspase 1 . These procedures are detailed in the supplemental experimental procedures . Unless otherwise stated , data are presented as mean ± SEM of triplicate or quadruplicate samples from at least three independent experiments . Statistical differences were tested using one-way ANOVA followed by Fisher's test , with a threshold of p<0 . 05 in all Figures . Correlation analyses were performed using the Pearson's Correlation test , with a threshold of p<0 . 05 . Probability indicated by asterisks: *p<0 . 05 , **p<0 . 01 , and ***p<0 . 001 . In experiments with siRNA-transfected cells , mock-treated or IAV-infected cells transfected with specific siRNAs were respectively compared to their control siRNA-transfected cells counterparts .
Although epithelial cells lining our respiratory tract are both the primary targets of influenza A virus ( IAV ) infection and major players in the outcome of this infection , we still have an imperfect understanding of their response to the virus . Such knowledge is important to design proper anti-influenza strategies . Here , we discovered that epithelial cells sense and respond to IAV infection quite differently than macrophages . While the pathogen recognition receptor ( PRR ) NLRP3 is crucial in macrophages , we show that IAV infection of primary respiratory epithelial cells triggers IL-1β secretion , which depends not only on NLRP3 but also on two other PRRs , RIG-I and TLR3 . In the IL-1β production pathway , RIG-I occupies the most upstream position; it does so directly , through the formation of a RIG-I/ASC inflammasome , and indirectly , through the up-regulation of these three PRRs via a type I IFN positive feedback loop . Further , the increased virulence of IAV in a ferret infection model implicated NS1 , a virus protein that targets RIG-I , decreasing both type I IFN and IL-1β secretion in epithelial cells . These results improve our understanding of the tissue-specificity of RIG-I antiviral mechanisms involving type I IFN and IL-1β , and suggest the use of RIG-I agonists in anti-viral therapy or as vaccine adjuvants .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "inflammation", "immunity", "virology", "innate", "immunity", "immunology", "biology", "microbiology" ]
2013
Type I IFN Triggers RIG-I/TLR3/NLRP3-dependent Inflammasome Activation in Influenza A Virus Infected Cells
P . multocida is the causative agent of a wide range of diseases of animals , including fowl cholera in poultry and wild birds . Fowl cholera isolates of P . multocida generally express a capsular polysaccharide composed of hyaluronic acid . There have been reports of spontaneous capsule loss in P . multocida , but the mechanism by which this occurs has not been determined . In this study , we identified three independent strains that had spontaneously lost the ability to produce capsular polysaccharide . Quantitative RT-PCR showed that these strains had significantly reduced transcription of the capsule biosynthetic genes , but DNA sequence analysis identified no mutations within the capsule biosynthetic locus . However , whole-genome sequencing of paired capsulated and acapsular strains identified a single point mutation within the fis gene in the acapsular strain . Sequencing of fis from two independently derived spontaneous acapsular strains showed that each contained a mutation within fis . Complementation of these strains with an intact copy of fis , predicted to encode a transcriptional regulator , returned capsule expression to all strains . Therefore , expression of a functional Fis protein is essential for capsule expression in P . multocida . DNA microarray analysis of one of the spontaneous fis mutants identified approximately 30 genes as down-regulated in the mutant , including pfhB_2 , which encodes a filamentous hemagglutinin , a known P . multocida virulence factor , and plpE , which encodes the cross protective surface antigen PlpE . Therefore these experiments define for the first time a mechanism for spontaneous capsule loss in P . multocida and identify Fis as a critical regulator of capsule expression . Furthermore , Fis is involved in the regulation of a range of other P . multocida genes including important virulence factors . Pasteurella multocida is an important veterinary pathogen of worldwide economic significance; it is the causative agent of a range of diseases , including fowl cholera in poultry , hemorrhagic septicemia in ungulates and atrophic rhinitis in swine . P . multocida is a heterogeneous species , and is generally classified into five capsular serogroups ( A , B , D , E and F ) and 16 somatic LPS serotypes ( 1–16 ) [1] . Each serogroup produces a distinct capsular polysaccharide , with serogroups A , D and F producing capsules composed of hyaluronic acid ( HA ) [2] , heparin and chondroitin [3] , respectively . The structures of the serogroup B and E capsules are not known , although preliminary compositional analysis suggests that these capsules have a more complex structure than those produced by serogroups A , D and F [4] . The genes involved in biosynthesis , export and surface attachment of the capsular polysaccharide have been identified for all capsule types [5]–[7] . For strains which express HA , the capsule biosynthetic locus ( cap ) consists of 10 genes; phyA and phyB are predicted to encode proteins responsible for lipidation of the polysaccharide , hyaE , hyaD , hyaC and hyaB encode proteins required for polysaccharide biosynthesis and hexD , hexC , hexB and hexA encode proteins responsible for transport of the polysaccharide to the bacterial surface [6] . The P . multocida capsule is a major virulence determinant in both serogroup A and B strains . In the serogroup A strain X-73 ( A:1 ) , inactivation of the capsule transport gene hexA resulted in a mutant strain that was highly attenuated in both mice and chickens , and was more sensitive to the bactericidal activity of chicken serum [8] . Similarly , mutation of the hexA orthologue , cexA , in the serogroup B strain M1404 also resulted in significant attenuation; the M1404 cexA mutant was 4–6 times more sensitive than the parent to phagocytosis by murine macrophages [9] . Spontaneous capsule loss during in vitro sub-culture has been described in P . multocida [10] , [11] . In one study , acapsular variants were derived from capsulated parent strains by repeated laboratory passage ( >30 sub-cultures ) [12] . Sequence analysis of the cap locus in one of these acapsular variants identified two nucleotide changes near the putative promoter region , but the authors did not determine whether these changes were responsible for the observed acapsular phenotype . No further work has been published on the genetic mechanisms of regulation of P . multocida capsule production . Fis is a growth phase-dependent , nucleoid-associated protein which plays a role in the transcriptional regulation of a number of genes in diverse bacterial species ( reviewed in [13] ) . In Escherischia coli , Fis is expressed at high levels in actively growing cells ( >50 000 molecules per cell in early exponential growth phase ) , and expression drops to very low levels during stationary phase [14] , [15] . In addition to growth phase regulation , levels of Fis are negatively regulated by the stringent response during nutrient starvation [16] . Fis can act as both a positive or negative regulator of transcription and it has both direct and indirect effects on gene transcription . In E . coli and Salmonella , Fis binds to a degenerate 15-bp consensus sequence GNtYAaWWWtTRaNC , inducing DNA bending , but only a few of the sequences fitting this consensus are high affinity binding sites [17] , [18] . Fis is involved in the regulation of genes encoding a wide range of functions , including quorum sensing in Vibrio cholerae [19] , and certain virulence factors in Erwinia chrysanthemi [20] , pathogenic E . coli [21] , [22] and Salmonella [23] . In this study , we have characterized three independently isolated spontaneous acapsular derivatives of the P . multocida A:1 strain VP161 . Whole genome sequencing and DNA microarrays were used to show that the global regulator Fis not only controls the expression of capsule biosynthesis genes in P . multocida , but also regulates a number of other genes , including known and putative virulence factors . Spontaneous capsule loss has been reported previously in P . multocida , and is generally associated with long term in vitro passage on laboratory media [10]–[12] . During routine strain maintenance of a signature-tagged mutagenesis library , we identified three independent P . multocida strains that presented with both large mucoid and small non-mucoid colonies after recovery from short term ( <1 year ) −80°C glycerol storage . Re-isolation of either colony type resulted in stable populations with colony morphologies identical to those of their parents , such that AL609 , AL622 and AL620 gave rise to the small non-mucoid variants AL1114 , AL1162 and AL1396 and to the large mucoid variants AL1115 , AL1163 and AL1397 , respectively ( Table 1 ) . Quantitative HA assays confirmed that all three small , non-mucoid colony variants ( AL1114 , AL1162 and AL1396 ) expressed significantly less capsular material than their paired large , mucoid colony variants ( AL1115 , AL1163 and AL1397 ) and the parental VP161 strain ( Fig . 1 ) . Indeed , the small colony variants expressed similar levels of HA to that expressed by a defined ( hyaB ) acapsular polysaccharide biosynthesis mutant generated by single crossover allelic exchange ( AL919; Table 1 ) ( Fig . 1 ) . As each of the paired strains was derived from transposon mutants with different transposon insertion sites ( AL609 , AL622 and AL620; Table 1 ) , and the transposon was still present at identical positions in both the paired mucoid and non-mucoid derivatives of each type , we concluded that the acapsular phenotype was independent of the initial transposition event . The genes responsible for HA capsule polysaccharide biosynthesis and transport have been identified previously and are located in a single region of the P . multocida chromosome [6] ( Fig . 2 ) . In order to investigate whether the loss of capsule production in these spontaneously arising acapsular variants was due to a mutation in the cap biosynthetic locus , the nucleotide sequence of the entire 14 , 935 bp locus of AL1114 and the wild-type parent VP161 was determined . Comparison of the sequences revealed that they were identical; indicating that the acapsular phenotype observed in AL1114 was not due to mutation within the cap locus . As there were no sequence changes observed between these two strains , we investigated transcription across the cap locus by quantitative real-time RT-PCR ( qRT-PCR ) . Transcription of the P . multocida capsule biosynthetic genes is predicted to initiate from divergent promoters located in the intergenic region between the divergent phyA and hyaE genes ( Fig . 2 , [6] ) . Transcription of phyA and hyaE was significantly reduced in the acapsular variant AL1114 as compared to both the paired capsulated strain AL1115 and the parent strain VP161 ( Fig . 3 ) . Furthermore , a directed P . multocida hyaB mutant ( AL919 , Table 1 ) , showed high levels of transcription across both genes showing that transcription across the locus is not affected by the level of capsular polysaccharide on the cell surface . These data show that the reduced capsule production in the acapsular variant AL1114 was likely a result of reduced transcription across the biosynthetic locus . To characterize further the transcriptional regulation of the cap locus , we identified the position of the hyaE transcriptional start site by fluorescent primer extension ( Fig . 2 ) . A primer extension product was generated from P . multocida VP161 RNA using the primer BAP5476 ( Table 2 ) . A 190 bp extension fragment was detected , ( Fig . 2B ) , which identified the transcript start site for hyaE as 37 bp upstream of the hyaE start codon ( Fig . 2 ) . The −10 and −35 regions of the hyaE promoter were predicted based on the identified transcript start site ( Fig . 2 ) . Repeated attempts failed to detect a primer extension product corresponding to phyA . To determine the activity of the phyA and hyaE promoters in both encapsulated and non-encapsulated strains , the intergenic region between phyA and hyaE ( Fig . 2 ) was cloned in both orientations into the P . multocida promoter-detecting vector pMKΩ ( Table 1; [24] ) to generate pAL596 and pAL597 . In pAL597 the pMKΩ kanamycin resistance gene is under the control of the hyaE promoter while in pAL596 it is under the control of the putative phyA promoter . These plasmids were then tested for their ability to confer kanamycin resistance on the wild-type P . multocida strain VP161 , the encapsulated strain AL1115 and the acapsular variant AL1114 ( Table 1 ) . Both plasmids conferred higher levels of kanamycin resistance to the wild-type strain VP161 and the encapsulated strain AL1115 than when present in the acapsular strain AL1114 ( Fig . 4 ) . In contrast , the acapsular strain AL1114 , harboring either pAL596 or pAL597 remained kanamycin sensitive , indicating that the phyA and hyaE promoters are inactive in this strain . These data show that both the phyA and hyaE promoters are active only when present in the encapsulated strains VP161 and AL1115 , indicating that the activity of these promoters is regulated by a trans-acting transcriptional regulator which is inactive in the acapsular strain AL1114 . In order to identify the trans-acting transcriptional regulator responsible for the regulation of capsule expression , we sequenced the entire genomes of the acapsular variant AL1114 and its paired capsular strain AL1115 , using high-throughput short read sequencing . Reference assemblies were generated for both strains using the fully annotated P . multocida PM70 genome [25] as a scaffold . These assemblies were then used to determine nucleotide differences between AL1114 and AL1115 , and thus identify changes unique to AL1114 . Three nucleotide changes were identified as unique to AL1114 when compared to AL1115 ( Table 3 ) ; of these , the mutations within asd and bioA were silent and did not result in amino acid substitutions . However , the observed nucleotide T to C transition within an ORF annotated as encoding Fis , would result in a non-conservative L28S amino acid substitution within the Fis protein . The deduced P . multocida Fis protein is 99 amino acids in length and shares 80% identity with the 98 amino acid E . coli Fis ( NCBI GeneID 947697; http://www . ncbi . nlm . nih . gov/sites/entrez ? db=gene&cmd=Retrieve&dopt=Graphics&list_uids=947697 ) which has been shown to be a nucleoid-associated transcriptional regulator . To confirm that the mutation observed in fis was associated with loss of capsule expression , the nucleotide sequence of fis was determined by Sanger dideoxy sequencing in all three acapsular variants ( AL1114 , AL1162 and AL1396 ) and their paired capsulated strains ( AL1115 , AL1163 and AL1397 ) . Analysis of these sequence data confirmed the L28S mutation in Fis in AL1114 compared to AL1115 . In AL1162 , a G to T transversion at nucleotide 3 resulted in a change from the methionine start codon to the non-start codon isoleucine ( ATT ) , stopping translation of Fis . In AL1396 , a C to T substitution at nucleotide 222 resulted in a nonsense mutation ( Q75* ) and termination of the Fis protein at amino acid 74 . These data are consistent with the hypothesis that mutation of fis was correlated with loss of capsule expression in all three spontaneous acapsular P . multocida strains . In order to confirm Fis as the transcriptional regulator of capsule expression , we complemented each of the spontaneous acapsular variants with an intact copy of Fis in trans . In E . coli , fis is auto-regulated , and is expressed as part of a two gene operon together with the upstream gene yhdG , predicted to encode a tRNA-dihydrouridine synthase [14] , [16] , [26]; the same organization is observed in P . multocida . We initially attempted to clone fis by itself but were unable to successfully make this construct . Therefore , we cloned fis , the overlapping upstream gene pm1087 and the predicted native promoter , into the P . multocida shuttle vector pPBA1100 , generating the plasmid pAL727 ( Table 1 ) . The plasmid pAL727 and the vector only ( pPBA1100 ) were separately introduced into each of the acapsular variants AL1114 , AL1162 and AL1396 and quantitative HA assays performed to determine levels of capsule expression . In all cases , HA production was significantly higher in strains harboring pAL727 ( AL1399 , AL1401 and AL1403 ) than in control strains harboring empty vector ( AL1398 , AL1400 and AL1402 ) ( p<0 . 05 ) , although full complementation to wild type levels was not observed ( Fig . 1 ) . To confirm that Fis is essential for capsule production in P . multocida we constructed two independent , marker free fis mutations in the wild-type P . multocida VP161 strain using the intron-mediated TargeTron system ( Sigma ) . We constructed two P . multocida-specific TargeTron vectors that were retargeted for the insertional inactivation of fis at nucleotide 48 ( pAL706 and pAL708; Table 1 ) . P . multocida transformants with intron insertions in fis were identified by PCR and , following curing of the mutagenesis plasmid , correct insertion of the intron in fis was confirmed by direct genomic sequencing ( data not shown ) . A single insertion mutant generated from transformation with either pAL706 or pAL708 was selected for further study , and designated AL1404 and AL1405 respectively . Quantitative HA assays confirmed that insertional inactivation of fis resulted in the loss of capsular polysaccharide production in both AL1404 and AL1405 ( Fig . 1; Table 1 ) , showing unequivocally that Fis is essential for the production of capsular polysaccharide in P . multocida strain VP161 . Fis is known to be a global regulator in a number of bacterial species [15] , [20] , [27] . We therefore used whole genome DNA microarrays to compare the transcriptome of the acapsular variant AL1114 ( expressing Fis L28S ) with the encapsulated paired strain AL1115 ( expressing wild-type Fis ) . Custom Combimatrix 12k microarrays were designed and used as described in Materials and Methods . Thirty one genes were identified as significantly down-regulated and eleven genes as significantly up-regulated in the acapsular variant AL1114 ( Table 4 ) . Seven of the ten capsule biosynthesis genes were identified as down-regulated in AL1114 compared to AL1115 , supporting the qRT-PCR data showing reduced transcription of phyA and hyaE . Expression of the known P . multocida virulence gene pfhB_2 and its predicted secretion partner lspB_2 was reduced 3- to 4-fold in AL1114 . In addition , the gene encoding the outer membrane lipoprotein PlpE , which is a surface exposed lipoprotein that can stimulate cross-serotype protective immunity against P . multocida infection [28] , was also down-regulated in the acapsular strain AL1114 . Other down-regulated genes included pglA , encoding a cryptic heparosan synthase; exbB , an iron-regulated virulence factor; pm1042 , encoding a predicted LPS-specific phosphoethanolamine transferase; htrA , encoding a heat shock protein; fruR , encoding the fructose operon repressor; glmS encoding a fructose-6-phosphate aminotransferase , and a range of genes encoding proteins of unknown function . Eleven genes were identified as up-regulated in the acapsular strain . These included pm1819 and pm1820 , which encode proteins with similarity to the Salmonella SrfB and SrfC proteins , both putative virulence factors also controlled by Fis [23] , tadC , a gene predicted to be involved in an outer membrane secretion system , and seven genes encoding proteins of unknown function . Several of the genes identified as differentially expressed were physically linked on the chromosome and given their similar expression patterns we predict that these are expressed as operons ( e . g . , plpE , pm1516 and pm1515; pm0996 , pm0997 and pm0998; pm1819 , pm1820 and pm1821; Table 4 ) . In order to confirm the differential expression of some of the genes identified by the microarray analyses , two different methods were used . Firstly , the putative promoter regions of each of the down-regulated genes pglA , pm0998 , pm1078 , lspB_2 and the region upstream of pm1818 containing the putative promoter for the operon containing the up-regulated genes pm1819 , pm1820 and pm1821 , were cloned into the P . multocida promoter probe vector pMKΩ ( Table 1 ) , generating the recombinant plasmids pAL795 , pAL796 , pAL797 , pAL798 and pAL799 , respectively ( Table 1 ) . The recombinant plasmids were transformed into the acapsular strain AL1114 ( expressing Fis L28S ) , the capsulated paired strain AL1115 ( expressing wild-type Fis ) and the wild-type parent strain VP161 ( Table 1 ) . With the exception of pAL799 , each of the recombinant pMKΩ derivatives conferred higher levels of kanamycin resistance to AL1115 and the wild-type VP161 than to the acapsular variant AL1114 ( Fig . 4 ) . These data support the microarray results and show that the activity of the promoters for pglA , pm0998 , pm1078 and lspB_2 are significantly reduced in the absence of wild-type Fis . Each of the strains harboring pAL799 showed similar levels of kanamycin resistance regardless of the capsule phenotype , suggesting that the cloned fragment in this construct does not contain a Fis regulated promoter , or that the fragment does not contain all the necessary Fis binding sites required for repression of this promoter . As a second method of confirmation , qRT-PCR and western immunoblot analyses were undertaken to confirm the reduced expression of plpE in AL1114 . PlpE is a predicted outer membrane lipoprotein which can stimulate cross-serotype protective immunity against P . multocida [28] . Microarray analysis indicated that the plpE transcription was reduced by approximately 3 . 8-fold in the spontaneously arising acapsular strain ( Table 4 ) . Transcriptional analysis of plpE by qRT-PCR confirmed that the transcription of this gene was significantly reduced ( data not shown ) . Western immunoblots using antiserum generated against recombinant PlpE ( Fig . 5 ) confirmed that PlpE expression was significantly reduced in the spontaneously arising acapsular variants AL1114 and AL1162 , as well as a directed plpE mutant AL1172 ( Table 1 ) , but not in the directed phyB acapsular strain AL1164 . Therefore , PlpE mRNA levels are positively regulated by Fis . The expression of a polysaccharide capsule is critical for the virulence of P . multocida [8] , [9] . While there is evidence that the level of capsule expression in P . multocida responds to certain environmental conditions ( such as growth in the presence of antibiotics , low iron or specific iron sources such as hemoglobin [29]–[32] , there is no information on the mechanism of capsule regulation . There have been numerous reports of spontaneous loss of capsule expression in P . multocida strains following in vitro passage [10] , [11] , but the mechanism by which this occurs has not been determined . Previous work with laboratory-derived , spontaneous acapsular strains has indicated that loss of capsule expression was associated with reduced transcription of genes within the capsule biosynthesis locus [12] . In this study , we identified three independent spontaneous acapsular strains and showed that loss of capsule expression in these strains was also due to reduced transcription of the cap locus . Furthermore , we showed that this reduced transcription was due to point mutations within the gene encoding the global transcriptional regulator Fis . Thus , Fis is essential for capsule expression and these experiments define a mechanism by which spontaneous capsule loss can occur and identify for the first time a transcriptional regulator required for capsule expression in P . multocida . Importantly , while Fis has been shown to be involved in the regulation of a large number of genes in a range of bacterial species , to our knowledge this is the first report showing a role for Fis in the regulation of capsule biosynthesis . Furthermore , this is the first report that a functional Fis protein is expressed in P . multocida and that it acts as a regulator of gene expression . Fis was initially identified as the factor for DNA inversion in the Hin and Gin family of DNA recombinases [33] , [34] . Subsequently , diverse roles for Fis have been described , including both positive and negative regulation of gene expression . Fis has also been identified in other members of the Pasteurellaceae , including Haemophilus influenzae Rd . While the H . influenzae Fis shared 81% identity with the E . coli Fis , it did not display identical activity [35] . Interestingly , P . multocida Fis shares 92% identity with the H . influenzae Fis but only 80% identity with E . coli Fis . Structurally , Fis folds into four α-helices ( A–D ) and a β-hairpin [36] . Helices A and B provide the contacts between Fis monomers , facilitating dimer formation , whereas the C and D helices form a helix-turn-helix motif that is essential for DNA binding [37]–[39] . We identified three spontaneous acapsular strains with point mutations within fis . The Fis mutation L28S is predicted to result in a highly unstable protein , as a mutation in the equivalent position in the E . coli Fis ( L27R ) resulted in an unstable protein with no discernible activity [36] . However , as the P . multocida Fis shares only 80% amino acid identity with the E . coli Fis , we can not rule out the possibility that the P . multocida L28S Fis is a partially functional protein that is impaired in only some specific functions of WT Fis . Computational models also suggest a requirement for hydrophobic residues at this position [40] and the substitution of leucine by the hydrophilic residue serine would significantly reduce the hydrophobicity at this position . The second spontaneous acapsular variant , AL1162 , contained a mutation within the fis start codon , which would result in complete abrogation of Fis expression . Finally , the fis gene in AL1396 contained a nonsense mutation at nucleotide 222 , terminating protein translation at amino acid 74 . This mutant Fis protein would lack the last 16 amino acids , including the helix-turn-helix motif that is essential for DNA binding [39] . As Fis is known to regulate a number of genes in other species , we used DNA microarrays to compare the transcriptome of wild-type P . multocida and the Fis L28S mutant ( AL1114 ) during exponential growth . Comparison of the fis mutant strain with wild-type P . multocida identified 31 genes ( representing at least 20 predicted operons ) as positively regulated by Fis , and 11 genes ( representing at least nine operons ) as negatively regulated by Fis . In E . coli , two transcriptional studies have been conducted comparing gene expression in wild-type and Fis mutant strains . The first study identified more than 200 genes that were regulated by Fis at various growth phases ( >2 fold change , p<0 . 05 ) [15] . The second study identified >900 genes ( 21% of the E . coli genome ) that were significantly differentially regulated in the fis mutant ( false discovery rate <1% ) , although only 17 of these were >2 fold differentially regulated [27] . Interestingly , approximately 70% of the 900 genes shown to be differentially regulated in the second study showed no Fis binding as determined by chromatin immunoprecipitation coupled with high resolution whole genome-tiling arrays [27] . In P . multocida we identified 42 genes as differentially regulated by Fis during the exponential growth phase . During this growth phase the regulation of P . multocida genes by Fis was skewed towards the up-regulation of genes by Fis ( 70% of operons ) , indicating that Fis generally acts as a transcriptional activator , a finding consistent with previous studies [15] , [27] . Both P . multocida and E . coli Fis share significant similarity across the C-terminal DNA binding region , suggesting that they may recognise similar sequences . However , using the available E . coli position specific weight matrix [15] , we were unable to identify conserved sites upstream of all of the Fis regulated genes identified in the DNA microarray experiments . This is not entirely unexpected , as Fis has been shown to bind a variety of AT-rich sequences more or less non-specifically [13] . Indeed , the ability of Fis to induce DNA bending is probably the most important factor in its ability to control transcription [41] . The relatively low number of P . multocida genes regulated by Fis in the exponential growth phase is somewhat surprising . However , as Fis expression in other bacteria has been shown to be growth phase dependant [15] , [42] , [43] , it is likely that other P . multocida genes will be differentially regulated by Fis during different growth phases . While an equivalent L27R mutation in E . coli Fis results in an unstable protein , we can not rule out the possibility that the L28S mutation in P . multocida Fis results in a protein that retains some , but not all , Fis regulatory functions . Thus , it is possible that more genes might be observed as differentially regulated in a Fis null mutant strain and we are currently investigating this possibility . Of the 42 differentially expressed genes identified in the P . multocida Fis mutant , a large number ( 16/42; 38% ) encode proteins that are surface expressed or involved in the synthesis of surface exposed structures . Clearly Fis regulates the genes involved in the biosynthesis of , and surface presentation of , capsular polysaccharide , and expression of these genes is critical for virulence . Fis is also involved in the regulation of the surface exposed virulence factor PfhB_2 and its outer membrane secretion partner LspB_2 and the surface expressed lipoprotein PlpE . Both PlpE and PfhB2 can provide protection against P . multocida infection when used as vaccine antigens [28] , [44] . Other surface-associated Fis-regulated genes identified by the DNA microarray analyses included: pm1042 , encoding a transferase predicted to attach phosphoethanolamine to lipid A of LPS; tadC , a gene located within the tight adherence locus that has been shown in Aggregatibacter actinomycetemcomitans to be responsible for non-specific attachment to surfaces and is required for full expression of the RcpABC outer membrane proteins [45]; pm1078 , encoding a putative iron-specific ABC transporter component; and the genes encoding PM0998 [46] , PM1050 and PM1819 [47] which have all been experimentally shown to be present in outer membrane sub-fractions of the P . multocida proteome . Fis also regulates the expression of ExbB , an inner membrane protein that interacts with TonB and is critical for iron uptake and virulence in P . multocida [48] . The P . multocida filamentous hemagglutinin PfhB_2 has been previously identified as a virulence factor [49] , [50] and recent work has shown that vaccination with recombinant PfhB_2 can induce protective immunity in turkeys [44] . In other species such as Bordetella pertussis the secretion of the filamentous hemagglutinin ( FHA ) into the extracellular medium is reliant on the outer membrane protein FhaC [51] . In both Haemophilus and Bordetella , expression of the outer membrane secretion component is controlled by the two-component signal transduction systems cpxRA [52] and bvgAS [53] respectively . It is clear from our work that in P . multocida Fis co-ordinately activates the expression of PfhB_2 and its upstream predicted secretion partner LspB_2 . However , we can not exclude the possibility that expression of these genes is also dependent on other regulatory mechanisms such as a two component signal transduction system . Of particular significance is the finding that Fis regulates plpE , which encodes the cross protective antigen PlpE [28] . Interestingly , previous studies on spontaneous acapsular strains have indicated that loss of a 39–40 kDa lipoprotein was correlated with the loss of capsular polysaccharide and it was hypothesized that the lack of expression of this protein on the surface was due to the physical loss of capsule [11] , [54]–[56] . We propose that the lipoprotein identified in the above studies is in fact PlpE and its expression is reduced in spontaneous acapsular strains because of the transcriptional down-regulation of the gene due to the absence of Fis . In summary , we have characterized three independently derived , spontaneous , acapsular variants of P . multocida . In all three strains , loss of capsule production was due to a single nucleotide change in the gene encoding the nucleoid-associated protein Fis , identifying for the first time a mechanism for spontaneous capsule loss and a regulator critical for P . multocida capsule expression . Furthermore , analysis of gene expression in the fis mutant provides convincing evidence for the role of Fis in the regulation of critical P . multocida virulence factors and surface exposed components . The bacterial strains and plasmids used in this study are listed in Table 1 . E . coli was grown in 2YT broth and P . multocida in brain heart infusion ( BHI ) broth or nutrient broth ( NB ) . Solid media were obtained by the addition of 1 . 5% agar . When required , the media were supplemented with streptomycin ( 50 µg/ml ) , spectinomycin ( 50 µg/ml ) , kanamycin ( 50 µg/ml ) or tetracycline ( 2 . 5 µg/ml ) . Restriction digests and ligations were performed according to the manufacturers' instructions using enzymes obtained from NEB ( Beverly , MA ) or Roche Diagnostics GmbH ( Mannheim , Germany ) . Plasmid DNA was prepared using Qiagen DNA miniprep spin columns ( Qiagen , GmbH , Germany ) . P . multocida genomic DNA was isolated using the RBC genomic DNA purification kit ( RBC , Taiwan ) . Amplification of DNA by PCR was performed using Taq DNA polymerase ( Roche ) and , when required , PCR amplified products were purified using the Qiagen PCR purification Kit ( Qiagen , GmbH , Germany ) . Oligonucleotides used in this study ( Table 2 ) were synthesized by Sigma , Australia . For transformation of plasmid DNA into P . multocida , electro-competent cells were prepared as described previously [8] and electroporated at 1800V , 600Ω , 25µF . DNA sequences obtained by Sanger sequencing were determined on an Applied Biosystems 3730S Genetic Analyser and sequence analysis was performed with Vector NTI Advance version 10 ( Invitrogen , Carlsbad , CA ) . For inactivation of hyaB in P . multocida strain VP161 we used the previously described single-crossover insertional mutagenesis method which utilizes the λ pir-dependent plasmid pUA826 [57] . A 720 bp internal fragment of hyaB was amplified by PCR using oligonucleotides BAP4399 and BAP4400 ( Table 2 ) , and cloned into the SalI site of pUA826tpi , generating pAL499 ( Table 1 ) . This plasmid was then mobilized from E . coli SM10 λ pir into P . multocida strain AL435 by conjugation , and insertional mutants selected on BHI agar containing tetracycline , spectinomycin and streptomycin . Single cross-over insertion of the recombinant plasmid into hyaB was confirmed by PCR using either of the genomic flanking primers BAP276 or BAP169 ( Table 1 ) together with BAP2782 located within the plasmid pUA826tpi . One transconjugant with the correct insertion in hyaB was selected for further study , and designated AL919 ( Table 1 ) . Disc diffusion assays were performed on soft agar overlays . Briefly , 100 µl of each P . multocida overnight culture was mixed with 3 ml of BHI containing 0 . 8% agar and immediately poured onto a BHI agar ( 1 . 5% ) base . Kanamycin at a range of concentrations , was absorbed onto sterile Whatman paper discs , placed on the agar overlay containing P . multocida , and incubated for 18 h at 37°C . Inhibition of growth was determined as the diameter of the zone of clearing around the discs . Crude capsular material was extracted as described previously [58] with the following modifications . One ml of a P . multocida overnight culture was pelleted by centrifugation at 13 000 g , and washed once with 1 ml of PBS . Washed cells were resuspended in 1 ml of fresh PBS , incubated at 42°C for 1 h , then pelleted , and the supernatant , containing crude capsular polysaccharide , collected . HA content was determined as described previously [8] . Fluorescent primer extension was performed as described previously [59] , with the following modifications . First strand cDNA synthesis was performed with SuperScript III RT ( Invitrogen ) according to the manufacturer's instructions . A typical reaction contained 10 µg of total RNA , 1mM dNTPs and 6-FAM labeled primer at a final concentration of 100 nM . Fragment length analysis of FAM-labeled cDNAs was performed by the Australian Genome Research Facility ( AGRF , Melbourne ) . cDNA fragments were separated on an AB3730 DNA analyzer ( Applied Biosystems ) , and sizes determined using Genemapper V3 . 7 software ( Applied Biosystems ) . High-throughput sequencing was performed on an Illumina GA2 ( Illumina , USA ) by the Micromon Sequencing Facility ( Monash University , Australia ) . Two lanes of 36-bp single end data were generated for both AL1114 and AL1115 . Raw sequence data from both strains was aligned independently to the P . multocida PM70 genome sequence using SHRiMP [60] ( average read depth ∼200 ) , which is able to produce alignments in the presence of single nucleotide polymorphisms ( SNPs ) and insertions and deletions ( indels ) . These alignments were then used to compile , for each position in the reference , a contingency table of counts of observed bases in each of the two samples , and the significance of each different base call was determined using Fisher's exact test . The determined significance values were corrected for multiple testing using the Bonferonni adjustment . Raw read data were also assembled de novo using VELVET [61] or CLC genomics workbench ( CLC ) . For complementation of spontaneous acapsular strains , wild-type Fis and the overlapping upstream ORF pm1087 , were amplified from P . multocida VP161 genomic DNA using oligonucleotides BAP5967 and BAP5969 ( Table 2 ) containing SalI and BamHI sites respectively . The amplified fragment was digested and cloned into SalI- and BamHI-digested pPBA1100 , generating pAL727 ( Table 1 ) . This plasmid was then used to transform the acapsular strains AL1114 , AL1162 and AL1396 , generating AL1399 , AL1401 and AL1403 . As a control , empty pPBA1100 was also used to transform each of these strains , generating AL1398 , AL1400 and AL1402 ( Table 1 ) . For analysis of promoter activity in P . multocida , predicted promoter containing fragments were amplified by PCR and cloned into the P . multocida promoter detecting vector pMKΩ , which contains a promoterless kanamycin resistance gene ( Table 1 , [24] ) . The genomic region containing the hyaE promoter and the predicted phyA promoter was amplified by PCR using the oligonucleotides BAP5091 and BAP5092 ( Table 2 ) and cloned in both orientations into pMKΩ to generate pAL596 and pAL597 . The predicted promoter containing fragments upstream of the genes pglA , pm0998 , pm1078 , lspB_2 and pm1818 ( the first gene in a putative operon containing pm1819 , pm1820 and pm1821 ) were amplified by PCR using the oligonucleotide pairs BAP5834 and BAP5835 ( pglA ) , BAP5828 and BAP5829 ( pm0998 ) , BAP5826 and BAP5827 ( pm1078 ) , BAP5832 and BAP5833 ( lspB_2 ) and BAP5838 and BAP5839 ( pm1818 ) ( Table 2 ) and each fragment cloned into pMKΩ to generate pAL795 , pAL796 , pAL797 , pAL798 and pAL799 , respectively ( Table 1 ) . Each of the recombinant plasmids was then transformed into the wild-type parent strain VP161 , the acapsular fis mutant strain AL1114 and its paired capsulated derivative AL1115 . Promoter activity from the cloned fragment in pMKΩ was assessed semi-quantitatively by disc diffusion assays where a reduced zone of growth inhibition around kanamycin impregnated discs indicated a higher level of kanamycin resistance and therefore promoter activity from the cloned fragment . The E . coli/P . multocida shuttle vector pAL99 ( Table 1 ) was used to generate two TargeTron vectors , pAL692 and pAL705 , for the generation of marker-free fis mutants in P . multocida . The spectinomycin/streptomycin resistant TargeTron vector pAL692 ( Table 1 ) was constructed as follows: pAL99 was amplified by PCR using outward facing primers that flank the aph3 gene ( BAP5358 and BAP5359 ) and digested with EcoRV . This fragment was ligated to an EcoRV-digested PCR fragment containing the aadA gene amplified from pUA826 using the primers BAP5360 and BAP5361 . Following ligation the plasmid was digested with HindIII and FspI and ligated to a 4 kb HindIII/FspI-digested fragment of pJIR750ai encoding the TargeTron intron and ltrA gene ( Table 1 ) such that transcription would be driven by the constitutive P . multocida tpiA promoter . For construction of the kanamycin resistant TargeTron vector pAL705 ( Table 1 ) , the aph3 gene was amplified from pAL99 using the primers BAP5433 and BAP5434 then cloned into EcoRV-digested pAL692 , thereby replacing the aadA gene . Retargeting of the intron within each vector to nucleotide 48 of fis was performed as per the TargeTron user manual ( Sigma ) using the oligonucleotides BAP5932-BAP5934 ( Table 1 ) . The retargeted mutagenesis plasmids , pAL706 ( KanR ) and pAL708 ( StrepR/SpecR ) ( Table 1 ) were used to transform P . multocida VP161 and antibiotic resistant transformants selected on either spectinomycin or kanamycin . Insertion of the intron into the P . multocida genome was detected using the fis-specific oligonucleotides BAP5967 and BAP5968 ( Table 1 ) ; the presence of the intron resulted in a 0 . 9 kb increase in the size of the PCR product compared to the PCR product generated from the wild-type fis ( data not shown ) . Mutants confirmed by PCR to have insertions in fis were cured of the replicating TargeTron plasmid by a single overnight growth in NB broth without antibiotic selection , followed by patching of single colonies for either StrepSSpecS or KanS . Strains cured of replicating plasmid were confirmed as fis mutants by additional PCR amplifications to show the presence of the intron and the absence of a copy of wild-type fis ( data not shown ) . Finally , fis mutations were confirmed by direct genomic sequencing using intron-specific primers . Bacteria were harvested from triplicate BHI cultures at late log phase ( ∼5×109 CFU/ml ) by centrifugation at 13 000 g , and RNA was isolated using TRIzol reagent ( Gibco/BRL ) as described by the manufacturer . The purified total RNA was treated with DNase ( 15 U for 10 min at 37°C ) , and then further purified on RNeasy mini columns ( Qiagen ) . Primers for qRT-PCR were designed using the Primer Express software ( ABI ) ( BAP4995-BAP4998; Table 2 ) . RT reactions were routinely performed in 20 µl volumes , containing 5 µg total RNA , 15 ng random hexamers , 0 . 5mM dNTPs and 300 U SuperScript III Reverse Transcriptase ( Invitrogen ) at 42°C for 2 . 5 h . The synthesized cDNA samples were diluted 50-fold prior to qRT-PCR , which was performed using an Eppendorf realplex4 mastercycler with product accumulation quantified by incorporation of the fluorescent dye SYBR Green . Samples were assayed in triplicate using 2 µl of diluted cDNA with SYBR Green PCR master mix ( ABI ) and 50 nM concentrations of each gene-specific primer . The concentration of template in each reaction was determined by comparison with a gene-specific standard curve constructed from known concentrations of P . multocida strain VP161 genomic DNA . gyrB was used as the normalizer for all reactions . All RT-PCRs amplified a single product as determined by melting curve analysis . Custom Combimatrix 12k microarrays ( Combimatrix , USA ) were designed based on the published sequence of P . multocida PM70 [25] , with the addition of probes specific for ORFs previously identified as unique to P . multocida strain VP161 [62] . cDNA for microarray hybridizations was prepared as for qRT-PCR , except that RNA contamination was removed from the cDNA by the addition of NaOH followed by column purification ( Qiagen minElute , Qiagen ) . A total of 2 µg of purified cDNA was labeled using KREAtech Cy3-ULS ( KREAtech , The Netherlands ) , and used in hybridizations with the Combimatrix 12k microarrays as per the manufacturer's instructions . Triplicate hybridized arrays were scanned on a Genepix 4000b scanner , and spot intensities determined using Microarray Imager v5 . 9 . 3 ( Combimatrix , USA ) . After scanning , each array was immediately stripped and re-scanned as per manufacturers' instructions . Spot intensities of stripped arrays were used as background correction for the quantification of subsequent hybridizations . Spots from duplicate probes were averaged , and the averaged probe intensities analyzed using the LIMMA software package [63] as follows . Background correction was performed using the LIMMA “normexp” method [64] , and the Log2 values calculated . Between-array quantile normalization [65] was then applied to the log transformed spot intensities . A moderated t-test on the normalized log intensities was performed to identify differentially expressed genes . Probes were sorted by significance , and the False Discovery Rate ( FDR ) [66] used to control for multiple testing . Probes showing ≥2-fold intensity change between AL1114 and AL1115 , with a FDR of <0 . 05 were considered differentially expressed ( Table 2 ) . Two probes were designed for all genes over 500 bp in length; genes were classed as differentially expressed if one or both probes showed a differential expression of ≥2- fold . DNA microarray experiments were carried out according to MIAME guidelines and the complete experimental data can be obtained online from the NCBI Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) submission number GSE17686 . SDS-PAGE was performed as described previously [67] . Proteins separated by SDS-PAGE were transferred to Immobilon-P membranes ( Millipore ) . Western immunoblot analysis was performed using standard techniques [68] , with chicken anti-recombinant PlpE as the primary antibody and peroxidase-conjugated anti-chicken immunoglobulin ( raised in donkeys ) as the secondary antibody . Blots were visualized using CDP-Star ( Roche ) , and imaged on a Fujifilm LAS-3000 chemiluminescent imager ( Fujifilm ) . Densitometry was performed using Multi-gauge software v2 . 3 ( Fujifilm )
Pasteurella multocida is an animal pathogen of worldwide economic significance . It causes fowl cholera in wild birds and poultry , hemorrhagic septicemia in ungulates , and atrophic rhinitis in swine . The major virulence factor in fowl cholera-causing isolates is the polysaccharide capsule , which is composed of hyaluronic acid . Although there have been reports of spontaneous capsule loss in some strains , to date there has been no systematic investigation into the molecular mechanisms of this phenomenon . In this study , we describe for the first time the underlying transcriptional mechanisms required for the expression of capsule in P . multocida , and identify a transcriptional regulator required for capsule production .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "biochemistry/bioinformatics", "microbiology/cellular", "microbiology", "and", "pathogenesis", "microbiology/immunity", "to", "infections" ]
2010
Fis Is Essential for Capsule Production in Pasteurella multocida and Regulates Expression of Other Important Virulence Factors
The centromere , on which kinetochore proteins assemble , ensures precise chromosome segregation . Centromeres are largely specified by the histone H3 variant CENP-A ( also known as Cse4 in yeasts ) . Structurally , centromere DNA sequences are highly diverse in nature . However , the evolutionary consequence of these structural diversities on de novo CENP-A chromatin formation remains elusive . Here , we report the identification of centromeres , as the binding sites of four evolutionarily conserved kinetochore proteins , in the human pathogenic budding yeast Candida tropicalis . Each of the seven centromeres comprises a 2 to 5 kb non-repetitive mid core flanked by 2 to 5 kb inverted repeats . The repeat-associated centromeres of C . tropicalis all share a high degree of sequence conservation with each other and are strikingly diverged from the unique and mostly non-repetitive centromeres of related Candida species—Candida albicans , Candida dubliniensis , and Candida lusitaniae . Using a plasmid-based assay , we further demonstrate that pericentric inverted repeats and the underlying DNA sequence provide a structural determinant in CENP-A recruitment in C . tropicalis , as opposed to epigenetically regulated CENP-A loading at centromeres in C . albicans . Thus , the centromere structure and its influence on de novo CENP-A recruitment has been significantly rewired in closely related Candida species . Strikingly , the centromere structural properties along with role of pericentric repeats in de novo CENP-A loading in C . tropicalis are more reminiscent to those of the distantly related fission yeast Schizosaccharomyces pombe . Taken together , we demonstrate , for the first time , fission yeast-like repeat-associated centromeres in an ascomycetous budding yeast . The high fidelity segregation of replicated chromosomes to daughter cells during cell division is essential in maintaining genome integrity . It is achieved by a dynamic and well-coordinated kinetochore-microtubule interaction on a specialized chromosomal element , known as the centromere . Strikingly , the centromere DNA shows rapid diversification in its sequence , length , and the organization of sequence elements across different species [1–3] . The centromere has been categorized into point and regional primarily based on its length . In addition , there are kinetochore protein complexes which are associated specifically to either the point or regional centromere [4] . Point centromeres , which are typically <400 bp long with conserved DNA elements ( CDEs ) but lacking DNA sequence repeats , appear to have evolved only once and are restricted to the Saccharomyces lineage [4] . However , the centromeres of most other organisms are regional in nature and span from as small as a few tens of kilobases ( kb ) as in fission yeast Schizosaccharomyces pombe to as large as multiple megabases ( Mb ) in length as observed in plants and animals . The large regional centromeres of most plants ( reviewed in [5 , 6] ) and animals ( reviewed in [7] ) are composed of an array of either repetitive sequences or transposable elements . A classic example is the human centromeres that are organized as 171 bp monomeric repeats arranged into a higher ordered alpha satellite sequence ( reviewed in [8] ) . The regional centromeres of two ascomycetous fungi , Neurospora crassa and S . pombe , and a basidiomycetous fungus Cryptococcus neoformans are much shorter ( 40 to 300 kb in length ) and composed of either transposon-rich repetitive sequences as in N . crassa [9 , 10] and in C . neoformans [11] , or a heterogeneous central core sequence ( cnt ) flanked by two distinct inverted repeats ( imr and otr ) that are conserved across the centromeres in S . pombe [12–14] . It is noteworthy that the repeat-associated fungal centromeres lack tandem arrays of repeats as observed in the centromeres of higher metazoans . Interestingly , centromeres of chicken [18] , potato [19] and unicellular red alga Cyanidioshyzon merolae [20] represent a distinct class where both repetitive and repeat-less centromeres exist in the same genome . On the other hand , shorter small regional centromeres of 3 to 5 kb non-repetitive , unique sequences have been identified in three Candida species–Candida albicans [15] , Candida dubliniensis [16] and Candida lusitaniae [17] . Interestingly , the centromeres in these organisms lack any sequence conservation shared among different chromosomes in the same species . However , CEN1 , CEN5 , and CENR in C . albicans as well as in C . dubliniensis possess pericentric inverted repeats which are unique to each centromere [16] . The driving force enabling the evolution of centromeres with such remarkable diversity both in the DNA sequence as well as structure , rather than a common optimized centromere configuration , across eukaryotes remains an enigma [1] . The centromere DNA sequence and the organization of the sequence elements are rapidly evolving even in closely related species of three major forms of eukaryotic life—fungi , plants , and animals [1 , 18] . In addition , a series of events including– ( a ) neocentromere formation [19–24] by centromere repositioning at ectopic sites with no obvious DNA sequence homology to the native centromere , ( b ) selective inactivation of a centromere in a dicentric chromosome [25–28] , and ( c ) the presence of identical sequences elsewhere in the genome that do not serve as centromere/neocentromere sites in various organisms support the conclusion that centromere specification is largely epigenetically regulated ( reviewed in [29 , 30] ) . The centromere specific histone H3 variant CENP-A ( also known as Cse4 in yeasts ) [31] is considered to be an epigenetic hallmark of active centromeres [32] . The unique structure of CENP-A chromatin provides the foundation to recruit other kinetochore proteins belonging to the Constitutive Centromere Associated Network ( CCAN ) , Ndc80 complex and Dam1/ Ska complex [33] , and nucleates kinetochore assembly in most organisms [34] . However , the mechanism ( s ) of CENP-A loading at a particular locus across species required for centromere specification and its propagation in subsequent generations remains unclear . As shown in S . pombe , CENP-A loading at the centromere is probably regulated via distinct processes leading to the establishment and propagation of a centromere in most organisms [35] . De novo CENP-A recruitment without any pre-existing mark is crucial to establish a centromere , whereas loading of CENP-A molecules during every cell cycle is important for the propagation of already established centromeres [36] . A common feature of the large regional centromeres in ascomycetous fungi is their inherent association with DNA repeats . Detailed studies on the centromeres of S . pombe revealed that centromere associated repeats provide structural determinants in de novo CENP-A recruitment [37] . In contrast , studies in the human pathogenic budding yeast C . albicans , which possesses small regional centromeres [3] reveal that the centromere DNA sequence ( CEN7 ) , that lacks pericentric repeats , fails to form functional centromere de novo on a naked plasmid harboring the CEN7 because CENP-A could not be recruited to the plasmid CEN7 [38] . This result implies that centromeres are epigenetically specified in absence of the pericentric repeats in C . albicans [38] . However , it remains to be tested whether centromeres with inverted repeats ( such as CEN5 ) can recruit CENP-A de-novo in C . albicans . Candida species , the most commonly encountered human fungal pathogens , cause a wide variety of mucosal infections and organ invasion in immunocompromised patients [39] . Although C . albicans has been long known to be the most abundant Candida species isolated from patients , recent global surveillance programs suggest that non-albicans Candida ( NAC ) species are rapidly emerging as a serious threat due to widespread use of antifungal drugs [40 , 41] . In particular , infections caused by Candida tropicalis , a parasexual human pathogenic yeast , has been increased dramatically worldwide . Particularly in sub-tropical regions of Asia-Pacific , the number of patients with C . tropicalis infection is higher than that caused by C . albicans [40 , 42] . Earlier , we reported centromere properties of C . albicans [15] and C . dubliniensis [16] . Here , we report the identification of the centromeres as binding sites of four evolutionarily conserved kinetochore proteins in C . tropicalis , which has a 30 Mb sequenced diploid genome arranged into 23 supercontigs [43] . A comparative analysis of centromeres suggests a rapid divergence not only in the centromere DNA sequence but also in the organization of the sequence elements in these closely related Candida species . Interestingly , pericentric repeats are shown to be important for de novo CENP-A recruitment on C . tropicalis centromeres . Based on the striking structural resemblance of centromeres and the necessity of pericentric repeats for de novo centromere formation both in C . tropicalis and S . pombe , we propose an independent evolution of repeat-associated centromeres in budding and fission yeasts . We identified four putative kinetochore proteins in C . tropicalis- CtCENP-A ( Cse4 ) , CtCENP-C ( Mif2 ) , CtNuf2 and CtDad1 ( Fig 1A ) . Each of these proteins shares a high degree of sequence conservation to those of the closely related species C . albicans ( S1A Fig ) . Subcellular localization of these proteins in C . tropicalis revealed localization patterns typical of kinetochore proteins in related yeasts [44–47]: a single punctate structure representing clustered kinetochores in unbudded G1 cells that then segregated into two puncta in large-budded cells undergoing mitosis ( Fig 1B ) . In addition , indirect immunofluorescence microscopy with anti-Cse4 antibodies [45] , which are specific to CtCENP-A ( S1B Fig ) , and anti-tubulin antibodies revealed CENP-A to be localized near the spindle pole bodies ( S1C Fig ) . On the basis of the sequence similarities and localization patterns at two different stages of the cell cycle , we conclude that these genes encode conserved kinetochore proteins in C . tropicalis . Kinetochore proteins are important for chromosome segregation in eukaryotes and their depletion results in chromosome segregation defects due to improper microtubule-kinetochore interactions , which may lead to cell cycle arrest due to activation of the spindle assembly checkpoint . For conditional expression of genes , we identified the GAL1 promoter sequence in C . tropicalis ( See Methods ) . To test the function of these putative kinetochore proteins on chromosome segregation in this diploid organism , one copy of each gene was replaced by a marker gene and the remaining copy was placed under the control of the GAL1 promoter . The inability of the conditional mutant strains to grow under non-permissive conditions confirmed that each of these four kinetochore proteins is essential for viability in C . tropicalis ( Fig 2A ) . Moreover , flow cytometry ( FACS ) analysis revealed an accumulation of large budded cells at the G2/M stage during growth in non-permissive conditions ( Fig 2B and S2 Fig ) . A significant number of the arrested cells had either an unsegregated nuclear mass at the bud neck , or unequally segregated nuclei indicating an arrest due to mitotic checkpoint activation ( Fig 2C and S2 Fig ) . Taken together , these results strongly suggest that each of these proteins is essential for proper chromosome segregation in C . tropicalis . Having identified authentic kinetochore proteins , we next sought to map the centromeres in the C . tropicalis genome as the binding sites of CENP-A and CENP-C by chromatin immunoprecipitation followed by next generation sequencing ( ChIP-seq ) [48] . The sequenced C . tropicalis strain MYA-3404 ( CSE4/ CSE4 ) and its derivatives CtKS201 ( MIF2/ MIF2-TAP ) were used for CENP-A ( anti-Cse4 antibodies ) and CENP-C ( anti-Protein A antibodies ) ChIP experiments respectively . Analysis of the ChIP-seq reads against the C . tropicalis genome [43] identified seven CENP-A- and CENP-C-bound overlapping but unique regions as centromeres in C . tropicalis ( Fig 3A and S3A and S3B Fig ) . Primers designed from the seven unique enriched regions identified by ChIP-seq were used to validate the enrichment of CENP-A and CENP-C binding by analyzing ChIP DNA of each of the four kinetochore proteins namely , CENP-A , CENP-C , Nuf2 , and Dad1 on seven supercontigs as compared to a non-centromeric locus ( CtLEU2 ) using semi-quantitative PCR assays ( Fig 3B ) . Moreover , each of these seven regions resides within a long ORF-free region ( S1 Table ) , a common centromeric feature observed in most organisms . To determine chromosomal identity of each of these centromeres , the chromosomes of C . tropicalis ( MYA-3404 ) were first separated on CHEF gels ( see methods ) . The probes were PCR amplified from a unique region adjacent to each centromere . The specific signals on the Southern blot of the CHEF gels revealed that at least five regions reside on different chromosomes ( S4 Fig ) . Due to limited resolution of higher molecular weight chromosomes , the chromosomal identity of two regions ( Scnt 3 and Scnt 4 ) could not be unambiguously verified by the CHEF analysis . These analyses , together with the previously reported 14 telomeric-linked scaffold ends [43] , strongly suggest that there are seven pairs of chromosomes in C . tropicalis . ChIP-seq analyses show a complete overlap in binding of CENP-A and CENP-C to a 2 to 3 kb region on each of the seven centromeres ( Fig 4A and S1 Table ) . To validate the length of the CENP-A/CENP-C binding regions obtained by the ChIP-seq analysis , we scanned the enrichment of each of the four above mentioned kinetochore proteins on the ORF-free region of Scnt 8 by ChIP followed by quantitative PCR ( ChIP-qPCR ) with primers designed at approximately 1 kb intervals across the 10 kb region of Scnt 8 . This analysis revealed that these kinetochore proteins were enriched over a 3 kb ( 632950–636200 ) region on Scnt 8 ( Fig 4B ) and confirms the results obtained from the ChIP-seq experiment . Binding of evolutionarily conserved kinetochore proteins on the same locus proves that the region on each of the seven chromosomes is an important part of a functional centromere in C . tropicalis . The sequence analysis of centromeric DNA revealed that all seven centromeres in C . tropicalis have common structural elements comprising a non-repetitive mid core flanked by inverted repeats ( IRs ) ( Fig 4A and S2 Table ) . The average length of the mid core region is 3 . 5 kb and is flanked by IRs of an average length of each repeat of 3 . 5 kb . This is a dramatic transition in the centromere organization in comparison with the centromeres of other closely related Candida species , C . albicans [15 , 49] , C . dubliniensis [16] and C . lusitaniae [17] . Incidentally , CEN1 , CEN5 and CENR of C . albicans and C . dubliniensis also contain non-conserved short pericentric repeats . The binding of both CENP-A and CENP-C is restricted to 2 to 3 kb non-repetitive mid core region in all centromeres in C . tropicalis ( Fig 4A ) . A similar length of CENP-A binding ( 3 to 5 kb ) has been observed in C . albicans [15] , C . dubliniensis [16] , and C . lusitaniae [17] suggesting a striking conservation in the length of CENP-A chromatin that provides the platform for kinetochore formation [50–52] . On the other hand , the AT-content of the CENP-A-bound mid core regions is found to be 64% in C . tropicalis , which is marginally less than the overall AT-content of the genome ( 67% ) . A similar AT-content of CENP-A bound centromere DNA ( 65% ) was observed in C . albicans [15] . Thus , in spite of the observed rapid change in the centromere DNA sequence and its organization , these closely related species employ a similar length and composition ( in terms of the AT-content ) of the centromere DNA for the recruitment of kinetochore proteins . In silico analysis of centromere sequences in C . tropicalis revealed that the inverted repeats ( IRs ) and mid core regions share a high degree of sequence homology across the centromeres ( Fig 4C and S5A–S5C Fig ) . Between different chromosomes , the mid core regions share 80% homology and 63% identity while the IRs show an average of 92% homology and 82% identity . However , the conservation is much higher between the left and right repeats ( LR and RR ) of the same centromere , with an average of 97% homology and 93% identity ( Fig 4C and S5D Fig ) . In addition , we also observed that tandem direct repeats are present within each inverted repeat ( S5E Fig and S3 Table ) . These groups of tandem repeats were prominent across all arms ( except Scnt 9 , which lacks the final group ) . However , the copy number varied significantly among arms ( S3 Table ) . The observed high level of sequence conservation of the mid core and inverted repeats among the different centromeres in C . tropicalis suggests that these regions might have undergone homogenization via intra- and inter-chromosomal recombinatorial events . Such process may be facilitated by the close association of centromeres in the clustered kinetochores of C . tropicalis ( Fig 1B ) . Rapid divergence in the centromere sequence and structure is often associated with karyotypic changes [53 , 54] , a hallmark of speciation [55–58] . Previously , we demonstrated rapidly changing DNA sequence at the centromeres of orthologous chromosomes in C . albicans and C . dubliniensis without any significant changes in synteny across chromosomes [16] . Here we performed a synteny dot plot analysis between C . albicans and C . tropicalis genomes . This analysis revealed massive chromosomal rearrangements involving several syntenic breaks happened between these two species . Unusually , it appears that intra-chromosomal transpositions and inversions are far more common than inter-chromosome recombination ( Fig 5 ) . Strikingly , inter-chromosome recombination , though uncommon , tends to occur more often near the centromeres ( Fig 5 and S6A Fig ) . For example , in CtScnt3 , the large number of genes to the left of the centromere , and a few on the right , map to CaChr3 . But immediately after the centromere , there are some segments on CtScnt3 that are in synteny with CaChrR and CaChr5 , and then the remainders of CtScnt3 are largely from CaChr6 ( Fig 5 ) . Similar patterns of rearrangement can be seen in most other supercontigs also except CtScnt 7 . This pattern of rearrangement was plausible probably due to recombination at highly identical sequences of inverted repeats . A similar phenomenon of centromeric repeat-mediated rearrangement and subsequent gain of a chromosome has been observed in two laboratory strains of S . pombe [59] . Incidentally , there is a change in chromosome number from eight pairs in C . albicans and C . dubliniensis to seven pairs in C . tropicalis indicating a possible structural rearrangement involving centromere which might have given rise to a centromere gain or loss ( S6B Fig ) . However , CtScnt7 comes almost entirely from CaChr7 , but has been heavily rearranged ( Fig 5 ) . The unusual preponderance of intra-chromosomal transposition and reversal compared to the smaller numbers of inter-chromosomal translocation may merit further study . In addition , a putative retrotransposon present at the centromere in C . tropicalis is found to be conserved at CEN7 in C . dubliniensis [16] ( S5B Fig ) . A similar retrotransposon was also found to be present within 50 kb region of CEN7 in C . albicans ( S6A Fig ) . This putative transposon is a member of the Ty3/Gypsy family but does not present at putative centromeres in any other Candida species . These results , together with the conservation in the CENP-A chromatin length , indicate that the centromere position of these related species was shared by a common ancestor and may have undergone chromosomal rearrangement involving the centromeres of more than one chromosome during evolution . The structural features of C . tropicalis centromeres strikingly resemble those of the distantly related fission yeast S . pombe . To understand the function of the underlying centromere DNA sequences in C . tropicalis , we engineered plasmids carrying either the full length centromere ( pCEN8 ) or a part of it ( pmid8 ) on a replicative plasmid pARS2 ( Fig 6A ) . The replicative plasmid pARS2 harbors CaARS2 [60] , which functions as an autonomously replicating sequence ( ARS ) on a circular plasmid in C . tropicalis ( S7 Fig ) . While the pmid8 plasmid conferred 10 to 13-fold increased mitotic stability as compared to pARS2 , inclusion of the full length centromere sequence harboring inverted repeats in the pARS2 plasmid ( pCEN8 ) resulted in a 37 to 42-fold higher mitotic stability after 10 generations of nonselective growth ( Fig 6B ) . A size-dependent stabilization of circular replicative plasmids has been reported previously in S . cerevisiae [61] . To rule out this possibility , we cloned a 10 kb of hererologous DNA sequence from bacteriophage λ ( pARS2-λ ) and measured the mitotic stability of the same . This plasmid , which is of similar length ( 15 kb ) to that of pCEN8 , did not show an increase in the mitotic stability as observed in pCEN8 ( Fig 6B ) . In addition , pCEN8 is 3 to 4-fold more stable mitotically than pmid8 carrying only the mid core sequence ( Fig 6B ) . These results suggest that the inverted repeats flanking the mid core can significantly improve the mitotic stability of an otherwise unstable replicative plasmid in C . tropicalis . Because CENP-A is known to bind to only functional centromeres , functionality of a centromere sequence cloned into the replicative plasmid was further assayed by the extent of CENP-A enrichment on these exogenously introduced plasmid DNA constructs . It should be noted that a unique SalI restriction site was introduced at the edge of the mid region of the plasmid-borne to differentiate it from the endogenous chromosomal ones ( see S8 Fig ) . CENP-A ChIP-qPCR analysis with plasmid specific primer-pair revealed that CENP-A is enriched at the mid core region on only the full length centromere DNA in pCEN8 ( Fig 6C ) suggesting that the inverted repeats ( LR and RR ) flanking the mid core are important for de novo CENP-A deposition . Thus , we conclude that the CENP-A recruitment process has been significantly rewired in closely related Candida species . Centromere function was shown to be dependent on the presence of inverted pericentric repeats in S . pombe as well [62] . On the other hand , Candida species and S . pombe shared a common ancestor more than 330 mya [63] . Thus , we demonstrate an extraordinary example of evolution of inverted repeat containing ‘fission yeast-like’ centromeres that appeared independently at least once in the Candida clade . In order to find out the role of pericentric inverted repeats and the DNA sequence associated with them for centromere function in C . tropicalis , we have constructed two different engineered plasmids namely pCEN801 and pCEN802 ( Fig 6A ) . The pCEN801 plasmid harbors the left repeat of CEN8 ( CtLR8 ) cloned in a direct orientation with respect to the right repeat of the same centromere ( CtRR8 ) . Thus , the only difference between pCEN8 ( inverted orientation ) and pCEN801 ( direct orientation ) is the orientation of pericentric repeats with respect to each other . However , pCEN801 is found to be significantly less stable mitotically as compared to the pCEN8 ( Fig 6B ) . Moreover , CENP-A ChIP-qPCR analysis revealed that CENP-A does not bind to this engineered pCEN801 plasmid ( Fig 6C ) . These suggest that the inverted orientation of pericentric repeats is an important structural feature for centromere function in C . tropicalis . To understand the function of the underlying DNA sequence of the inverted repeats , we cloned the inverted repeats of CEN5 ( CaIR5 ) from C . albicans into the pmid8 plasmid ( pCEN802 ) . However , the mitotic stability of pCEN802 is found to be 4 to 6-fold lower in C . tropicalis as compared to pCEN8 , which harbors pericentric inverted repeats ( IR8 ) of C . tropicalis ( Fig 6B ) . This observation has been further verified by CENP-A ChIP-qPCR analysis ( Fig 6C ) and confirms that the sequence of the inverted repeats per se is also crucial for centromere function in this species . Thus , we conclude that the DNA sequence of the repeats as well the arrangement of the repeats in an inverted fashion is both important for centromere function in C . tropicalis . To elucidate the route of centromere diversification , we reconstructed a phylogenetic tree of 13 species representing all major lineages of Ascomycota ( Fig 7A ) . It demarcates three distinct monophyletic subphyla within the Ascomycota—Taphrinomycotina , Pezizomycotina and Saccharomycotina ( Fig 7A ) . Moreover , this study also supports that Taphrinomycotina and Pezizomycotina are the early radiating branches in Ascomycetes . Thus , it is evident from both the phylogenetic relationship and the centromere structures of S . pombe and N . crassa that the invasion of transposons or symmetric repetitive elements shaped centromere structure in Taphrinomycotina and Pezizomycotina during an early era of ascomycete evolution ( Fig 7A ) . In contrast , a dramatic reduction in centromere length with a concurrent absence or loss of centromeric transposons or repeats , is evidenced from the centromeres of Candida and Saccharomyces species , and , therefore , evolved in Saccharomycotina ( Fig 7A ) . The identification of the centromere in C . tropicalis in this study is the first report that shows the evolution of repeat-associated centromeres in the clade of Saccharomycotina ( Fig 7A ) . In this study , we identified and analyzed the centromeres in C . tropicalis . We demonstrate that each centromere consists of a central non-repetitive mid core region , which is bound by evolutionarily conserved proteins from various layers of the kinetochore , and is flanked by inverted repeats . This is the first known saccharomycetous yeast in which all seven native centromeres are repeat-associated . Moreover , the inverted repeats of the same chromosome as well as across different chromosomes of C . tropicalis are highly similar in sequence . Taking together these centromere properties of C . tropicalis and those of other saccharomycetous yeasts , it is now evident that centromeres of all types—point centromeres with conserved motifs that are < 400 bp in length ( as in Saccharomyces cerevisiae ) , shorter non-repetitive regional centromeres with unique CENP-A-rich regions of 3 to 5 kb long ( as in C . albicans , C . dubliniensis and C . lusitaniae ) as well as repeat-associated regional centromeres of 10 to 11 kb ( as in C . tropicalis ) –evolved in Saccharomycotina ( Fig 7B ) . Although centromere structures are known in only a limited number of organisms , the discovery of all major types of centromeres in the saccharomycetes makes it a unique sub-phylum for tracing the path of evolution of monocentric chromosomes . The CENP-A-bound DNA sequence is the most preferred site of kinetochore assembly in an entire chromosome . In spite of sharing conserved motifs among centromeres , the CENP-A- bound DNA sequences are often variable , even in the genetically defined point centromeres of S . cerevisiae . Intriguingly , a comparative analysis between S . cerevisiae and its closest relative Saccharomyces paradoxus , identified that the CENP-A-bound CDE-II elements are the fastest evolving region of the genomes [64] . Similarly , in S . pombe flanking repeat sequences are conserved among the different chromosomes but the CENP-A-rich central core sequences are heterogeneous [65] . The most extreme cases of rapid divergence have been observed in the centromeres of C . albicans [15] , C . dubliniensis [16] , and C . lusitaniae [17] , where CENP-A-rich centromere DNA sequences are all unique and different in each species . In contrast , CENP-A is found to be enriched on highly homogenized arrays in most plants , mouse , and humans ( reviewed in [7] ) . Thus , homogenization of CENP-A-bound mid core regions in C . tropicalis , as observed in this study , provides a unique feature of yeast centromeres that is more reminiscent of metazoan centromeres . It has been proposed that transposable elements are a major source of centromeric satellite repeats , which gradually homogenized over time by an unknown mechanism in a metazoan system ( reviewed in [66] ) . We also observed a similar association of a retrotransposon in one centromere in C . tropicalis . More recently , it has been shown that the CENP-A-bound central core has a sequence feature enabling de novo recruitment of CENP-A molecules in S . pombe [67] . Thus , it will be intriguing to investigate a feature of CENP-A-enriched mid core regions in C . tropicalis that may facilitate CENP-A recruitment . Centromeres are known to be species-specific as centromeres of one organism do not function even in a related species [68] . Inter-species crosses , mostly in plants , suggest that functional incompatibility of centromeres is a frequent cause of uniparental genome elimination [69–71] . Recently , it has been reported that perturbation of the length of the CENP-A binding domain to adopt a uniform size is a prerequisite for a successful inter-species hybridization between maize and oat [69] . Thus , the length of the CENP-A-rich region at the centromere may be a key factor for centromere incompatibility in close relatives . In addition , the length of the CENP-A binding domain is found to be uniform in an organism regardless of the chromosome size or the nature of the centromere . Indeed , we observed that the length of the CENP-A binding region ( 3 to 5 kb ) is surprisingly conserved in related Candida species , in spite of the dramatic transition in the centromere organization . A uniform length of the CENP-A-bound regions in these related species may thus suggest a possible role in maintaining uniform kinetochore-microtubule interactions . This is further supported by the fact that the Dam1 complex is essential in C . tropicalis . Essentiality of the Dam1 complex has been previously correlated to a one microtubule-one kinetochore type of interaction as observed in S . cerevisiae and C . albicans [44 , 46] . Recently , it was proposed that DNA sequence repeats might have evolved to provide a ‘safety buffer’ against drifts in kinetochore position [72] . Interestingly , we found that the binding of kinetochore proteins is restricted to a non-repetitive mid core region in all cases in C . tropicalis and does not spread to the surrounding inverted repeats . CENP-A chromatin is generally repressive ( reviewed in [73] ) and thus the safety buffer provided by the pericentric inverted repeats perhaps act as a barrier to prevent the drift of kinetochore position and maintain the size of CENP-A binding domain in this organism . A series of growing lines of evidence suggest that fungal centromeres are rapidly evolving genomic loci ( reviewed in [2] ) . It has been proposed that rapid evolution of centromere DNA may contribute to its functional incompatibility and perhaps aids in speciation [1 , 18] . Speciation is , however , a poorly defined and less understood process in asexual organisms [74] . Some Candida species with known centromere structures ( C . albicans , C . dubliniensis and C . tropicalis ) are primarily parasexual and capable of mating but lack a recognized meiotic program . In spite of this , we observed in this study a high degree of divergence in the centromere DNA sequences as well as in the organization of centromere elements in these related Candida species . Why does the centromere structure diverge so rapidly in these related organisms ? It has been proposed that the loss of centromere function followed by the birth of a centromere in a new position can be viewed as a life cycle of a centromere that operates during evolution ( reviewed in [75] ) . For such an event , massive chromosomal rearrangements including the loss of an existing centromere would have to occur . Coincidentally , a comparative analysis among the relatives of both yeasts [76] and mammals [77] identified frequent breakpoints adjacent to centromeres . These results suggest that centromeres are among the most fragile sites in a genome . We also observed a gross chromosomal rearrangement between C . albicans and C . tropicalis specifically at the centromeres . It is also clear that the centromere loss or gain happened in these two organisms during their divergence from a common ancestor . Being both commensal and opportunistic pathogens , Candida species show considerable genome plasticity possibly as a means to survive in a hostile host environment . Genome rearrangements including karyotype changes , aneuploidy , and loss of heterozygosity have been frequently observed in clinical isolates of Candida species ( reviewed in [78] ) . Thus , it is likely that the evolutionary life cycle of a centromere may have contributed to their rapid divergence in these related pathogenic yeast species . Evolution is typically thought to proceed to generate diversity [79] . However , independent evolutionary origins of similar biological structures or functions in distantly related taxa challenge this common paradigm [80] . In this study , we observed that structural features of the C . tropicalis centromeres resemble a shorter version ( 10 to 11 kb ) of the distantly related S . pombe centromeres ( 40 to 110 kb ) [12 , 65] . However , the pericentric inverted repeats observed in C . tropicalis have no sequence identity to either the pericentric repeats of S . pombe or the centromere associated inverted repeats of C . albicans or C . dubliniensis . A notable difference between the centromeres of S . pombe and C . tropicalis is the absence of outer repeats ( otr in S . pombe ) in C . tropicalis . The otr is the site of small RNA ( siRNA ) generation and subsequently otr recruits other heterochromatin proteins ( such as Swi6 and Clr4 in S . pombe ) to make the centromeric region heterochromatic in S . pombe ( reviewed in [81] ) . Heterochromatin proteins and siRNAs play a vital role in centromere identity in this organism . Unlike S . pombe , C . tropicalis genome neither possesses the full RNAi machinery nor several key players required for heterochromatin formation such as an ortholog of Clr4 ( H3K9 methyltransferase ) [82] . Thus involvement of repeat elements in establishing RNAi-dependent H3K9me heterochromatin formation , as observed in S . pombe , is unlikely in C . tropicalis . In conclusion , we demonstrate for the first time the evolution of repeat-associated centromeres in an ascomycetous budding yeast ( Fig 7B ) . The most reasonable explanation for the appearance of the repeat-associated centromere structure is the contribution of repeats to de novo CENP-A deposition . CENP-A is a universal marker of functional centromeres and does not localize at inactivated centromeres . Studies on artificial CENP-A recruitment , either by direct tethering of CENP-A or its chaperone HJURP ( also known as Scm3 in yeasts ) to an ectopic locus [83 , 84] , suggest that de novo CENP-A deposition is in general one of the most significant rate limiting steps to the acquisition of centromere function . The process of CENP-A recruitment is known to be regulated by both genetic and epigenetic means ( reviewed in [2 , 29] ) . However , neither the DNA elements nor epigenetic factors are conserved across the kingdom implying an astounding flexibility in centromere specification . In this study , we demonstrate that a dramatic transition in centromere organization has rewired the genetic and epigenetic regulation of CENP-A deposition in related species . Thus , the ways in which the genetic and the epigenetic factors are co-evolving to orchestrate de novo CENP-A recruitment on a DNA sequence to establish a functional centromere may determine the shape of the centromere structure in an organism . C . tropicalis strains were grown either in YPDU ( 1% yeast extract/ 2% peptone/ 2% glucose/ 0 . 010% uracil ) , or in complete minimal ( CM ) media unless stated otherwise . C . tropicalis cells were transformed by the standard lithium acetate method as stated previously [45] . It is important to note that C . tropicalis requires uracil and not uridine in the medium to supplement the Ura auxotrophy . The centromeric histone H3 CENP-A homolog in C . tropicalis [85] , was identified in a BLAST analysis using C . albicans CENP-A ( CaCse4 ) as the query sequence against the Candida tropicalis genome [43] . The BLAST analysis revealed that the proteins with high scores ( score >213 ) were the putative CENP-A homologue , CtCse4 ( CTRG_02639 . 3 ) , and histone H3 proteins ( CTRG_04732 . 3 , CTRG_00676 . 3 and CTRG_05645 . 3 ) . The CtCse4 ( Scnt 3: 1334129–1334845 ) is a 238-aa-long protein that shows 90% homology with the C-terminal histone fold domain of CaCse4 ( S1A Fig ) . Similarly , CENP-C ( Mif2 ) , Nuf2 , and Dad1 homologs of C . tropicalis were identified in a BLAST analysis . The CtMif2 ( CTRG_05763 . 3 ) is a 523-aa-long protein ( Scnt 9: 474053–475624+ ) with a conserved CENP-C box , which is identical in sequence between the CaMif2 and CtMif2 ( S1A Fig ) . CtNUF2 ( CTRG_05381 . 3 ) and CtDAD1 ( CTRG_03625 . 3 ) encode 492-aa- and 99-aa-long proteins respectively . Both of these proteins show a high degree of sequence conservation in comparison to those of C . albicans ( S1A Fig ) . The sequence upstream of the GAL1 gene in S . cerevisiae , harboring the upstream activation sequence ( UAS ) , is used as the GAL1 promoter to regulate the expression of desired genes [86 , 87] . However , no such regulatable promoter has been identified previously in C . tropicalis to control the expression level and study the essentiality of proteins . The C . tropicalis homolog of GAL1 was identified as the ORF ( CTRG_04617 ) by BLAST using S . cerevisiae GAL1 as the query sequence . Further , on analyzing the genomic location of this gene , we found that the synteny of GAL1 and GAL10 genes was maintained as observed in S . cerevisiae . The primer sequences and all C . tropicalis strains used in this study are listed in S4 and S5 Tables respectively . The detailed information about the strain construction is available in the S1 Text . Cells of C . tropicalis strains expressing GFP tagged kinetochore proteins were grown overnight , harvested , and washed twice with sterile distilled water . Cells were then resuspended into sterile distilled water to obtain the desired density before taking the images with a Delta Vision Microscopy Imaging system . Indirect immunofluorescence was done as described before [45] . Asynchronously grown C . tropicalis cells were fixed with a 1/10th volume of formaldehyde ( 37% ) for 1 h at room temperature . Antibodies used were diluted as follows: 1:500 for rabbit anti-Cse4 antibodies [45] and 1:30 for rat anti-tubulin antibodies ( Abcam , Cat No . ab6161 ) . The dilutions for secondary antibodies used were Alexa flour 568 goat anti-rabbit IgG ( Invitrogen , Cat No . A11011 ) 1:500 and Alexa fluor 488 goat anti-rat IgG ( Invitrogen , Cat No . A11006 ) 1:500 . DAPI ( 4 , 6-Diamino-2-phenylindole ) ( D9542 Sigma ) was used to stain the nuclei of the cells . Cells were examined under 100 ( multi ) magnifications using a confocal laser scanning microscope ( LSM 510 META , Carl Zeiss ) . The digital images were processed with Adobe Photoshop . C . tropicalis cells were harvested at two different time points and processed as described before [45] . Prior to injection of the sample into the flow cytometer , the cell suspension was sonicated briefly ( 30% amplitude , 7s pulse ) . The sonicated samples were diluted to a desired cell density in 1X PBS and injected into the flow cytometer ( BD FACSCalibur ) for analysis . The output was analyzed using the BD CellQuestPro software . The conditional mutant strains of C . tropicalis grown in both permissive and non-permissive media were harvested , washed , and resuspended in 300 μl of sterile distilled water . These cells were fixed by adding 700 μl absolute ethanol and incubated at room temperature for 1 h . After fixing , the cells were washed with 1ml of sterile distilled water twice and resuspended in sterile distilled water to obtain desired cell density prior to imaging . To 5 μl cell suspension , 3 μl DAPI ( 100 ng/ml ) was added in the well , mixed gently by pipetting , and the cover slip was then placed . After 5 min of incubation , the cells were imaged using a fluorescence microscope ( Olympus BX51 ) under 100 ( multi ) magnifications . C . tropicalis strains were grown overnight in YPDU and cells were harvested . The harvested cells were washed with lysis buffer ( 0 . 2 M Tris , 1 mM EDTA , 0 . 39 M ammonium sulphate , 4 . 9 mM magnesium sulphate , 20% glycerol , 0 . 95% acetic acid , pH 7 . 8 ) and resuspended in 0 . 5 ml of the same buffer . The cells were disrupted using acid-washed glass beads ( Sigma , Cat . No . G8772 ) by vortexing 5 min ( 1 min vortexing followed by 1 min cooling on ice ) at 4°C . C . tropicalis cell lysates were electrophoresed on a 12% SDS-PAGE gel and blotted onto a nitrocellulose membrane in a semi-dry apparatus ( Bio-Rad ) . The blotted membranes were blocked with 5% skim milk containing 1X PBS ( pH 7 . 4 ) for 1 h at room temperature and were then incubated with following dilutions of primary antibodies: anti-Cse4 antibodies [45] 1:500; anti-H3 antibodies [Abcam , Cat No . ab1791] 1:2500; for 1 h at room temperature . Next , the membranes were washed three times with PBST ( 0 . 1% Tween-20 in 1X PBS ) solution . Anti-rabbit HRP conjugated antibodies [Bangalore Genei , Cat No . 105499] in 1:1000 dilutions were added and incubated for 1 h at room temperature followed by three to four washes with the PBST solution . Signals were detected using the chemiluminescence method ( SuperSignal West Pico Chemiluminescent substrate , Thermo scientific , Cat No . 34080 ) . The ChIP assays were done as described previously [15] . Briefly , each strain was grown until exponential phase ( ~2×107 cells/ml ) and cells were cross-linked with formaldehyde ( final concentration 1% ) . Chromatin was isolated and sonicated to yield an average fragment size of 300–500 bp . Then the DNA was immunoprecipitated with anti-Cse4 antibodies [45] ( final concentration is 6 μg/ml ) or anti-protein A antibodies ( final concentration is 24 μg/ml ) or anti-V5 antibodies ( Life Technologies , Cat No . R960-25 ) ( final concentration is 0 . 94μl/ml ) and purified . The duration of cross-linking varies—15 min for CENP-A , 20 min for CENP-C , 1 h 45 min for Nuf2 and 3 h 15 min for Dad1 . The total , immunoprecipitated ( IP ) DNA , and beads only material were used to determine the binding of kinetochore proteins in all seven putative centromeres by semi-quantitative PCR . PCR conditions for primers ( as listed in S5 Table ) were used as follows: 94°C for 2 min , Tm for 30 s ( Tm varies with the primers ) , 72°C for 1 min , for 1 cycle; 94°C for 30 s , Tm for 30 s , 72°C for 1 min for 24 cycles in case of CENP-A and CENP-C; and 27 cycles for Nuf2 and Dad1; 72°C for 10 min . ChIP-seq analyses were conducted as described previously [23] . The detailed procedure of ChIP-seq and analysis are provided in the S1 Text . C . tropicalis strain MYA-3404 was grown until exponential phase ( ~2×107 cells/ml ) . Cells were washed with 50 mM EDTA and counted with a hemocytometer . Approximately 6×108 cells were used for the preparation of 1 ml genomic DNA plugs . The plugs were made according to the instruction manual protocol ( BioRad , Cat No . 170–3593 ) with cleancut agarose ( 0 . 6% ) and the lyticase enzyme provided by the kit . A 0 . 6% pulsed field certified agarose gel was prepared using 0 . 5X TBE buffer ( 0 . 1 M Tris , 0 . 09 M boric acid , 0 . 01 M EDTA , pH 8 ) and the PFGE was performed on a CHEF-DR II ( Bio-Rad ) for 72 h ( 24 h at 4 . 5 V/cm/106° with an initial and final switch times 200 s; 48 h at 3 V/cm/106° with an initial and final switch time 700 s ) . The gel was stained with ethidium bromide ( EtBr ) and analyzed by using the Quantity One software ( Bio-Rad ) . To determine the extent of binding of kinetochore proteins on the centromere of Scnt 8 , real time PCR ( qPCR ) was performed . The template used was as follows: 1 μl of 1:100 dilutions for input and 1 μl of 1:5 dilutions for IP . The conditions used in qPCR were as follows: 94°C for 2 min; 94°C for 30 s , Tm for 30 s ( Tm varies with the primers ) , 72°C for 45 s for 30 cycles . The results were plotted on a graph according to the percentage input method using the formula: 100*2^ ( adjusted Ct input−adjusted Ct of IP ) . Here , the adjusted value is the dilution factor ( log2 of dilution factor ) subtracted from the Ct value of diluted input or IP [88] . Similar conditions were used to determine the enrichment of CENP-A proteins on the centromeric plasmids . To determine conservation rates for inverted repeats ( IRs ) within and across centromeres , and mid regions across different centromeres , we used Sigma version 2 [89] , a program that aims to minimize spurious alignments by using a stringent p-value for all local alignments , and uses a background model with correlations and an evolutionary model to link sequences . The background model and substitution matrix were drawn from S . cerevisiae and close relatives , and are not expected to vary significantly across Saccharomycetes . The branch lengths were determined dynamically . The conservation rates in Fig 4C were determined from these alignments using custom python scripts . The visual representation of the alignments as shown in S5A , S5C and S5D Fig was created with an in-house program . The dotplot in S5E Fig was created with dotmatcher , from EMBOSS 6 . 3 . 1 [90] . Additionally , the inverted repeats and mid regions were scanned for tandem repeats using the Tandem Repeats Finder version 4 . 04 [91] . The parameters used were “filename 2 5 5 80 10 2 2000” ( maximum period size 2000 ) . The results are summarized in S3 Table . For the synteny analysis as in Fig 5 , orthology information was obtained from the Fungal Orthogroups Repository ( http://www . broadinstitute . org/regev/orthogroups ) [92] . Genes in each species within 100 kb of each centromere were examined , and orthologous genes were plotted using an in-house program . Approximately 1 μg of DNA of both pARS2 and the control parental ( pUC19-CaURA3 ) plasmids were used to transform CtKS04 strain using both the lithium acetate and the spheroplast transformation methods as stated before [93] . After transformation , the cells were plated on the complete media lacking uracil ( CM-Ura ) and incubated at 30°C for 3 to 5 days before taking photographs . The ARS activity of pARS2 was determined as the transformation efficiency ( i . e . , the number of transformants/ μg of DNA ) . Each transformation was performed at least 3 times . The mitotic stability assay was performed to determine the loss rate of pARS2 , pmid8 , pCEN8 , pARS2-λ , pCEN801 and pCEN802 in C . tropicalis . Briefly , the C . tropicalis strain , CtKS102 transformed with above mentioned plasmids were streaked on CM-Ura plates for single colonies . Single colonies thus obtained were subsequently inoculated in a nonselective media ( YPDU ) and incubated at 30°C for overnight for at least 10 generations . Next day , equal numbers of cells were simultaneously plated on YPDU and CM-Ura and incubated at 30°C for 2 days . Colonies grown on both plates were counted and the mitotic stability was calculated in percentage as follows: Mitotic stability = ( S/NS ) , where S and NS denote the number of colonies grown on selective and nonselective media respectively . A phylogenetic tree with estimated geological time was created via a multiple alignment of 573 gene orthologue sets in 13 sequenced species of Ascomycetous fungi ( as shown in Fig 7A ) –namely , C . tropicalis , S . cerevisiae , C . glabrata , K . lactis , A . gossypii , N . casetelli , C . dubliniensis , C . albicans , C . lusitaniae , D . hansenii , C . guilliermondii , Y . lipolytica , N . crassa , A . nidulans , S . japonicus , S . octosporus , S . pombe . The orthologous genes were identified using the Fungal Orthogroups Repository ( http://www . broadinstitute . org/regev/orthogroups/ ) [92] , except in the case of C . dubliniensis for which orthologues to C . albicans were used as annotated in the gene sequences from the Candida Genome Database ( http://www . candidagenome . org/ ) . Only genes for which there were unique reciprocal orthologues between S . cerevisiae and each of the 13 other species , and which lacked introns ( or from which we could easily remove introns ) were considered . To remove bias from outliers , the orthologous genes in all species were further sub-selected for genes that evolve uniformly . For this , the average rates of synonymous ( ds ) and non-synonymous ( dn ) substitution were calculated separately from codon-level alignments . Only genes whose ds and dn both fell within 1 . 5 standard deviations of the mean for the full set were considered . This yielded a list of 573 genes . These coding DNA sequences were aligned at the codon level with FSA [94] ( command line option “—translated” ) , concatenated with gaps removed , and a tree was generated with codonphyml [95] ( command line “-d codon -q” ) . Since the quantity of sequence was very large ( nearly 10 Mbp , or over 0 . 5 Mbp per species ) bootstrapping was not done .
Centromeres aid in high fidelity chromosome segregation . Paradoxically , centromere DNA sequences are rapidly evolving in fungi , plants , and animals . Centromere DNA sequences in fungi can be unique in each chromosome or share conserved features such as motifs for sequence specific protein binding , pericentric repeats , or transposon-rich elements . Ascomycetous fungi , in particular , show a wide range of diversity in centromere sequence elements . However , no ascomycetous budding yeast species is known to possess repeat-associated centromeres in all of its chromosomes . Here , we identified and mapped all seven centromeres in an ascomycete , a rapidly emerging human pathogenic yeast , Candida tropicalis . The repeat-associated centromeres of highly homogeneous DNA sequences in C . tropicalis are significantly diverged from the mostly non-repetitive unique centromeric DNA sequences of its closely related sequenced species , Candida albicans , Candida dubliniensis and Candida lusitaniae . Structurally , the centromeres of C . tropicalis more closely resemble those of the distantly related fission yeast Schizosaccharomyces pombe . Thus , we discover rapidly diverging repeat-associated centromeres in an ascomycetous budding yeast and provide evidence of emergence of repeat-associated centromeres via two independent evolutionary events in ascomycetous fungi .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "sequencing", "techniques", "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "chromosome", "structure", "and", "function", "centromeres", "pathogens", "microbiology", "fungi", "model", "organisms", "molecular", "biology", "techniques", "fungal", "pathogens", "schizosaccharomyces", "research", "and", "analysis", "methods", "sequence", "analysis", "mycology", "sequence", "alignment", "chromosome", "biology", "medical", "microbiology", "microbial", "pathogens", "schizosaccharomyces", "pombe", "repeated", "sequences", "molecular", "biology", "yeast", "candida", "dna", "sequence", "analysis", "chromosomes", "cell", "biology", "genetics", "biology", "and", "life", "sciences", "yeast", "and", "fungal", "models", "genomics", "organisms", "candida", "albicans" ]
2016
Repeat-Associated Fission Yeast-Like Regional Centromeres in the Ascomycetous Budding Yeast Candida tropicalis
Genome wide association studies ( GWAS ) for fasting glucose ( FG ) and insulin ( FI ) have identified common variant signals which explain 4 . 8% and 1 . 2% of trait variance , respectively . It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance . To test this , we analyzed exome-array data from up to 33 , 231 non-diabetic individuals of European ancestry . We found exome-wide significant ( P<5×10-7 ) evidence for two loci not previously highlighted by common variant GWAS: GLP1R ( p . Ala316Thr , minor allele frequency ( MAF ) =1 . 5% ) influencing FG levels , and URB2 ( p . Glu594Val , MAF = 0 . 1% ) influencing FI levels . Coding variant associations can highlight potential effector genes at ( non-coding ) GWAS signals . At the G6PC2/ABCB11 locus , we identified multiple coding variants in G6PC2 ( p . Val219Leu , p . His177Tyr , and p . Tyr207Ser ) influencing FG levels , conditionally independent of each other and the non-coding GWAS signal . In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation , establishing G6PC2 as an effector gene at this locus . Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered . In contrast to earlier reports suggesting that , paradoxically , glucose-raising alleles at this locus are protective against type 2 diabetes ( T2D ) , the p . Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk . Coding variant associations for glycemic traits in GWAS signals highlight PCSK1 , RREB1 , and ZHX3 as likely effector transcripts . These coding variant association signals do not have a major impact on the trait variance explained , but they do provide valuable biological insights . Large-scale GWAS of non-diabetic individuals have successfully identified > 60 loci associated with FG and FI levels , many of which are also implicated in susceptibility to T2D [1 , 2 , 3 , 4] . Despite these successes , lead SNPs at GWAS loci have modest effects and cumulatively explain only a small proportion of the trait variance in non-diabetic individuals . By design , GWAS have focused predominantly on the interrogation of common variants , defined here to have MAF > 5% . Most of the identified variants are non-coding , complicating attempts to establish the molecular consequences of these GWAS loci . We therefore chose to extend discovery efforts to coding variants , particularly those of lower frequency that have not been well captured by GWAS genotyping and imputation . We aimed both to identify novel coding loci for FG and FI , and to evaluate the role of coding variants at known GWAS loci , thereby expecting to highlight causal transcripts and to facilitate characterization of the molecular mechanisms influencing glycemic traits and T2D susceptibility . Through single-variant analysis , we identified 12 coding variants ( all of which were non-synonymous changes ) associated with FG levels at exome-wide significance , two low-frequency and ten common ( S3 Table ) . These variants mapped to seven loci , six of them previously implicated in FG regulation . The signals at known loci included previously-reported common coding variants driving GWAS signals at GCKR ( p . Pro446Leu , MAF = 36 . 9% , P = 5 . 3×10−18 ) and SLC30A8 ( p . Arg325Trp , MAF = 35 . 7% , P = 2 . 5×10−10 ) [2 , 11] . Three additional common coding variants associated with FG ( in C2orf16 , GPN1 , and SLC5A6 ) were in moderate linkage disequilibrium ( LD; r2 = 0 . 2–0 . 4 ) with the p . Pro446Leu GCKR variant . Their associations were eliminated after conditioning on p . Pro446Leu , the known functional GWAS variant in this region [12 , 13] , indicating no causal role for these additional variants on FG regulation ( S3 Table ) . The sixth variant influencing FG levels at exome-wide significance was a low-frequency non-synonymous change which did not map to any previously known FG-influencing locus: p . Ala316Thr at GLP1R ( MAF = 1 . 5% , P = 4 . 6×10−7; Table 1 and S1B Fig . ) . This variant showed modest association ( P = 1 . 3×10−4 ) in a previous GWAS meta-analysis of FG [3] , which partially overlaps with the present study , but now achieves exome-wide significance . The alanine residue at p . Ala316Thr is conserved across vertebrates , and the threonine substitution is predicted to be “possibly damaging” by in silico mutation analysis ( S4 Table ) . GLP-1R ( glucagon-like peptide 1 receptor ) is the receptor for the incretin hormone glucagon-like peptide 1 ( GLP1 ) , which is released from enteroendocrine cells after food ingestion and potentiates insulin secretion . GLP1 receptor agonists are an established treatment for T2D [14] . The six remaining coding variants all map to known FG-associated GWAS loci , but have not previously been implicated as playing a causal role . These include two variants in the islet-specific glucose-6-phosphatase catalytic subunit ( G6PC2 ) gene at the G6PC2/ABCB11 locus: p . Val219Leu , a common variant ( P = 6 . 0×10−9 , MAF = 48 . 1% ) , and p . His177Tyr , a low-frequency variant ( P = 3 . 1×10−8 , MAF = 0 . 8%; S2A Fig . ) . These variants remained significantly associated ( p . Val219Leu , Pconditional = 7 . 1×10−10 and p . His177Tyr , Pconditional = 1 . 3×10−11 ) with FG after conditioning on the intronic lead GWAS SNP , rs560887 ( Table 1 and S2B Fig . ) . Conversely , conditioning on the coding variants did not completely abolish the association signal at the lead GWAS SNP ( Punconditional = 6 . 4×10−78; Pconditional onHis177Tyr = 3 . 1×10−55 , Pconditional onVal219Leu = 1 . 2×10−58 , and Pconditional onHis177Tyr and Val219Leu = 2 . 1×10−83 ) , confirming that the effect of the coding variants were largely independent of the lead GWAS SNP . Furthermore , the coding variants each remained associated with FG at exome-wide significance even after conditioning on both the lead GWAS SNP and the other coding variant , providing clear evidence of at least three association signals at this locus ( Table 1 and S2C-S2D Fig . ) . These results are consistent with a recent study in Finnish individuals that reported a FG association signal at p . His177Tyr [15] , but we extend that finding by demonstrating exome-wide significant association of multiple coding variants after conditioning on other associated variants in the region . G6PC2 was also the only one of the 14 , 465 genes with multiple exome-array variants to demonstrate evidence of significant association with FG levels with any mask in gene-based tests ( Table 2 ) . In fact , for this gene we observed significant association with FG levels for all the masks encompassing multiple variants . These gene-based associations remained significant even after Bonferroni correction for testing of four different variant masks . Step-wise conditional analyses , adjusting for each variant included in the respective masks , revealed that the gene-based signals were primarily driven by two variants: p . His177Tyr and p . Tyr207Ser ( S5 Table ) . The protein-truncating variant ( PTV ) p . Arg283* , which introduces a stop mutation in the last exon of the gene , showed no association with FG levels in single-variant or gene-based analyses . The most likely explanation is that this variant evades nonsense mediated decay ( as is usual for PTV in the last exon ) and that the truncated protein ( missing only the terminal 72 amino acid residues ) retains normal functional activity [16] . Due to its high allele frequency , and annotation as benign across multiple annotation algorithms , p . Val219Leu was not included in any of the gene-based variant masks ( S6 Table ) . However , based on the single-variant it also has independent effects , with the result that we have three coding variants in G6PC2 ( p . His177Tyr , p . Tyr207Ser , and p . Val219Leu ) influencing FG levels . These three variants explain an additional 0 . 2% of the phenotypic variance in FG beyond that explained by the GWAS variant rs560887 , bringing the total variance explained by this locus to 1 . 1% . However , we recognize that this estimate has been obtained in the discovery cohort and consequently might be inflated . Both G6PC2 and ABCB11 have been considered strong biological candidate genes for glucose regulation , and advocated as potential effector transcripts at this GWAS locus [17 , 18] . However , none of the 21 coding variants in ABCB11 that passed quality control ( twelve rare , eight low-frequency , and one common ) were significantly associated with FG levels , nor was there an aggregate association signal ( P>0 . 05 ) . Together , our genetic data provide compelling evidence that G6PC2 is an effector gene for FG regulation at this GWAS locus , with p . His177Tyr , p . Tyr207Ser , and p . Val219Leu as likely causal coding variants . The phenotypic impact of these coding variants might , we reasoned , be influenced by the action of the non-coding GWAS variants on G6PC2 transcript regulation . Haplotype analysis of the four variants ( rs560887 , p . His177Tyr , p . Tyr207Ser , and p . Val219Leu ) in a subset of 4 , 442 individuals revealed that the C allele encoding Leu219 was carried exclusively in cis with the glucose-raising allele at the GWAS SNP ( Fig . 1 ) . The estimated effect size of p . Val219Leu was considerably smaller ( β^ =0 . 020 ± 0 . 004 mmol/L per allele ) than rs560887 ( β^ =0 . 070 ± 0 . 004 mmol/L per allele ) . These observations together explain the reversal in direction of effect of the Leu219 allele between conditional and unconditional analyses and indicate that , whilst Leu219 appears to have a glucose-raising effect in single-variant analyses , the molecular consequence of Leu219 is likely to be to lower glucose ( Table 1 ) . The minor alleles of the other two coding variants ( p . His177Tyr , p . Tyr207Ser ) also displayed glucose-lowering effects in conditional analyses . Given the role of G6PC2 in beta-cells we predicted that these would also be associated with reduced G6PC2 function , a hypothesis that we set out to test with a series of in vitro studies . First , we generated recombinant FLAG-tagged G6PC2 constructs to investigate the impact of these variants on protein expression and subsequent cellular localization . Transient transfection of all three constructs showed a marked reduction in G6PC2 protein levels . In HEK293 cells , protein levels were decreased by 99% ( p . His177Tyr ) , 100% ( p . Tyr207Ser ) , and 49% ( p . Val219Leu ) , when compared to wild type ( defined for this study as the major allele for each of these variants ) G6PC2 ( Fig . 2A ) . Reduced protein expression was also confirmed in the rat pancreatic β-cell line INS-1E ( 76% , 97% , and 49% reduction , respectively; Fig . 2B ) . The functional impact of the variant proteins mirrored our genetic observations; the variant protein with the p . Val219Leu substitution , which has only a modest effect on FG , was present at higher levels in both HEK293 and INS-1E cells than the p . His177Tyr and p . Tyr207Ser proteins , both of which have larger impacts on FG levels . Our functional results for p . His177Tyr and p . Tyr207Ser are concordant with data from the in silico mutation assessment tools SIFT and PolyPhen-2 , which predicted these variants as deleterious ( S4 Table ) . In contrast , the common p . Val219Leu variant was predicted to be benign , whereas in vitro characterization clearly shows a significant reduction in protein expression , demonstrating the importance of experimentally evaluating coding variants for functional consequences . The observed decrease in G6PC2 protein levels caused by the FG-associated variants is also directionally consistent with the evidence indicating that the non-coding GWAS SNP rs560887 may have effects on pre-mRNA splicing [19] . Next , we used specific inhibitors of the proteasomal and lysosomal pathways ( MG-132 and chloroquine , respectively ) to demonstrate that the three G6PC2 variant proteins with p . His177Tyr , p . Tyr207Ser , and p . Val219Leu substitutions were predominantly degraded through the ubiquitin-proteasome pathway , an important cellular mechanism for clearing misfolded proteins . Protein expression could be rescued in the presence of MG-132 but not chloroquine ( Fig . 2C ) . We also evaluated the impact of the variants on cellular localization of G6PC2 to the endoplasmic reticulum ( ER ) using calnexin as an ER marker . The variant proteins displayed similar localization patterns to wild type G6PC2 ( Fig . 2D ) . Our finding that loss of G6PC2 function leads to a reduction in FG levels in humans is consistent with rodent data , which show that G6pc2 knockout mice have a ~15% decrease in FG levels [20] . Hence , our data , linking genetic associations with reduced protein function , indicate that normal G6PC2 function is critical for glucose homeostasis and that these variants most likely impact FG levels through altered intracellular catalysis of glucose-6-phosphate to glucose and inorganic phosphate in pancreatic β-cells . We evaluated the impact of these functional G6PC2 variants on other related quantitative traits and disease outcomes to gain further insights into the metabolic processes involved ( S7 Table ) . None of the variants showed any evidence of association with FI levels ( P>0 . 1 ) in 30 , 825 non-diabetic individuals analyzed in the present study . No association of the lead G6PC2 GWAS variant with T2D risk has previously been shown in Europeans [2 , 21 , 22] . However , in a meta-analysis of exome-array data from 28 , 344 T2D cases and 51 , 801 controls of European ancestry ( including the 33 , 231 controls used in the present meta-analyses ) , the common coding variant , p . Val219Leu , showed modest association with T2D risk ( P = 0 . 0011; odds ratio = 1 . 05 , 95% confidence interval 1 . 02–1 . 06 ) . The G allele encoding Val219 , which displayed a glucose-raising effect , conferred an increased risk of disease . In contrast to the observations in FG single-variant analysis , the direction of effect on T2D at this variant was unchanged , even after conditioning on the GWAS variant . This is consistent with a small case-control study in 3 , 676 individuals of Chinese ancestry where a nominal association ( P = 0 . 0062 ) with T2D risk was reported [23] . Our finding provides evidence that G6PC2 is critical not only for controlling FG levels in the physiological range , but that impairment of its function contributes to T2D pathogenesis . The effect on T2D risk is modest given the impact of the p . Val219Leu variant on FG levels but the effect size is similar to that reported for the common non-coding variant GWAS signal at GCK [2] . GCK encodes the glycolytic enzyme glucokinase which catalyzes the reverse reaction to G6PC2 . These observations are consistent with defects in glucose sensing rather than β-cell function . Of the 12 coding variants significantly influencing FG levels , we have discussed eight above . The four remaining signals mapped to three additional established FG-associated GWAS regions and support the candidacy of particular effector transcripts at these loci . Two map to PCSK1 ( p . Gln665Glu , MAF = 27 . 9% , P = 3 . 0×10−8; p . Ser690Thr , MAF = 27 . 9% , P = 4 . 1×10−8 ) , and have previously been proposed as likely causal variants at this GWAS locus because of strong LD with the lead non-coding GWAS SNP ( rs4869272 ) in Europeans ( r2 = 0 . 81 ) [3] . These two variants are in complete LD with each other ( r2 = 1 ) and both have residual association signals after adjusting for the lead GWAS SNP ( p . Gln665Glu , Pconditional = 8 . 1×10−3; p . Ser690Thr , Pconditional = 0 . 01 ) ( Table 1 and S3 Table ) . Conversely , conditioning on the coding variants completely abolished the association signal at the GWAS SNP ( Punconditional = 7 . 2×10−7; Pconditional onGln665Glu = 0 . 24 , Pconditional onSer690Thr = 0 . 25 , and Pconditional onGln665Glu and Ser690Thr = 0 . 34 ) . Although we were unable to statistically distinguish between these two coding variants , there is suggestive in vitro evidence that the p . Gln665Glu variant may decrease PCSK1 activity whilst p . Ser690Thr behaved as wild-type [24] , supporting the former as the most likely causal variant at the PCSK1 locus . PCSK1 encodes prohormone convertase 1/3 ( PC1/3 ) , a calcium-dependent serine endoprotease , which is essential for the conversion of a variety of prohormones , including proinsulin and proglucagon , to their bioactive forms . The penultimate variant was in ZHX3 ( p . Asn310Ser , MAF = 23 . 8% , P = 3 . 9×10−7 ) which maps to the TOP1 GWAS locus influencing FG levels [4] . Adjustment for p . Asn310Ser in a conditional analysis eliminated the association signal at the non-coding GWAS lead SNP rs6072275 ( Punconditional = 2 . 5×10−5 and Pconditional = 0 . 33 ) , supporting ZHX3 as the plausible causal gene at this locus ( Table 1 and S3 Table ) . ZHX3 ( zinc fingers and homeoboxes 3 ) encodes a transcriptional repressor which belongs to a protein family known to regulate gene expression in the kidney podocytes and plays roles in both lipoprotein metabolism and triglyceride regulation in mice [25 , 26] . The final variant was in RREB1 ( p . Ser1554Tyr , MAF = 21 . 1% , P = 8 . 4×10−9 ) which resides in the RREB1/SSR1 GWAS locus influencing FG levels [4] and T2D risk [27] ( Table 1 ) . We were unable to explore the relationship between this association signal and the lead FG ( rs17762454 ) or T2D ( rs9502570 ) GWAS SNPs at this locus as neither the variants themselves , nor a close proxy ( r2>0 . 80 ) , was present on the exome-array . Based on European haplotypes from the 1000 Genomes Project , the coding variant was more strongly correlated ( r2 = 0 . 59 ) with rs9502570 as compared to rs17762454 ( r2 = 0 . 08 ) , which might indicate multiple FG association signals in this region . These data point to a likely functional role for RREB1 at this locus , although further studies are needed to confirm this hypothesis . Turning to the analysis of FI , we identified six non-synonymous variants associated at exome-wide significance ( one rare and five common ) . These mapped to four loci , three of them previously implicated in FI regulation ( S3 Table ) . The single novel FI- influencing locus was represented by a rare variant in URB2 ( p . Glu594Val , MAF = 0 . 1% , P = 3 . 1×10−7; Table 1 and S1 Fig . ) . The variant allele was observed in individuals across Europe , including UK , Denmark , Finland , and Sweden , and genotype calls across all cohorts passed visual inspection for clustering accuracy . Heterozygous genotypes ( n = 6 ) were 100% concordant for 3 , 999 individuals genotyped on the array that had also been exome sequenced ( S8 Table ) . This variant has a relatively large effect , with each copy of the minor allele increasing FI level by 32% . URB2 encodes ribosome biogenesis 2 homolog , which interacts with nuclear lamins [28] . The precise mechanistic role of URB2 is still poorly understood , but conditions caused by defects in lamin genes ( laminopathies ) , including familial partial lipodystrophy , can cause loss of adipose tissue , insulin resistance , and metabolic syndrome [29 , 30] . The remaining five coding variants implicated in the FI analysis , included three previously-reported FI-associated common variants in GCKR ( p . Pro446Leu , P = 8 . 1×10−11 ) , PPARG ( p . Pro12Ala , MAF = 14 . 7% , P = 1 . 3×10−7 ) , and COBLL1 ( p . Asn939Asp , MAF = 11 . 3% , P = 6 . 7×10−8 ) [3 , 4] . The final two variants ( in C2orf16 and GPN1 ) also mapped within the GCKR FG/FI-associated GWAS locus , and their associations were eliminated after conditioning on the GCKR p . Pro446Leu variant as seen in FG analysis ( S3 Table ) . Summary statistics of single-variant and gene-based analyses are available at http://www . diagram-consortium . org/Mahajan_2014_ExomeChip/ All human research was approved by the relevant institutional review boards , and conducted according to the Declaration of Helsinki and all patients provided written informed consent . FIN-D2D 2007 , DPS , DR’s EXTRA , FINRISK 2007 , FUSION , and METSIM were approved by the University of Michigan Health Sciences and Behavioral Sciences Institutional Review Board ( ID: H03-00001613-R2 ) . The Danish studies ( Health 2006 , Inter99 , and Vejle Biobank ) were approved by the local Ethical Committees of Capital Region ( approval # H-3-2012-155 , KA 98155 and KA-20060011 ) and Region of Southern Denmark ( approval # S-20080097 ) . The GoDARTS study was approved by EoS REC 09/S1402/44 . The Twins UK study was approved by EC04/015 . The OBB study was a approved by South Central , Oxford C , 08/H0606/107+5 , IRAS project 136602 . The PIVUS study is approved by 00–419 and ULSAM study by 251/90 and 2007/338 . The PPP study was approved by the Committee On the Use of Humans as Experimental Subjects at MIT ( IRB 0912003615 ) . Study participants . FG was measured in mmol/L and FI in pmol/L . Individuals were excluded from the analysis if they had a physician diagnosis of diabetes , were on diabetes treatment ( oral or insulin ) , or had a fasting plasma glucose concentration ≥7 mmol/L or ≥11 . 1 mmol/L following a 2-hour oral glucose tolerance test . Individual studies applied further sample exclusions , including for pregnancy , non­fasting measurements , and type 1 diabetes ( S1 Table ) . Measures of fasting glucose made in whole blood were corrected to approximate plasma level by multiplying by 1 . 13 [35] . Trait transformations and adjustment . To achieve approximate normality of the traits within each study , FG and natural logarithm–transformed FI levels were adjusted for age , sex , BMI , and study specific covariates followed by inverse normalization of the residuals . Inverse normalized residuals were used as the dependent quantitative trait in genetic association models to calibrate type 1 error . Effect estimates were obtained using untransformed FG and natural logarithm–transformed FI levels after adjusting for age , sex , BMI , and study specific covariates . The Illumina HumanExome Beadchip array was genotyped by individual studies . This custom array was designed to facilitate large-scale genotyping of 247 , 870 mostly rare ( MAF<0 . 5% ) and low-frequency ( MAF 0 . 5–5% ) protein altering variants selected from sequenced exomes and genomes of ~12 , 000 individuals ( see URLs ) . Details of genotype calling and quality control are presented in S1 Table . To confirm the genotyping quality of all the variants discussed in the manuscript , we compared the genotype calls in 2 , 312 to 4 , 000 individuals for which we have both exome-array genotypes and exome-sequence data ( S8 Table ) . The results are highly concordant for all variants ( 99% heterozygous genotype concordance and 100% concordance observed for non-reference homozygotes ) . Call rate and Hardy-Weinberg equilibrium p-values for each variant are provided in S9 Table . Single-variant analysis . We tested single variants for association with FG- and FI-derived inverse normalized residuals assuming an additive genetic model using a linear mixed model to account for relatedness with EMMAX [5] . Study-specific QQ plots and genomic lambdas are shown in the S3 Fig . We repeated single-variant association analyses with untransformed FG and natural logarithm–transformed FI residuals to obtain effect estimates . We then combined the association summary statistics across studies by using a fixed-effects meta-analysis ( sample size Z-score weighted ) using METAL [36] . Genotype cluster plots of all variants described here were inspected visually in all studies . Single-variant conditional analysis . Conditional analysis was performed to identify additional association signals at known or novel loci . The analysis included the genotypes of the lead variant ( s ) at the conditioning loci as covariate ( s ) in the regression analysis in EMMAX . We then performed meta-analysis of the association summary statistics across studies by using a fixed-effects meta-analysis ( sample size Z-score weighted ) . Gene-based analysis . For gene-based testing , we first computed single-variant score statistics and their covariance matrices for all polymorphic markers within each study . We then combined the single-variant score statistics from all studies using the Cochran-Mantel-Haenszel method and computed corresponding variance-covariance matrices centrally [6] . These variance-covariance matrices were used to compute gene-level statistics . We applied a frequency-weighted burden test which assumes variants have similar effect sizes and SKAT , a dispersion test that performs well when both protective and deleterious variants are present [8 , 9] . Test-specific asymptotic distributions were used to evaluate significance . For gene-based analyses , we used only unrelated individuals ( n = 32 , 223 for FG and n = 29 , 848 for FI ) and included principal components as covariates to adjust for population structure . We generated four variant lists using frequency data and functional annotation . Variants were mapped to transcripts in Ensembl 66 ( GRCh37 . 66 ) . Using annotations from CHAoS v0 . 6 . 3 , SnpEff v3 . 1 , and VEP v2 . 7 , we identified variants predicted to be protein-truncating ( PTV; e . g . nonsense , frameshift , essential splice site ) or protein-altering ( e . g . missense , in-frame indel , non-essential splice site ) in at least one mapped transcript ( by at least one of the three algorithms ) [37 , 38] . We additionally used the procedure described by Purcell et al . to identify subsets of missense variants meeting “strict” or “broad” criteria for being deleterious , using annotation predictions from Polyphen2-HumDiv , PolyPhen2-HumVar , LRT , MutationTaster , and SIFT [10] . Masks 1 ( “PTV-only” ) and 3 ( “PTV + NSstrict” ) are restricted to variants with predicted major effect on protein function , and , as a result , disproportionately favor inclusion of rare variants , whilst masks 2 ( “PTV + missense” ) and 4 ( “PTV + NSbroad” ) are more permissive . In total , we tested 1 , 028 , 14 , 465 , 4 , 603 , and 13 , 093 genes having at least two such variants in the above four categories respectively . For gene-based tests reaching exome-wide significance , if the conditional analysis showed that the signal was driven by a single variant , we required the variant to achieve exome-wide significance in the single-variant test as well . Gene-based conditional analysis . We performed conditional gene-level analysis to evaluate whether rare or low-frequency variants associated with the trait in single-variant analysis could account for or were due to a gene-based test association signal [6] . The genotypes of the variant ( s ) at the conditioning locus were included as covariate ( s ) in this analysis . Estimating phenotypic variance explained by SNPs . We used a subset of Finnish samples ( FIN-D2D 2007 , DPS , DR’s EXTRA , FINRISK 2007 , and METSIM; n = 10 , 266 ) to calculate variance explained by G6PC2 . We ran a model regressing BMI adjusted FG on the four G6PC2 variants: intronic GWAS lead SNP rs560887 , p . His177Tyr ( rs138726309 ) , p . Tyr207Ser ( rs2232323 ) , and p . Val219Leu ( rs492594 ) , assuming an additive model ( and adjusting for sex , age , age2 , and study origin ) . A separate model was run excluding the GWAS SNP to determine the additional variance captured with the three coding variants . Power calculations . We had >99 . 9% power to identify variants that explain >0 . 3% of the phenotypic variance and 80% power to detect coding variants that explain >0 . 1% of the phenotypic variance . To achieve >80% power for variants with MAF<0 . 05% would require effect sizes of at least 1 SD unit of residuals of mmol/L for FG and pmol/L for FI . When we estimate power to detect association for aggregation tests , we make many assumptions: i ) proportion of variants contributing to trait variation , ii ) direction of effects , iii ) number of variants aggregated , and iv ) allele frequency distribution of the variants [34] . In this study , assuming 100% of the variants contribute to trait variation , we had >99 . 9% power to detect association for genes that explain >0 . 25% of the phenotypic variance and 80% to detect genes that explain >0 . 1% of the phenotypic variance using a burden test and >0 . 5% of the phenotypic variance using SKAT . In a less favorable scenario , for example assuming a gene explains 0 . 25% of the phenotypic variance , 25% of the variants contribute to trait variation , different directions of effect , 20 variants tested , and variants sampled from the reported allele frequency distribution in the exome-array design , power to detect association in this study may be near 0% for a burden test and 63% for SKAT [34] . Haplotype analysis . In 4 , 442 individuals from the Oxford Biobank , we used an expectation-maximization ( EM ) algorithm to obtain the posterior distribution of haplotypes consistent with the observed genotypes at four G6PC2 variants: intronic GWAS lead SNP rs560887 , p . His177Tyr ( rs138726309 ) , p . Tyr207Ser ( rs2232323 ) , and p . Val219Leu ( rs492594 ) . Haplotype association with FG- and FI-derived residuals ( after adjustment for age , sex , and BMI ) was tested in a linear regression framework , as a function of haplotype dosage from posterior distribution , and including principal components as covariates to account for population structure using the most frequent haplotype as baseline . In-silico mutation analysis . SIFT [39] , PolyPhen-2 [40] , and Condel [41] algorithms were used to predict the functional effects of the associated non-synonymous variants on protein function . Genomic Evolutionary Rate Profiling ( GERP ) [42] scores were calculated to indicate the degree of evolutionary conservation at a given human nucleotide based on multiple genomic sequence alignments and were measured as site-specific ‘rejected substitutions’: higher scores indicate greater conservation . Site directed mutagenesis . Human G6PC2 cDNA ( NM_021176 . 2 ) within a pCMV6-Entry vector ( with a C-terminal FLAG-tag ) was purchased from OriGene ( RC211146 ) . We generated non-synonymous variants in the G6PC2 coding sequence of the clone using Quikchange II Site-Directed Mutagenesis ( Agilent ) . All mutations were verified by Sanger sequencing; in each case , only the desired nucleotide substitutions was introduced . Western blot analyses . HEK293 and INS-1E 832–13 cells were transfected with each FLAG-tagged wild type or mutant G6PC2 construct using Lipofectamine 2000 ( Invitrogen ) . In protein degradation assays , cells were treated with 10μM MG-132 ( Calchembio ) or 100μM chloroquine ( Sigma ) for 15h . At 48h after transfection , cells were collected and homogenized by sonication in lysis buffer . Total cellular protein was separated by 4–12% SDS-PAGE ( Invitrogen ) and transferred to nitrocellulose membranes . We determined G6PC2 expression by immunoblotting using a mouse monoclonal FLAG M2 antibody ( Sigma , F1804 ) . A rabbit polyclonal antibody against β tubulin ( Santa Cruz , sc-9104 ) was used as a loading control . Secondary antibodies specific to mouse or rabbit IgG were obtained from Thermo Fisher Scientific . Protein bands were detected using the ECL reagent ( Pierce Thermo Fisher Scientific ) . Western blots were quantified by densitometry analysis using ImageJ and paired t tests of densitometric data were carried out in GraphPad Prism . Immunofluorescence . HEK293 cells were transfected with each FLAG-tagged G6PC2 construct using FuGene 6 transfection reagent ( Promega ) in 4-well chamber slides ( BD Biosciences ) . After 48h , cells were fixed with 4% paraformaldehyde in PBS for 15 min . Cells were permeabilized with 0 . 05% Triton X-100 in PBS for 15 min , and blocked for 1 h with 10% BSA in PBS-Tween 20 . We carried out double immunostaining of cells using FLAG M2 ( Sigma , F1804 ) and calnexin ( Santa Cruz , sc-11397 ) primary antibodies followed by anti-mouse fluorescein ( Vector Labs ) and anti-rabbit TRITC ( Dako ) . DRAQ5 fluorescent probe ( Thermo Fisher Scientific ) was applied at 20μM as a far-red DNA stain . Slides were mounted with Vectashield mounting medium ( Vector Labs ) and visualized on a BioRad Radiance 2100 confocal microscope with a 60× 1 . 0 N . A . objective . Images were acquired with different laser settings that were optimized for each sample and therefore fluorescent intensities are not comparable across samples .
Understanding how FI and FG levels are regulated is important because their derangement is a feature of T2D . Despite recent success from GWAS in identifying regions of the genome influencing glycemic traits , collectively these loci explain only a small proportion of trait variance . Unlocking the biological mechanisms driving these associations has been challenging because the vast majority of variants map to non-coding sequence , and the genes through which they exert their impact are largely unknown . In the current study , we sought to increase our understanding of the physiological pathways influencing both traits using exome-array genotyping in up to 33 , 231 non-diabetic individuals to identify coding variants and consequently genes associated with either FG or FI levels . We identified novel association signals for both traits including the receptor for GLP-1 agonists which are a widely used therapy for T2D . Furthermore , we identified coding variants at several GWAS loci which point to the genes underlying these association signals . Importantly , we found that multiple coding variants in G6PC2 result in a loss of protein function and lower fasting glucose levels .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[]
2015
Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus
Root-knot nematodes ( genus Meloidogyne ) exhibit a diversity of reproductive modes ranging from obligatory sexual to fully asexual reproduction . Intriguingly , the most widespread and devastating species to global agriculture are those that reproduce asexually , without meiosis . To disentangle this surprising parasitic success despite the absence of sex and genetic exchanges , we have sequenced and assembled the genomes of three obligatory ameiotic and asexual Meloidogyne . We have compared them to those of relatives able to perform meiosis and sexual reproduction . We show that the genomes of ameiotic asexual Meloidogyne are large , polyploid and made of duplicated regions with a high within-species average nucleotide divergence of ~8% . Phylogenomic analysis of the genes present in these duplicated regions suggests that they originated from multiple hybridization events and are thus homoeologs . We found that up to 22% of homoeologous gene pairs were under positive selection and these genes covered a wide spectrum of predicted functional categories . To biologically assess functional divergence , we compared expression patterns of homoeologous gene pairs across developmental life stages using an RNAseq approach in the most economically important asexually-reproducing nematode . We showed that >60% of homoeologous gene pairs display diverged expression patterns . These results suggest a substantial functional impact of the genome structure . Contrasting with high within-species nuclear genome divergence , mitochondrial genome divergence between the three ameiotic asexuals was very low , signifying that these putative hybrids share a recent common maternal ancestor . Transposable elements ( TE ) cover a ~1 . 7 times higher proportion of the genomes of the ameiotic asexual Meloidogyne compared to the sexual relative and might also participate in their plasticity . The intriguing parasitic success of asexually-reproducing Meloidogyne species could be partly explained by their TE-rich composite genomes , resulting from allopolyploidization events , and promoting plasticity and functional divergence between gene copies in the absence of sex and meiosis . Fully asexual reproduction occurs in only ~0 . 1% of animal lineages , which generally occupy shallow branches in the tree of life [1 , 2] . Although there are some exceptions [3–5] , the majority of asexual lineages of animals seem to be recently derived from sexual lineages , suggesting they are generally short-lived . Asexual animals lack the possibility to combine advantageous alleles from different individuals via sexual recombination and in association with Hill-Robertson effect and linkage between conflicting alleles , selection is assumed to be less efficient [6 , 7] . Furthermore , Muller's ratchet [8] and Kondrashov’s hatchet [9] models of “clonal decay” predict that they progressively accumulate deleterious mutations . Supporting these models , different studies have demonstrated accelerated accumulation of harmful mutations in asexual lineages [10–14] , or ( short-term ) increased accumulation of transposable elements ( TE ) in the absence of sex [15 , 16] . Hence , it is commonly postulated that obligate parthenogenetic animals have evolutionary and adaptive disadvantages compared to their sexual relatives and therefore represent evolutionary dead-ends . Consistent with the geographical parthenogenesis model , parthenogenetic populations of plant and animals are generally present at the edge of the geographical distribution of species , in marginal or anthropologically disturbed environments [17 , 18] . Their uniparental clonal reproductive mode is supposed to be advantageous for colonizing marginal environments where they escape competition with their sexual relatives . Indeed , parthenogenetic species are frequently found at higher latitudes and altitudes [17] . Root-knot nematodes ( genus Meloidogyne ) display a variety of reproductive modes ranging from sexual reproduction ( amphimixis ) to obligate asexual reproduction ( apomixis ) with intermediates able to alternate between sexual ( amphimixis ) and asexual ( automixis ) reproduction [19] . These notorious plant pests have been ranked number one in terms of economic threat to the agriculture among all nematodes [20] . Challenging the view that fully asexual lineages of animals are outcompeted by their sexual relatives , Meloidogyne species that reproduce without meiosis and without sex have a broader host range , a wider and more southern geographical distribution and are more devastating than their sexual relatives [21 , 22] . Whether some genomic singularities could account for their higher parasitic success despite the absence of sex remains unclear . In 2008 , we coordinated the publication of the draft genome sequence of Meloidogyne incognita [23] , an obligatory asexual nematode and the draft genome of M . hapla , a facultative sexual , was published the same year [24] . One singularity of the M . incognita genome was the presence of genomic regions in two or more copies that spanned several megabases and had an average nucleotide divergence of ~8% [23] . Such a structure was identified neither in the facultative sexual M . hapla nor in any nematode able to reproduce sexually , so far . The possible origin of the duplicated and diverged genomic regions observed in M . incognita is still debated . Two main hypotheses for the origin of this duplicated genome structure are that ( i ) duplicated regions represent former paternal and maternal genomes that diverged and became rearranged after their diploid sexual ancestor became asexual or ( ii ) they result from interspecific hybridization events [21] . As early as 1983 , observation of heterozygous patterns of isozymes had led to the hypothesis that M . incognita might have undergone hybridization [25] . Likewise , based on the presence of multiple divergent ITS nuclear markers within apomictic Meloidogyne despite closely related mitochondrial markers between species , it was suggested that these species had undergone hybridization from a set of closely related females with more diverse paternal lineages [26] . Recently , on the basis of the comparative analysis of the initial M . incognita genome and a draft of the meiotic asexual M . floridensis genome , it was also suggested that M . incognita is of hybrid origin [27] . Regardless of its origin , the potential functional impact conferred by the duplicated genome structure of M . incognita has never been assessed . Furthermore , in the absence of genomes for other apomictic Meloidogyne , it was impossible to state whether such a duplicated genome structure is a specificity of M . incognita or a more general signature of the most economically important root-knot nematodes that , intriguingly , all reproduce asexually . Here , we aimed at characterizing the genome structures of asexual root-knot nematodes , their most likely origin and the potential consequences at the functional level . We have re-sequenced the genome of M . incognita at much deeper coverage and have sequenced de novo the genomes of M . javanica and M . arenaria , two other apomictic root-knot nematodes of high economic importance . We have assembled these three genomes and validated genome assembly sizes with experimental assays . We confirm that the genomes of M . incognita and of the two other mitotic asexual Meloidogyne are made of duplicated yet diverged and rearranged genome copies . We have annotated the protein-coding genes and TE of the three genomes and performed a comparative genomic analysis , including the genome of the facultative sexual species M . hapla and the meiotic parthenogenetic M . floridensis . We show that the genomes of asexual mitotic Meloidogyne have a higher abundance of TE than M . hapla and any other nematode genome published so far . Using a phylogenomic analysis of the duplicated genomic regions conserved between species , we deciphered the origin and evolutionary history of the peculiar genome architecture of mitotic asexual Meloidogyne . To assess the potential functional outcome of these duplicated regions at a whole-genome scale , we searched and found signs of positive selection between the gene copies defining these genomic blocks . Using RNAseq analysis of different life stages of M . incognita , we show that the majority of gene pairs forming duplicated blocks display diverged expression profiles . Furthermore , gene pairs detected as under positive selection show a significantly higher proportion of diverged expression profiles . Our results show that mitotic asexual Meloidogyne possess duplicated , highly diverged and TE-rich genomes , an ensemble of features unequaled in any other nematode genome so far . We propose that the peculiar genome structures of these nematodes offer potential for adaptive plasticity and might contribute to the paradoxical success of these plant-parasitic animals despite the absence of sex . We sequenced the genomes of three asexually reproducing Meloidogyne species and the assemblies reached 184 , 236 and 258 Mb , for M . incognita ( Mi ) , M . javanica ( Mj ) and M . arenaria ( Ma ) , respectively ( Table 1 ) . These genome assemblies are bigger than any Meloidogyne genome assembly reported so far . To confirm these genome sizes , we measured DNA content via flow cytometry experiments and obtained size estimates of 189 ±15 , 297 ±27 and 304 ±9 Mb for Mi , Mj and Ma , respectively . The genome assembly of Mi was in the range of estimated size via flow cytometry whereas Mj and Ma assemblies were smaller by 34–60 Mb . To check whether these differences in sizes could be explained by duplicated or repetitive regions collapsed during genome assembly , we plotted the distribution of read coverage along the genome ( S1 Fig ) . We estimated that 17 . 1 ( Mi ) , 42 . 9 ( Mj ) and 21 . 6 ( Ma ) Mb of genome assemblies have a coverage twice higher than the rest of the genome sequence and might represent collapsed duplicated regions . Hence , part of the differences in sizes can be explained by these collapsed regions , as previously observed in the genome of the obligate mitotic rotifer Adineta vaga [5] . The genome assemblies contained 97% ( Mi ) , 96% ( Mj ) and 95% ( Ma ) of the 248 Core Eukaryotic Genes ( CEG ) in complete length [28] . These are the highest scores for a Meloidogyne genome so far , suggesting these assemblies are the most complete available to date . We annotated 45 , 351 ( Mi ) , 98 , 578 ( Mj ) and 103 , 269 ( Ma ) genes ( including , protein-coding genes , ncRNAs , rRNAs and tRNAs ) . Protein-coding genes spanned up to 43 . 7 ( 24% ) , 75 . 2 ( 32% ) and 82 . 2 ( 32% ) Mb of the Mi , Mj and Ma genomes , respectively . Because genome assemblies of the asexual Meloidogyne were ~3–5 times bigger than the haploid genome size of the facultative sexual M . hapla , we suspected these genomes to be polyploid . As a proxy to estimate ploidy levels , we mapped back all the protein-coding sequences ( CDS ) to their respective genome assemblies and analyzed the proportion of CDS mapping one locus or several loci in the genomes ( Fig 1 ) . In the facultative sexual M . hapla , we observed a peak of CDS mapping one single locus in the genome , indicating no sign of whole genome duplication ( WGD ) . In contrast , in the mitotic asexuals , we observed peaks of CDS mapping 3 , 3 to 4 and 4 loci in the genomes of Mi , Mj and Ma , respectively . These CDS mapping multiple loci are consistent with the genome sizes of the asexual Meloidogyne ( 3-5x bigger than the M . hapla genome ) and support their polyploid nature . Transposable elements ( TE ) covered 50 . 0% ( Mi ) , 50 . 8% ( Mj ) and 50 . 8% ( Ma ) of the genome assemblies . In comparison , only 29 . 2% of the M . hapla genome was covered by TE , using the same annotation protocol ( Table 2 ) . Due to its high fragmentation state , the genome of M . floridensis could not be annotated for TE . On average , 27–30% of the genes of mitotic parthenogenetic species are included within TE , whereas this proportion reaches only 17% in M . hapla ( see TE section for more details ) . Genome sizes as well as distribution of multi-mapping CDS strongly suggested polyploidy in the asexual Meloidogyne ( see above ) . We used MCScanX [29] to further investigate the duplication relationships of the protein-coding genes in Meloidogyne genomes . MCScanX classifies protein-coding genes as ( i ) singleton when no duplicates are found in the assembly , ( ii ) proximal when duplicates are on the same scaffold and separated by 1 to 10 genes , ( iii ) tandem when duplicates are consecutive , ( iv ) WGD or segmental when duplicates form collinear blocks with other pairs of duplicated genes and ( v ) dispersed when the duplicates cannot be assigned to any of the other categories . In the three mitotic asexual Meloidogyne species , 93 . 0–94 . 1% of protein-coding genes were estimated to be duplicated whereas only 46 . 6% were duplicated in the facultative sexual M . hapla and 52 . 9% in the meiotic parthenogen M . floridensis ( Table 3 ) . We noted that the dispersed category was the most frequent in all Meloidogyne genomes . However , this proportion negatively correlated with N50 values in the mitotic Meloidogyne , suggesting that these duplicates might be re-classified in other categories in the future . Interestingly , 12 , 445 , 5 , 806 and 15 , 632 genes were classified in the WGD / segmental category in Mi , Mj and Ma , respectively ( Table 3 ) . They formed 933 ( Mi ) , 581 ( Mj ) and 1 , 648 ( Ma ) pairs of segmentally duplicated genome regions . In contrast , there were only 90 genes forming 11 pairs of duplicated regions in M . hapla and only 12 genes forming one pair of regions in M . floridensis ( Table 4 ) . Collinear duplicated regions span up to 58 . 6 , 14 . 8 and 59 . 0 Mb of Mi , Mj and Ma genomes , corresponding to 31 . 8% , 6 . 3% and 23 . 0% of their respective sizes ( Table 4 ) . Average nucleotide divergence between pairs of duplicated regions was 8 . 4% , 7 . 5% and 8 . 2% for Mi , Mj and Ma , respectively , indicating a similar average divergence of ~8% . The distribution of % divergence between duplicated regions presented one single to two almost totally overlapping peaks ( S2 Fig ) . This observation holds for the three apomictic Meloidogyne and suggests the duplication events have occurred in a same time window . The divergence levels were substantially lower in coding regions ( 4 . 7 , 6 . 0 and 5 . 9% ) than in non-coding regions ( 9 . 7 , 9 . 0 and 9 . 7% for intergenic and 11 , 10 . 4 and 11 . 1% for introns ) for Mi , Mj and Ma , respectively ( Table 4 , S3 Fig ) . Median rates of synonymous substitutions ( Ks ) between gene pairs forming duplicated regions were 0 . 1 for the three apomictic Meloidogyne . Averaged Ks for duplicated pairs of regions were significantly negatively correlated with collinearity ( P<10−8 for Mi , Mj and Ma ) , which we measured as the fraction of collinear genes within a pair of regions ( S4 Fig ) . This indicates that divergence in terms of number of conserved genes between a pair of regions correlates with the nucleotide divergence of the coding sequences . In M . incognita and M . arenaria , we found 5 instances of duplicated regions on a same scaffold ( Fig 2 ) . In M . incognita , this corresponded to 42 collinear genes present in 4 pairs of tandem regions and 1 palindrome , whereas in M . arenaria , we found 29 collinear genes present in 2 pairs of tandem regions and 3 palindromes . If the duplicated regions represent vestiges of homologous chromosomes , such tandem and palindrome structures appear consistent with absence of chromosome pairing and meiosis , such as in the genome of A . vaga [5] . No similar structure was found in the genomes of M . javanica , M . hapla or M . floridensis . Average Ks value of gene pairs forming tandem or palindromic regions were in the range of Ks values measured for gene pairs in the rest of duplicated regions , suggesting they have the same divergence times . We found that 29–37% of gene copies forming duplicated regions in mitotic Meloidogyne were TE-derived , a proportion comparable to the proportion observed for the rest of the whole gene sets ( 27–30% ) . Furthermore , the distribution of Ks for pairs of TE-derived genes is not significantly different from the distribution of the rest of pairs of genes in duplicated regions , according to a Wilcoxon test . Thus , we can rule out the possibility that the observed duplicated regions are the results of TE multiplications . In plant genomes , following WGD , fractionation biases can be observed . One genomic copy tends to retain more genes and to accumulate less mutations than the other copy [30] . For each pair of duplicated regions in Meloidogyne , we tested whether a bias of retention of ancestral genes could be observed ( Methods ) . We found 24 ( Mi ) , 1 ( Mj ) and 36 ( Ma ) cases where one region had significantly ( Chi-square test , 5% level ) retained more ancestral genes than its counterpart . By comparing all the genes in duplicated regions and the MCScanX classification of gene copies , we also estimated that only 6% , 4% and 5% of ancestral collinear genes had no more copies anywhere in the Mi , Mj and Ma genomes , respectively and had probably been lost after WGD . To decipher the evolutionary history of the duplicated structure observed in the mitotic Meloidogyne , we conducted a phylogenomic analysis focused on the gene copies forming pairs of duplicated regions . We identified and used a dataset composed of 60 groups of homologous genomic regions defined as follows . The genomic regions must be conserved and contain at least 3 collinear genes in 2 copies in each of the mitotic Meloidogyne vs . one single copy in the amphimictic M . hapla ( Fig 3 for an example ) . These 60 groups of genomic regions encompass 2 , 202 homologous genes distributed in 222 clusters ( Fig 3A for an example , S5 Fig for the 60 conserved and duplicated homologous regions ) . Within each of the 60 groups of genomic regions , we generated multiple alignments of all the clusters of homologous genes individually . Although duplicated genes within a species are , on average , relatively distant ( Ks = 0 . 1 , 5–6% nucleotide divergence ) , gene copies between species can occasionally be identical . In order to maximize phylogenetic signal , the multiple alignments of each cluster of homologous genes were concatenated in each group of conserved duplicated regions . From the 60 concatenated multiple alignments , we successfully generated 54 maximum-likelihood ( ML ) phylogenies ( 6 failed because of short alignments , see Fig 3B for an example tree and S5 Fig for the 54 ML trees of conserved homologous regions ) . Only three possible bifurcating monophyletic topologies exist to separate the three mitotic Meloidogyne ( Fig 4 ) : ( 1 ) : ( Mi , ( Ma; Mj ) ) , ( 2 ) : ( Ma , ( Mi; Mj ) ) or ( 3 ) : ( Mj , ( Ma; Mi ) ) . We identified 60 such monophyletic clades and the most frequent corresponded to topology 1 , observed 33 times . Topology 2 was observed 15 times and topology 3 , 12 times ( Fig 4 ) . A total of 20 trees combined two of the three topologies mentioned above and allowed testing whether or not the two duplicated regions present the same evolutionary history across the 3 mitotic Meloidogyne . Among these 20 trees , a majority ( 13 ) combined two different topologies for the apomictic Meloidogyne , suggesting that the two regions have different evolutionary histories rather than a common ancestral duplication ( Fig 5 ) . The combination of topologies 1 and 2 was observed 7 times ( see Fig 3B for an example ) . The combination of topologies 1 and 3 and the combination of topologies 2 and 3 were each observed 3 times . Only 7 of the 20 trees showed twice the same topology; and in all these cases this was twice topology 1 . Part of the genes forming duplicated regions were present in more than two copies in at least one apomictic species . We identified 387 groups of homologous collinear genes ( total of 4 , 262 genes ) forming 3 or 4 duplicated regions in at least one mitotic Meloidogyne and at least 2 duplicated regions in the other mitotic . To decipher the evolutionary history of these additional copies , we counted the number of times the third or fourth copies hold a recent in-paralog ( or allele-like position ) relative to another copy , vs . the number of times these copies were in a new independent branching position ( Fig 6 ) . For genes present in 3 copies in a given genome assembly , the number of allele-like relationship was significantly lower ( binomial test , P<10−6 ) than the number of new phylogenetic position , for all three mitotic species ( Table 5 ) . Hence , genes present in 3 copies more frequently formed a new independent branch in the phylogenetic trees than species-specific recent paralogs or allele-like branches . For genes in four copies within a given genome assembly , the number of allelic-like relationship was lower than the number of new positions in all species but the difference was significant ( binomial test , P<10−5 ) , for M . arenaria only ( Table 5 ) . Overall , this ensemble of results suggests that the duplicated genome regions have different evolutionary histories and thus probably result from allopolyploidization . These pairs of regions and the corresponding gene pairs can thus be considered as homoeologous [32] . This term refers here to pairs of genes that originated by speciation and were brought back together in the same genome by hybridization . To reveal the maternal evolutionary history of Meloidogyne species included in our analysis , we performed a phylogeny based on mitochondrial protein-coding genes as well as the 12S and 16S rRNAs ( S1 Text ) . The phylogenetic tree ( Fig 7 , S6 Fig , S1 Table ) returned the following highly-supported topology: ( Ma , ( ( Mi , Mf ) , Mj ) ) ) . This topology corresponds to topology 2 , the second most frequently observed in the analysis of the 60 groups of homoeologous duplicated regions ( Fig 4 ) . This suggests that genomic regions displaying topology 2 correspond to the maternal contribution to the nuclear genome . We also measured the average nucleotide divergence of mitochondrial genes between the 3 apomictic Meloidogyne ( Mi , Mj and Ma ) . On average , the inter-species nucleotide divergence was very low ( 0 . 17% ) and ranged from 0 . 00 to 0 . 33% . In contrast , the average nucleotide divergence between the meiotic M . hapla and the three mitotic was 24 . 50% and ranged from 24 . 42 to 24 . 58% . Hence , mitochondrial phylogenetic analysis reveals a high similarity between mitochondrial genomes of the three mitotic species and a substantial distance to their sexual relative M . hapla . We tested whether gene redundancy due to the duplicated genomic regions might result in a relaxation of selective pressure on the gene copies . We employed two different strategies to detect positive and episodic diversifying selection . One raw approach based on pairwise computation of the ratios of rates of non-synonymous ( Ka ) vs . synonymous mutations ( Ks ) ; and a phylogeny-based statistical approach . We found that 612 ( 8 . 8% ) ( Mi ) , 698 ( 22 . 4% ) ( Mj ) and 2 , 061 ( 20 . 9% ) ( Ma ) homoeologous gene pairs had a Ka / Ks ratio greater than 1 , indicating possible positive selection ( Fig 8 ) . In a second , phylogeny-based approach , we looked for signs of episodic diversifying selection ( EDS ) in homoeologous genes shared by the 3 apomictic Meloidogyne genomes . We retrieved all homoeologous genes present in the three apomictic species and M . hapla and in 2 or more copies in at least one apomictic Meloidogyne . We found 1 , 735 such groups and used them to generate multi-gene alignments and their respective ML midpoint-rooted phylogenies . Using the random effects branch-sites model [33] , we found 172 ( Mi ) , 109 ( Mj ) and 208 ( Ma ) gene copies showing evidence of EDS ( S7 Fig for an example ) at the 0 . 05 confidence level ( P_Holm: corrected for 9 tests using the Holm-Bonferroni procedure ) . Among these genes , 20 ( Mi ) , 21 ( Mj ) and 47 ( Ma ) were also found to have Ka / Ks ratios >1 . To assess which functional categories were affected by positive selection or EDS , we examined Pfam domains and gene ontology ( GO ) terms associated to these genes ( S1 Text ) . Overall , a large variety of Pfam domains and associated GO terms were identified among proteins encoded by genes under positive selection ( Ka / Ks >1 ) or subject to EDS , in the three apomictic species . As many as 363 , 304 and 674 distinct Pfam domains , corresponding to 177 , 167 , and 310 distinct GO terms were found in proteins encoded by genes with Ka / Ks >1 in Mi , Mj and Ma , respectively ( S2 Table ) . Similarly , we identified 123 , 78 and 174 distinct Pfam domains , corresponding to 93 , 56 and 112 distinct GO terms , in proteins encoded by genes under EDS in Mi , Mj and Ma , respectively ( S3 Table ) . Regardless of the dataset ( Ka / Ks or EDS ) , few Pfam domains and GO terms were common to the 3 apomictic species and the majority of them were related to enzymatic , binding and metabolic activities as well as cell cycle-related and transport functions ( S2 and S3 Tables ) . Mapping raw GO terms to the more generic GO-slim terms , revealed more overlap between the three mitotic species . The vast majority of GO-slim terms were shared by the three species in the EDS as well as in the Ka / Ks datasets ( S2 and S3 Tables ) . Overlap between the EDS and Ka / Ks datasets was also high as 23 of the 28 GO terms shared by the three mitotic in the EDS dataset were also shared by them in the Ka / Ks dataset . These terms were mainly related to diverse enzymatic , catabolic , metabolic and biosynthetic functions . We identified significantly enriched GO and GO-slim terms in the Ka / Ks datasets as compared to the rest of homoeologous gene pairs ( S2 Table ) . However , no significantly enriched GO or GO-slim term was common to the three species . No GO or GO-slim term was found to be enriched at the significance threshold ( FDR<0 . 05 ) in the proteins under EDS as compared to the rest of homoeologous proteins . Functional divergence between gene copies can be viewed at different levels , including the biochemical function , the biological process or the expression pattern . Gene copies featuring the same biochemical function but expressed in different tissues or time points can be involved in different biological processes ( e . g . development of different organs ) . To biologically assess whether functional divergence actually occurs between homoeologous gene copies , we analyzed their expression patterns across four developmental life stages ( eggs , J2 infective juveniles , J3-J4 larval stages and adult females ) of M . incognita using RNAseq ( methods ) . We generated between 60 . 5 ( J3-J4 replicate 2 ) and 94 . 2 million ( egg replicate 2 ) 2x75bp paired-end reads across the 12 libraries ( 4 stages x 3 replicates ) . After all the cleaning steps , between 11 . 8 ( J3-J4 replicate 2 ) and 48 . 5 ( egg replicate 2 ) million clean paired-end reads were mapped to the M . incognita reference genome . The proportion of paired-end reads aligned on the genome varied between 75 . 0% ( female replicate 3 ) and 96 . 2% ( egg replicate 1 ) . The majority of the read pairs ( 57 . 2–76 . 1% ) mapped to a unique position on the genome ( Table 6 ) . Overall , a total of 42 , 705 M . incognita protein-coding genes ( or 97 . 7% of 43 , 718 in total ) had a log10 ( FPKM+1 ) >1 in at least one sample and were considered as expressed . After filtering out low-signal values as well as low-complexity genes , a total of 38 , 870 expressed genes remained , including 6 , 767 homoeologous gene pairs ( 7 , 299 initially ) . This ensemble of expressed genes was classified into 24 distinct expression clusters ( methods ) . We assessed whether homoeologous gene pairs tended to fall in the same expression cluster or in different expression clusters , indicating functional divergence . We found that 4 , 326 out of 6 , 767 ( 63 . 9% ) expressed homoeologous gene pairs showed signs of diverged expression by being assigned to two different expression clusters ( Fig 9 ) . Interestingly , pairs of homoeologous genes showing evidence of positive selection in M . incognita tend to be more often in different expression clusters than those showing no sign of positive selection ( 74 . 1% vs 63 . 9% , p-value <10−7 ) . This ensemble of results biologically confirms that the peculiar allopolyploid genome structure of asexual root-knot nematodes is associated to functional divergence between gene copies . Although recombination can prevent the accumulation of TE , sexual reproduction can favor transmission of TE between individuals . In parallel , hybridization can initially favor TE multiplication by exposing naïve host genomes to TE uncontrolled by their inactivation machinery ( e . g . chromatin modification or small RNAs ) . Thus , we investigated whether differences in TE abundance could be revealed between sexual and asexual Meloidogyne . With 29 . 2% of its genome occupied by TE , M . hapla has a relatively high TE abundance compared to other nematodes . Indeed , TE span 16 . 5% and 22 . 4% of the genomes of C . elegans and C . briggsae , respectively [34] , 18% in Trichinella spiralis [35] , 14–15% in Brugia malayi [36] and 22% in Bursaphelenchus xylophilus [37] . We found that TE span 50 . 0 , 50 . 8 and 50 . 8% of the genome assemblies of the asexual Mi , Mj and Ma , respectively ( Table 2 ) . The genomes of the asexually reproducing Meloidogyne thus appear to be particularly rich in TE and 1 . 7 times richer than the only sexual Meloidogyne genome available to date . Consistent with this observation , Class I retro-elements are on average 1 . 5 times more abundant in the asexual species . Within Class I elements , DIRS-like ( Dictyostelium intermediate repeat sequence ) appear to have undergone a particular expansion in the asexuals as they are on average 5 . 5 times more abundant than in the sexual species . Class II DNA transposons are 1 . 9 times more abundant in the three apomictic species than in the M . hapla genome . Although Helitron occupy a comparable proportion in asexuals and in the sexual , all the other categories are more than 2 times more abundant in the asexuals . This includes Maverick-like and TIR ( terminal inverted repeats ) elements as well as “unclassified” TE that possessed characteristics of Class II elements but could not be further assigned to one family . The rest of the potential TE is in the “other” category , which gathers DNA fragments displaying contradictory features of both Class I and II elements . This category was also more abundant in the asexuals than in the sexual species ( ~1 . 8 times ) . This overall abundance of TE in asexual Meloidogyne has implications at the protein-coding level . While 27–30% of the protein-coding genes of asexual Meloidogyne are totally included within TE , only 17% of M . hapla genes are within TE . Hence , TE abundance partly explains the higher number of genes observed in the asexual Meloidogyne ( 43 , 718–102 , 269 compared to 14 , 207 in M . hapla ) . We tested whether the higher gene numbers observed in asexual Meloidogyne were homogeneously distributed along all protein domain families . We plotted the abundance of protein domains in Mi , Mj and Ma as a function of their abundance in Mh ( Fig 10 ) . The abundances of protein domains in Mi , Mj and Ma were all positively correlated to the abundance in Mh ( R2 = 0 . 92 , R2 = 0 . 89 and R2 = 0 . 87 for Mi , Mj and Ma , respectively ) . The slopes of the linear regressions were 3 . 06 , 4 . 49 and 4 . 80 for Mi , Mj and Ma , respectively , suggesting that most of the protein domains are between 3 and 5 times more abundant in the three asexuals as compared to M . hapla . We compared the abundance of Pfam domains known to be found in TE-related genes and important for their own transposition activity ( e . g . reverse transcriptase , integrase , transposase ) in the four Meloidogyne species . We found that , on average , these domains were 3 . 4 to 9 . 8 times more abundant in asexual Meloidogyne than in M . hapla ( S4 Table ) . For instance , rve ( integrase core domain ) is present in 205–689 copies in the three asexuals while it is found in only 59 copies in M . hapla . Similarly , the DDE_ 3 ( DDE superfamily endonuclease ) domain is absent in the M . hapla protein set while it is found in 13–61 copies in the three asexuals . This suggests that expansion of at least some families of TE might be in part responsible for the higher number of protein-coding genes in the asexuals . Meiotic pairing and segregation require high sequence identity and collinearity between homologous chromosomes . Usually , sequencing the genome of a diploid sexual animal involves performing repeated cycles of inbreeding to obtain lineages virtually homozygous at all loci . Genome assembly then results in collapsing all these virtually identical paternal and maternal variants into one single haploid reference sequence . We actually observed this in M . hapla which was assembled into a ~54 Mb genome [24] , similar to previously reported measures of haploid genome sizes ( ~50 Mb ) [38 , 39] , and confirmed by our flow cytometry measures ( ~60 ± 1 . 5 Mb , Table 1 ) . Concordance of genome assembly size with experimental measures , associated to the absence of extensive duplications of genomic regions , indicate a canonical sexual diploid genome . The haploid chromosome number of M . hapla is n = 16 , similar to the putative ancestral haploid number of chromosomes ( n = 18 ) in Meloidogyne species [19 , 22 , 40] . Hence , we can hypothesize that the ancestral haploid genome size for a Meloidogyne is ~55–60 Mb with n = 16–18 chromosomes . The genome assembly sizes of the three mitotic Meloidogyne species we describe here reach ~180 Mb , ~235 Mb and ~260 Mb for Mi , Mj and Ma , respectively . This represents ~3x , ~4x and >4x the expected haploid genome size for a Meloidogyne species . Flow cytometry measures of nuclear DNA content suggest an even larger genome size of up to ~300 Mb for Mj and Ma ( Table 1 ) . Hence , the genomes of apomictic Meloidogyne ( ~180–300 Mb ) are 3 ( Mi ) to 5 times ( Ma ) bigger than the ancestral haploid genome size for a Meloidogyne species . Furthermore , Pfam domains are on average 3 , 4 . 5 and ~5 times more abundant in the mitotic Mi , Mj and Ma genomes , respectively than in the M . hapla genome ( Fig 10 ) . Moreover , alignment of the CDS to the respective Meloidogyne genomes showed that while in the sexual M . hapla , most CDS map one single locus; we observe a peak at 3 matching loci for Mi , a peak between 3 and 4 for Mj and a peak at 4 matching loci for Ma ( Fig 1 ) . Finally , we showed that a substantial proportion of gene copies form collinear blocks of duplicated genome regions . Taken together , these results strongly suggest that the genomes of mitotic Meloidogyne are polyploid , with M . incognita being most likely triploid , M . javanica tetraploid and M . arenaria tetra- to pentaploid . Observation of chromosome numbers ( supplementary discussion S1 ) further supports polyploidy of the three asexual Meloidogyne . Similarity between genome assembly sizes and measures of total nuclear DNA content via flow cytometry suggests that most of the former paternal and maternal donor genomes have been separately assembled , probably due to their high within-species divergence . Indeed , the duplicated collinear genome regions span several Mb and thousands of genes in each mitotic Meloidogyne genome and show a similarly high within-species average nucleotide divergence of ~8% , confirming initial analysis of the Mi draft genome[23] . Likewise , the per-site synonymous substitution rate ( Ks ) of collinear gene pairs that define these duplicated genome regions had a very similar median of 0 . 1 for all three species . This homogeneity of nucleotide divergence and Ks between pairs of collinear regions for the three mitotic Meloidogyne species suggests that they have duplicated in a same time window and thus separated for a similar amount of time . Due to multiple synteny breakpoints , no long scaffold could be aligned on its whole length to another long scaffold in any of the three mitotic Meloidogyne . This rearranged chromosomal structure combined with the high average divergence between homoeologous blocks suggest chromosome pairing must be complicated if not impossible . Furthermore , in Mi and Ma , we observed collinear regions present in palindromic or tandem arrangement on a same scaffold . Such structures , similar to the ones observed in the ancient asexual bdelloid rotifer A . vaga [5] , appear incompatible with segregation of homologous chromosomes in conventional meiosis . Both the difficulty of pairing homologous chromosomes and the impossibility to separate the genome in two equivalent chromosome sets are consistent with the absence of meiosis and the strict asexual reproduction of these organisms . Palindromes or tandem blocks were not observed in the genome of the meiotic M . hapla , and because this genome presents high contiguity ( the highest for a Meloidogyne ) ; this most probably represents true absence . Similar analysis could not be performed for the M . floridensis genome; due to its low contiguity and fragmented nature , ( only 12 genes were found in one pair of duplicated regions ) . The duplicated genome regions in mitotic Meloidogyne tend to be more similar across different species than they are to their other copies within the same species . Furthermore , when duplicated regions form two or more clades in phylogenomic analysis , these clades more frequently present distinct topologies . Thus , collinear duplicated regions within a species have different origins and evolutionary histories and probably do not originate from common ancestral allelic regions that accumulated mutations separately ( i . e . no Meselson-White effect ) . Contrasting with the high within-species divergence of duplicated blocks in the nuclear genome ( avg . divergence ~8% ) , mitochondrial genes are almost identical in Mi , Ma and Mj ( avg . divergence ~0 . 17% ) . This confirms previous observations that these three species share virtually identical mtDNA markers [26 , 41 , 42] and suggests that Mi , Mj , and Ma share closely related or common maternal ancestors . The mitochondrial genome is expected to accumulate mutations faster than the nuclear genome ( e . g . 100–1 , 000 times more rapidly than the nuclear genome in C . elegans [43–45] ) . Hence , the divergence time between the nuclear genome copies within a same species is assumed much higher than the divergence time between the different species themselves , based on mitochondrial data . Inter-specific hybridization is the most likely hypothesis that could resolve at the same time the discrepancy between low between-species mitochondrial divergence and high within-species nuclear divergence levels and the observed topologies in the phylogenomic analysis ( alternative hypotheses are discussed in S1 Text ) . We propose that not only Mi but also Mj and Ma most likely originated from multiple hybridization events with a same or closely related maternal donor lineage and different paternal donors . This confirms , at a whole genome scale , a previous formulation of this hypothesis based exactly on the same kind of observed discrepancy between low divergence in mitochondrial markers between species and high divergence in ITS nuclear markers within species of apomictic Meloidogyne [26] . In this regard , the case of salamander in the Ambystoma genus constitute an interesting parallel . Indeed , some unisexual species in this genus are characterized by their absence of meiosis , their various ploidy levels ( from 2n to 5n ) , their hybrid origin and their closely related mitochondrial genomes [46] . In apomictic Meloidogyne , because the mitochondrial divergence is very low , the speciation between Mi , Mj and Ma as well as the hybridization and associated loss of sex must be very recent . The very low proportion of collinear genes lost in duplicated genomic blocks further support recent whole genome duplication events ( via hybridization ) . Indeed , after a whole genome duplication event , regardless whether it involves hybridization or not , most of the redundant gene copies are expected to be lost relatively rapidly . For instance , it has been shown in teleost fish that 70–80% of the genes have been rapidly lost after the latest WGD event [47] . Based on genome sizes , Pfam domain abundance and peaks of genes in 3 , 4 or more copies , we estimated that Mi was most likely triploid while Mj and Ma were respectively most likely tetra to penta-ploids ( see above ) . Some collinear regions are conserved in more than 2 copies within all the genomes , which allowed assessing the evolutionary histories of the third and fourth genome copies . For the three asexual Meloidogyne , the third copies of collinear genes were significantly more frequently similar to a cognate gene in another Meloidogyne species than to any of the other two copies found in the same species ( Table 5 ) . Thus , the third copies probably derive from a distinct hybridization event . This suggests a two-step hybridization process . First , homoploid hybridization ( hybridization between two diploid AA and BB progenitors without associated genome doubling [48 , 49] ) took place and led to a diploid AB hybrid . Then , a second hybridization between an unreduced AB gamete of the homoploid hybrid with a reduced C gamete of another sexual species led to the presence of three distinct copies ( ABC ) of nuclear genomes within a same species . It should be noted that unreduced gametes are frequently produced by inter-specific hybrids [50] . Although this hypothesis could explain the triploid genome of M . incognita , additional steps are needed to explain the tetra to penta-ploid genomes of M . javanica and M . arenaria . We hypothesize that the triploid bridge pathway described in several polyploid plants [51 , 52] could explain the transition between triploids ( similar to M . incognita ) and tetraploids ( similar to M . javanica ) . Indeed , under this hypothesis , triploids can constitute a bridge towards tetraploidy by producing unreduced triploid gametes , that , by fusing with a haploid gamete , would lead to a tetraploid progeny . Those tetraploids would in turn produce diploid gametes that would combine with haploid gametes of other species , creating a new triploid . And this triploid , could in turn serve as an intermediate towards new tetraploid by fusing unreduced triploid gametes with haploid gametes , constituting a “triploid-tetraploid-triploid” circle as suggested in [53] . Finally , fusion of an unreduced triploid gamete with either a reduced gamete from a tetraploid or an unreduced gamete from a diploid , could lead to a pentaploid hybrid similar to M . arenaria . In this perspective , the plant genus Boechera constitutes a good exemplary system for cases of hybridization at different ploidy levels and ecological success [54] . Indeed , it constitutes a genus in which both homoploid diploid and triploid hybrids are present with also less frequent tetraploids or species of higher ploidy levels . Similarly to the Meloidogyne , the hybrids are apomicts and highly heterozygous . The whiptail lizards constitute an interesting similar example of animal with fully asexual reproduction . Like the asexual Meloidogyne , these lizards are of hybrid origin . Interestingly , several polylploid lineages were identified and they also present a fixed heterozygosity [55 , 56] . Following loss of sexuality , it has been hypothesized that TE could invade the genomes because recombination would tend to favor their elimination [57] . Alternatively , it has been suggested that the only asexual animals that survive are those that control TE multiplication in their genomes . Examples supporting these two different hypotheses exist in the literature . In Daphnia arthropods , sexual reproduction seems to be correlated with an initial slower accumulation of TE in genomes whereas , at the long-term sex is associated with higher TE loads [15] . In parasitoid wasps , it has been shown that TE are more abundant in Wolbachia-induced asexual lineages than in sexual lineages [58] . However , whether this is a consequence of sex loss or of Wolbachia infection remains to be clarified . In contrast , in the ancient asexual bdelloid rotifer A . vaga , TE occupy only 3% of the genome and while a high diversity of TE was found , they are generally present at very low copy numbers [5] . This suggests that TE proliferation might be under control in this species . Recently , a comparison of the TE load in five sexual vs . asexual lineages of arthropods showed no evidence for TE accumulation in the asexuals [59] . In Meloidogyne , we found that TE occupy ~50% of the genomes of the three mitotic species while they occupy only 29% of the genome of M . hapla . Although it appears that TE have proliferated in the genomes of the asexual Meloidogyne , this might be a consequence of their hybrid origin rather than of their mode of reproduction . Regardless their origin , this abundance of TE might constitute a potential for genomic plasticity in the absence of sexual recombination . Supporting this hypothesis , some canonical full length TE were previously experimentally identified in these Meloidogyne species [60] . Furthermore , a Tm1 transposon has been identified in apomictic Meloidogyne but no homolog with an intact transposase could be found in the sexually-reproducing relative M . hapla [61] . Interestingly , the Cg-1 gene , whose deletion is associated to resistance-breaking strains of M . javanica , has been identified within one of these Tm1 transposons . Thus , TE possibly have an adaptive impact on these nematodes , including on their host plant range . Mi , Mj and Ma are exceptionally successful , globally distributed parasites of diverse agricultural crops [62 , 63] . Intriguingly , their geographical distributions and host ranges are wider than those of their sexual relatives . Furthermore , in controlled condition , they are able to overcome plant resistance within a few generations [22] . In the absence of sex and meiotic recombination to provide genomic plasticity and adaptability , their allopolyploid nature may provide benefits contributing to their parasitic success . First , polyploidy can provide the raw material for neo- and sub-functionalization of duplicated gene copies , resulting in novel genetic variation [64 , 65] . It has been shown in yeast that ploidy level is correlated to faster adaptation [66] . Also , it has been suggested that polyploidy could mask deleterious recessive alleles [67] and limit their accumulation via gene conversion between homologous regions [5] . Furthermore , allopolyploidy , by combining several genomes in one species , may lead to transgressive phenotypes that surpass those of the parent species via novel genetic combination and heterosis [50 , 67 , 68] . Ambystoma salamanders constitute one clear case of transgressive phenotype in animals . Indeed the hybrids between one native and one introduced species are ecologically fitter and more successful than the parental native species as well as other related species in the native environment [69 , 70] . Here , we tested whether the presence of several divergent genomic copies in a same species , could have functional consequences at the coding level . Hybridization brings together homoeologs chromosomes and therefore orthologous gene copies within an individual . Because the three mitotic Meloidogyne have very close mitochondrial genomes , their speciation was certainly recent . Hence , we can hypothesize that most of the high within-species nucleotide divergence between duplicated genomic regions is due to hybridization rather than long-term divergence . Most likely , the hybrid inherits orthologs that had retained similar function and following functional redundancy , selective pressure on these genes may relax and drive them to different evolutionary trajectories [71 , 72] . In some cases , the relaxation of selective pressure can allow emergence of new adaptive mutations . We have shown that ~8 to 20% of gene copies coming from the duplicated genomic regions harbor signs of positive selection . A diversity of Pfam domains and associated gene ontology terms were predicted in proteins encoded by positively selected genes . Although many terms and domains were related to enzymatic and other catalytic functions , there was a poor overlap between the three apomictic species , and different domains and functions were specifically enriched in positively selected genes in each species . These observations suggest that the functional consequences of the hybrid genome structure were different in each species . In the model root-knot nematode M . incognita , we showed that more than 60% of homoeologous gene copies display diverged expression patterns . These gene copies resulting from hybridization have only single-copy equivalents in the sexual relative M . hapla . This biological confirmation of functional divergence suggests that additional genes in asexual root-knot nematodes are not just merely functionally redundant with their single-copy orthologs in the sexual relatives but actually support plasticity and variability . Thus , we can assume that the allopolyploid genome structures of asexual root-knot nematodes provide them with a reservoir of variability and adaptability that could partly compensate the absence of sexual reproduction . Noteworthy , these results are consistent with two other recent studies of hybrid animal genomes ( the Atlantic salmon and the frog Xenopus laevis ) that both also showed extensive functional divergence at the expression level between homoeologous gene copies [73 , 74] . Interestingly , we noted that the proportion of expression divergence is significantly higher ( >70% vs . >60% , p-value<1 . 10−7 ) in homoeologous gene pairs that are under positive selection . These gene pairs combine both divergence at the expression level and accumulation of non-synonymous mutations that could lead to functional divergence at the biochemical level . They are thus the most obvious candidates for neo or sub functionalization . How an animal can survive without sexual reproduction and compete with its sexual relatives remains an evolutionary puzzle . Intriguingly , asexually reproducing ( apomictic ) root-knot nematodes outcompete their sexual relatives as plant parasites of global economic impact . We have shown here that the genomes of the apomictic Meloidogyne are duplicated most likely because of a complex series of hybridization events . Although the parental lineages are unknown , they probably belong to the sexual relative clades . Hence , this parasitic success could be viewed as a case of transgressive phenotype , where the ecological success of the hybrid progeny surpasses those of the parents [27 , 68] . Furthermore , hybridization has been proposed as an important evolutionary phenomenon that could give rise to new parasites and pathogens . For instance , hybridization of two host-specific plant parasitic tephritid fruit flies gave rise to a new species able to parasitize a new invasive host plant [75] . Similarly , hybridization of two Blumeria fungal pathogens gave rise to a new species that is able to infest a host plant of economic interest resistant to both progenitor species [76] . In the asexual root-knot nematodes , the presence of duplicated and diverged genomic regions probably promotes functional novelty between resulting gene copies , following positive selection . We confirmed this functional divergence at the expression level at the whole genome scale . Furthermore , the TE-rich nature of their genomes might also foster genomic plasticity not only actively by TE movements across the genomes but also passively by promoting chromosomal shuffling between these repeated genomic regions . Such a TE-promoted chromosomal shuffling associated to adaptation to different host plants has already been shown in a plant-pathogenic fungus [77] . Part of the intriguing success of mitotic asexual Meloidogyne could thus reside in their duplicated , diverged and TE-rich genomes resulting from hybridization . It would be interesting to explore the potential for plasticity and adaptation in the genomes of other asexual animals , particularly parasites and pathogens , to assess whether convergent or independent genomic characteristics support this potential . DNA samples preparation protocols for genome sequencing are detailed in the S1 Text . Genome assemblies were performed in four steps , following the same procedure as developed for resolving the degenerate tetraploid genome structure of the bdelloid rotifer A . vaga [5]: ( i ) assembly of 454 data into contigs , ( ii ) correction of the 454 contigs using Illumina data , ( iii ) scaffolding of 454 contigs and ( iv ) gap closing using Illumina data . For the first step , we used the multi-pass assembler MIRA [78] version 3 . 9 . 4 ( normal mode , default options except the number of cycles ) to generate contigs from the 454 genomic libraries ( S5 and S6 Tables ) . Although computationally demanding , running MIRA with multiple cycles is particularly appropriate to separate heterozygous regions in genomes , as anticipated in polyploid species . Moreover , Sanger reads of the M . incognita first draft genome sequence [23] were used to generate the current assembly . Twelve ( M . arenaria and M . javanica ) or sixteen ( M . incognita ) cycles were performed to separate a maximum of repeats and heterozygous regions . We subsequently used Illumina data to correct the homopolymer errors of the 454 contigs following a standard procedure [79] . The corrected contigs were linked into scaffolds using the program SSPACE [80] with 454 , Sanger and Illumina data . Finally , assemblies were gap-closed using GapCloser from the SOAPdenovo 2 package [81] with Illumina data . The statistics of the three genome assemblies are summarized in S5 Table . We assessed the completeness of the three genome assemblies by counting the number of Core Eukaryotic Gene ( CEG ) using CEGMA [82] . Flow cytometry was used to perform accurate measurement of nuclear DNA content in the three apomictic Meloidogyne ( M . incognita , M . javanica and M . arenaria ) as well as in the facultative sexual M . hapla , compared to internal standards with known genome sizes . Caenorhabditis elegans strain Bristol N2 ( approximately 200 Mb at diploid state [83 , 84] ) and Drosophila melanogaster strain Cantonese S . ( approximately 350 Mb at diploid state [85 , 86] ) were used as internal standards . Extraction of nuclei was performed as previously described [87] . Briefly , for each Meloidogyne species about two hundred thousand stage 2 juveniles ( J2s ) were suspended in 2 mL lysis buffer ( 1mM KCl , 30 mM NaCl , 10 mM MgCl2 , 0 . 2 mM EDTA , 30 mM Tris , 300 mM sucrose , 5 mM sodium butyrate , 0 . 1 mM PMSF , 0 . 5 mM DTT , 40 μl Igepal ) , grinded for 10 min with a Dounce homogenizer and filtered through a 0 . 20 μm nylon mesh . Subsequently , this 2 mL suspension was overlaid on top of 8 mL suspension buffer ( same as lysis buffer except for sucrose , 1 . 2 M , and without Igepal ) so that the tubes were ready for centrifugation ( 10 , 000 rpm , 30 min , 4°C ) to reduce the level of debris and to pellet nuclei . Supernatant was completely discarded and pelleted nuclei were re-suspended in suspension buffer . Then nuclei suspension was stained , at 37°C for 30 min , with 75 μg/mL propidium iodide and 50 μg/mL DNAse-free RNAse . The same nuclei extraction protocol was performed at the same time on the samples and on the two internal standards . Flow cytometry analyses were carried out using a LSRII / Fortessa ( BD Biosciences ) flow cytometer operated with FACSDiva v6 . 1 . 3 ( BD Biosciences ) software . Data were analyzed with Kaluza v1 . 2 software ( Beckman Coulter ) and cytograms exhibiting peaks for each phase of the cell cycle ( G0/G1 , S and G2/M ) were obtained . Standards and samples were processed both alone and together . Only mean fluorescence intensity of the first peak ( arbitrary units ) , corresponding to G0/G1 phase of the cell cycle of the cytograms , was taken into account to estimate DNA content . In this method [88 , 89] , the amounts of DNA in the Meloidogyne samples were determined by interpolating the fluorescence signals generated from the standards using the following equation: Meloidogyne DNA content ( Mb ) = ( G0/G1Meloidogyne samplex Standard DNA content ) /G0/G1standard . The estimated DNA contents of the Meloidogyne samples were calculated by averaging the values obtained from three biological replicates ( S8 Fig ) . To check whether some nearly identical duplicated genomic regions had been collapsed during the assembly ( as previously observed in the A . vaga genome [5] ) , we aligned the Illumina PE-reads of each species against their respective genome assembly sequence , using BWA [90] with default parameters . We computed the per base read coverage using BEDtools genomeCoverageBed [91] and plotted the distribution of the per-base coverage depth . This clearly showed 2 peaks for the three species , one systematically at twice the coverage of the first peak ( S1 Fig ) . We calculated the number of bases with per base coverage comprised in the range of the second peak and summed it up to obtain the total size of the duplicated regions that had been collapsed during the assembly . Predictions of protein-coding genes were performed using EuGene 4 . 1c [92] , optimized and tested for M . incognita on a dataset of 301 non-redundant full-length cDNAs . Translation starts and splice sites were predicted using SpliceMachine [93] . Three datasets of M . incognita transcribed sequences were provided to EuGene to contribute to the prediction of gene models: i ) Sanger ESTs ( Genbank 20110419 ) , ii ) a dataset of seven Illumina transcriptomes obtained in our lab in a previous study [94] , and iii ) a dataset of nine Trinity [95] assemblies of RNAseq data , generated in this study ( S7 Table , S1 Text ) . Transcribed sequences were aligned on the genome using GMAP [96]; spliced alignments spanning 80% of the transcript sequence length at a 90% identity cut-off were retained . Similarities to i ) C . elegans release Wormpep221 , ii ) G . pallida , release 1 . 0 [97] , and iii ) Swiss-Prot release December 2013 ( excluding proteins similar to REPBASE [98] ) were searched using BLAST [99] and provided to EuGene to contribute to gene modelling . The gene modelling algorithm used the standard parameters for the 4 . 1c version , except for the fact that i ) the gene finding algorithm was applied on both strands independently allowing overlapping gene models , ii ) non-canonical GC/donor and AC/acceptor sites were allowed on the basis of transcriptional evidences , iii ) a gene model was not allowed to span a gap ( ‘N’ ) longer than 1 , 000 nucleotides , iv ) the minimum length of introns was set to 35 nucleotides , and v ) the minimum CDS length cut-off was set to 150 nucleotides . For M . arenaria and M . javanica , the EuGene pipeline , with models and parameters tuned on M . incognita , was used to annotate both genomes . Two modifications were applied on the selection of reference datasets i ) Swiss-Prot ( excluding proteins similar to REPBASE ) and the proteome of M . incognita were used as reference proteomes ii ) assemblies of M . arenaria and M . javanica RNAseq data were used as sources of transcription evidences . We annotated ncRNAs using RNAmmer [100] , tRNAscan-SE [101] , Rfam release 11 [102] , and in house scripts to remove redundancy and consolidate results . The predicted protein sequences of M . incognita , M . javanica , M . arenaria and M . hapla were scanned for the presence of Pfam protein domains using the program PfamScan [103] against the Pfam-A HMM domain library ( release 27 . 0 ) , using default thresholds and parameters . A gene ontology annotation was inferred from the Pfam protein domain annotation using the pfam2go mapping file maintained at the gene ontology portal and generated from the InterPro2GO mapping [104] . Gene ontology terms were also mapped on the generic GO-slim ontology using the GOSlimViewer utility developed as part of AgBase [105] . The duplicated structures of Meloidogyne species were estimated by detecting conserved blocks of duplicated genes . The protein sequences of each genome were initially self-blasted to determine a homologous relationship with an e-value threshold of 1e-10 . Conserved blocks of duplicated genes were detected based on the gene locations in the genome using MCScanX [29] with default parameters . We required at least 3 collinear genes pairs for MCScanX to form a block . Using the perl script “add_ka_and_ks_to_colinearity . pl” included in the MCScanX package , we calculated Ks values for each homologous gene pairs between duplicated blocks . The median Ks value was considered a representative of the divergence between duplicated regions . We used a custom python script ( S2 Text ) to compute the pairwise nucleotide identity between collinear blocks for each species . Briefly , pairs of duplicated genomic regions were extracted according to the GFF3 positions of their first and last collinear genes . They were then aligned using NUCmer from MUMmer v3 . 23[106] with default parameters . We then filtered out sub-alignment shorter than 50 nt ( delta-filter -l 50 ) and summarized alignment using the dnadiff program from the MUMmer package . The average identity at the nucleotide level between duplicated regions was obtained from the output of dnadiff . Identity within coding and non-coding sequences was obtained by masking coding or non-coding sequences in each duplicated region before NUCmer alignment using BEDtools maskFastaFromBed v2 . 17 . 0 [91] . To analyze synteny conservation between genomes , we concatenated all the inter-/intra-species BLAST hits ( e-value threshold of 1e-10 ) of M . incognita , M . javanica and M . arenaria and M . hapla protein sequences and fed MCScanX with this pooled BLAST result as well as with information on the location of the corresponding genes in the respective genomes , as recommended in the MCScanX manual for multi-species comparisons . The M . floridensis genome had to be discarded from this comparative analysis because only one pair of regions composed of 12 genes block was detected for this genome preventing any large-scale analysis of conserved synteny . We required at least 3 collinear genes pairs for MCScanX to detect a block . We parsed the results of the collinearity analysis between genomes of Meloidogyne species ( HTML files output by MCScanX ) to extract collinear genes forming duplicated regions conserved between Meloidogyne species . We used those homologous collinear genes to perform phylogenomics analyses ( see below ) . For each pair of duplicated regions , the genes present on each region were counted and the number of genes that were present in the ancestor of these two regions was calculated as the total number of genes on the two collinear regions minus the number of gene pairs . We then compared the number of genes in each region to the number of estimated genes in the ancestral region to statistically determine whether one region had retained significantly more genes than the other within a pair . First , protein sequences were aligned using MUSCLE v3 . 8 . 31 [107 , 108] . Second , protein alignments were back translated into codon alignment using PAL2NAL v . 14 [109] with the ‘nogap’ option . Third , codon alignments were trimmed using GBLOCKS [110] with default options . The fittest model of nucleotide evolution was searched using the function ModelTest as implemented in the R package phangorn [111] . We then used PhyML [112] ( -d nt -b -4 -m GTR -f e -t e -v e -a e -s BEST ) to build maximum likelihood phylogenies with SH-like branches support on these pruned alignments . We rooted the phylogenies using the midpoint function of R package phangorn . For the rest of the analyses , we only retained the trees in which M . hapla displayed an outgroup position relative to the other Meloidogyne species in the midpoint-rooted topologies . Tree topologies were classified and counted using a custom R script . Phylogenetic tree figures were formatted and edited using EvolView [113] . To compute the Ka / Ks ratios per pair of collinear homologous genes , we used the Nei-Gojobori method [114] implemented in MCScanX . We eliminated all cases where 0 . 01<Ks<1 to discard genes that were either evolving extremely slowly or extremely rapidly and could potentially yield erroneous Ka/Ks estimates . We performed tests of episodic diversifying selection ( EDS , a form of positive selection ) using the random effects branch-sites model [33] implemented in the HYPHY package [115] . We looped the branchSiteREL . bf script over the 1 , 735 multi-sequence alignments and their respective ML midpoint rooted trees . Each alignment contained at least one collinear protein-coding gene for all three apomictic species and M . hapla and a duplicate in at least one asexual species . We chose the adaptive version of BSRE and allowed branch-site variation in synonymous rates . Branch with length less than 0 . 01 were not considered because ω rate classes cannot be inferred reliably for very small branches ( < 0 . 01 ) . Total RNAs were extracted from 4 M . incognita developmental stages ( pre-parasitic J2s , parasitic J3-J4 , adult females and eggs ) using TRIzol Reagent ( Invitrogen ) ; three independent biological replicates were performed for each stage . Total RNA quality and quantity were assessed by a 2100 Bioanalyser ( Agilent technologies ) . Samples with RNA integrity number ( RIN ) over 8 . 5 were kept for cDNA library construction , except for eggs samples for which RIN ranged between 6 and 7 . An input of 100 ng total RNA was provided to construct cDNA libraries via the Ovation Universal RNAseq system ( Nugen technologies ) . To eliminate unwanted rRNA transcripts , we designed 101 InDA-C primers to target M . incognita 28S and 18S transcripts for depletion . The 12 cDNA libraries ( 4 stages x 3 replicates ) were quantified and equilibrated to 4 nM using Kapa QPCR ( Kapa Biosystems ) . Finally , multiplexed libraries were sequenced on an Illumina NextSeq 500 sequencer on two High 150 flow cells ( 400M PE75 reads ) , on the UCA Genomix sequencing platform of Nice Sophia-Antipolis . The quality of the raw read fastq files were manually checked using FastQC and the following series of filters were applied to all the files . We first eliminated possible remaining ribosomal RNA contamination using SortMeRNA [116] . We then used PRINSEQ [117] to trim sequence ends with quality score lower than 28 , and only kept reads with an overall score >28 and a length >60 nucleotides . We aligned the cleaned reads to the M . incognita indexed genome assembly using the STAR 2-pass procedure [118] . We used RSEM [119] to estimate read counts , transcripts per million ( TPM ) as well as fragments per kilobase per million mapped reads ( FPKM ) for the M . incognita predicted protein-coding genes . RSEM takes into account multi-mapped reads and assigns them proportionally to the different loci according to probabilities estimated based on uniquely mapped reads . We transformed the raw FPKM values in log10 ( FPKM+1 ) values . To avoid the risk of spurious read counts due to low complexity regions in transcripts , we eliminated all the transcripts that had more than 1/3 of their length covered by low-complexity regions , as measured by RepeatMasker [120] . We also filtered out genes showing too much variability between replicates and showing an inside-replicate coefficient of variation of log10 ( FPKM+1 ) higher than 0 . 8 . We finally averaged expression over each triplicate , and filtered out genes with log10 ( FPKM+1 ) mean expression values lower than 0 . 3 in all conditions , as this corresponded to low signal . We then clustered genes according to their expression pattern in the four conditions . To be as robust and conservative as possible , we clustered together genes showing the same relative expression patterns in the four conditions , i . e . genes whose expression values are ranked in the same order between the four conditions , resulting in 24 ( = 4 ! ) groups . Homoeologous genes from a same pair that were located in two different gene expression clusters were considered as having diverged expression patterns .
Sexual reproduction is evolutionary successful in animals as more than 99% of species reproduce sexually . The few animals that have abandoned sex are usually believed to be short-lived and outcompeted by their sexual relatives . Yet , in the root-knot nematodes , plant pests of global economic importance , an intriguing feature is observed . Species that have abandoned sex cause more damage and have a wider worldwide geographic distribution than their sexual cousins . To understand this puzzling success without sex , we have sequenced and analyzed the genomes of the three most devastating asexual nematodes and compared them to that of a sexual relative . We showed that their genomes are large , duplicated , transposon-rich and have hybrid origins . Due to this polylploid hybrid origin , most of their genes are in several copies with substantial sequence divergence . We detected signs of positive selection between these gene copies and confirmed functional divergence at the expression pattern level . We hypothesize that their peculiar hybrid genome structures provide these nematodes with a potential for adaptation and plasticity and could explain their paradoxical success in the absence of sex .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "amphibian", "genomics", "taxonomy", "invertebrate", "genomics", "phylogenetics", "data", "management", "phylogenetic", "analysis", "genome", "analysis", "research", "and", "analysis", "methods", "sequence", "analysis", "genomic", "libraries", "computer", "and", "information", "sciences", "sequence", "alignment", "bioinformatics", "proteins", "comparative", "genomics", "evolutionary", "systematics", "animal", "genomics", "biochemistry", "database", "and", "informatics", "methods", "genetics", "protein", "domains", "biology", "and", "life", "sciences", "genomics", "evolutionary", "biology", "computational", "biology" ]
2017
Hybridization and polyploidy enable genomic plasticity without sex in the most devastating plant-parasitic nematodes
Metagenomic sequencing has produced significant amounts of data in recent years . For example , as of summer 2013 , MG-RAST has been used to annotate over 110 , 000 data sets totaling over 43 Terabases . With metagenomic sequencing finding even wider adoption in the scientific community , the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis , such as comparative analysis between multiple data sets . Moreover , although the system provides many analysis tools , it is not comprehensive . By opening MG-RAST up via a web services API ( application programmers interface ) we have greatly expanded access to MG-RAST data , as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data . This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects . As part of the DOE Systems Biology Knowledgebase project ( KBase , http://kbase . us ) we have implemented a web services API for MG-RAST . This API complements the existing MG-RAST web interface and constitutes the basis of KBase's microbial community capabilities . In addition , the API exposes a comprehensive collection of data to programmers . This API , which uses a RESTful ( Representational State Transfer ) implementation , is compatible with most programming environments and should be easy to use for end users and third parties . It provides comprehensive access to sequence data , quality control results , annotations , and many other data types . Where feasible , we have used standards to expose data and metadata . Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users . We present an API that exposes the data in MG-RAST for consumption by our users , greatly enhancing the utility of the MG-RAST service . Over 110 , 000 metagenomic data sets have been uploaded and analyzed in MG-RAST [1] since 2007 , totaling over 43 Terabases ( TBp ) . Data uploaded falls in three classes: shotgun metagenomic data , amplicon data , and , more recently , metatranscriptomic data . The MG-RAST pipeline normalizes all samples by applying a uniform pipeline with the appropriate quality control mechanisms for the various data sources . Uniform processing and robust sequence quality control enable comparison across experimental systems and , to some extent , across sequencing platforms . With the inclusion of standardized metadata [2] MG-RAST has enabled meta-analysis available through its web-based user interface at http://metagenomics . anl . gov . The user interface provides an easy-to-use way to upload data access data via download or interface , perform analyses , and create and share projects . As with most GUIs , however , there are limitations to what can be done . Examples of this include the number of samples processed in a single analysis , access to complete metadata , and easy access to raw data and quality metrics for each sample . As part of the DOE Systems Biology Knowledgebase project ( KBase ) we have implemented a web services application programmers interface ( API ) that exposes all data to ( authenticated ) programmers , enabling users to access available data and functionality through software applications . User access to MG-RAST's internal data structures is now possible . The MG-RAST API enables programmatic access to data and analyses in MG-RAST without requiring local installations . With the new API , users can authenticate against the service , submit their data , download results , and perform extensive comparisons of data sets . We chose to use the Representational State Transfer ( REST ) [3] architecture . The REST approach allows download of data in ASCII format , which allows users to query the system via URLs and returns MG-RAST data objects in their native format ( e . g . similarity tables or sequence files ) . For structured data ( e . g . metadata or project information ) the MG-RAST API uses JSON ( Javascript Object Notation , a widely used standard ) as its data format . Using this approach users can use simple tools to download data files to their machines or view the JSON in their web browsers using one of the many available JSON viewers . In addition , many programming languages have libraries for convenient HTTP interaction and JSON conversions . This article focuses on describing the architecture used - the underlying components of a web services architecture , their interactions , and the data used for their operation . REST has several key advantages for system scalability . Unlike more traditional remote procedure call methods , REST APIs make the semantics of requests visible at the HTTP protocol layer . This makes the system easier to scale , optimize , and harden through the use of HTTP level appliances providing security , caching , and proxy capabilities . REST APIs also have useful properties in terms of client adoption . They have a minimal number of prerequisites and any language with HTTP and JSON support or command line utilities , such as "curl" , can easily integrate with the design . The MG-RAST RESTful API supports introspection and versioning . In order to access a specific version of the API , the version number must be added to the base URL . The base URL for all API calls is http://api . metagenomics . anl . gov . Calling the base URL of the API without any options returns a list and description of available resources; calling a resource without any options returns a description of the resource and its request options with example calls . The MG-RAST pipeline accepts sequences in a variety of formats from most DNA sequencing platforms and transforms all sequences using automated pipelines ( see Figure 1 ) . The pipeline performs quality control , protein prediction , clustering , and similarity-based annotation on nucleic acid sequence data sets . The analyses provided by MG-RAST rely , to some extent , on comparison with external protein databases , maintained as a single data product in the M5nr [4] , and enabling users to switch annotation sources and thus naming conventions used for annotation at analysis time . Using the M5nr database , MG-RAST provides links to all major sequence databases and , for example , allows linking from metagenomic sequences to complete genomes ( see Table 1 for a list of available namespaces ) . Users are provided access to these MG-RAST resources as well as to analysis results being produced ( public data and the users' own data ) . Table 2 lists the high-level objects that can be accessed; in addition , users can upload sequence and metadata into their own private MG-RAST staging area . Some objects ( e . g . , metagenome , metadata , project , M5nr database ) will seem intuitive , while others are different from what most users would expect ( e . g . , download , annotation , matrix ) . We have designed these additional objects to allow rapid access to sets of sequences or analysis results related for a data set ( download ) , annotated sequences or BLAT results for a data set ( annotation ) , and abundance information for many data sets ( matrix ) . Most of the API calls are simply URLs , which can be entered in the address bar of a web browser to perform the download through the browser . These URLs can also be used with a command line tool like curl , in programing-language-specific libraries , or in command line scripts . The examples in the Results section illustrate the use of each of these methods . The example scripts are available on in the supplementary materials and on GitHub ( https://github . com/MG-RAST/MG-RAST-Tools ) along with other useful illustrative scripts . MG-RAST enables users to extract data based on functional or taxonomic annotations . The necessary functionality is provided by two API calls . The first API ( Box 1 ) call lists all metagenomes with certain metadata fields and functional contents , the second API call extracts all requested reads from a given metagenome . The following example script exploits these two API calls to produce a file with sequences annotated as proteases , using SEED annotations from all samples from marine environments . The reads are labeled with the originating data set and the read identifier , as well as the underlying similarity result . Download allows users to extract analysis result files from MG-RAST ( Box 2 ) . The following example below shows how to download BLAT [6] results for a given metagenome . The inbox is a staging area where users can upload metadata and sequence files and manage their data . This requires a MG-RAST account and user authentication ( Box 3 ) . An authentication token can be created through the user preferences in MG-RAST . Users can retrieve abundance profiles ( Box 4 ) based on functional or taxonomic profiles . Default output format is BIOM . As mentioned earlier , we use a M5-based nonredundant database to perform annotations . Here is an example of extracting the UniProt database entry record for a given sequence in a metagenome ( Box 5 ) . Using the M5nr , we identify the UniProt database record most similar to the sequence of a given feature . Users can retrieve project information ( Box 7 ) by using project ID and output as a JSON formatted file . Available information about individual samples , including IDs and metadata , can be accessed as shown in Box 8 . Using the search resource , users can search for data they want to retrieve . Queries can be made for , metadata , function , and taxonomy ( Box 9 ) . Complex queries are supported . In MG-RAST , all data is initially private . Users who submit data can decide to share that data with specific users ( by typing in an email address for the users ) or make the data publicly available . Both actions require the provision of standard-compliant minimal metadata by the submitting user . The API provides access to both public and nonpublic data , requiring users to submit authentication tokens for access to private data . Authentication tokens can be obtained via the MG-RAST web interface through the user preferences page and are valid for up to 14 days ( Box 10 ) . The token serves as login and password for the API . Below is an example of how to use the tokens in three different scenarios . Users can invalidate a token at any time by generating a new one . Note that accessing a remote site through an XMHttpRequest requires support for Cross-Origin Resource Sharing ( CORS ) compliance and Preflight Request . CORS requires the remote site to accept the local site's origin ( AccessControl AllowOrigin ) . For Preflight Requests , if an HTTP request from a browser adds a custom header to the request ( in the example “AUTH” ) , the browser first makes an OPTIONS request to the largest server , inquiring whether AccessControlAllowHeaders allows this header and whether AccessControlAllowMethod allows the request method ( GET/POST ) .
Metagenomic sequencing has produced significant amounts of data in recent years . For example , as of summer 2013 , the MG-RAST metagenomics analysis system has been used to annotate over 110 , 000 data sets totaling over 43 Terabases . With metagenomic sequencing finding even wider adoption in the scientific community , the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for comparative analysis ( i . e . , number of data sets ) . Moreover , although the system provides many analysis tools , it is not comprehensive . By opening MG-RAST up via a web services API ( application programmers interface ) we have enabled a programmatic way for others to use their bioinformatics tools with MG-RAST data .
[ "Abstract", "Introduction", "Design", "and", "Implementation", "Results" ]
[ "biodiversity", "ecology", "biology", "and", "life", "sciences", "computational", "biology" ]
2015
A RESTful API for Accessing Microbial Community Data for MG-RAST
The evolution of cooperation is a paradox because natural selection should favor exploitative individuals that avoid paying their fair share of any costs . Such conflict between the self-interests of cooperating individuals often results in the evolution of complex , opponent-specific , social strategies and counterstrategies . However , the genetic and biological mechanisms underlying complex social strategies , and therefore the evolution of cooperative behavior , are largely unknown . To address this dearth of empirical data , we combine mathematical modeling , molecular genetic , and developmental approaches to test whether variation in the production of and response to social signals is sufficient to generate the complex partner-specific social success seen in the social amoeba Dictyostelium discoideum . Firstly , we find that the simple model of production of and response to social signals can generate the sort of apparent complex changes in social behavior seen in this system , without the need for partner recognition . Secondly , measurements of signal production and response in a mutant with a change in a single gene that leads to a shift in social behavior provide support for this model . Finally , these simple measurements of social signaling can also explain complex patterns of variation in social behavior generated by the natural genetic diversity found in isolates collected from the wild . Our studies therefore demonstrate a novel and elegantly simple underlying mechanistic basis for natural variation in complex social strategies in D . discoideum . More generally , they suggest that simple rules governing interactions between individuals can be sufficient to generate a diverse array of outcomes that appear complex and unpredictable when those rules are unknown . Despite the appearance of cooperation in many social systems , natural selection will generally favor exploitative individuals that can maximize fitness by performing less of a costly cooperative act while maintaining the benefits accrued from the cooperative behavior of others . The evolution and maintenance of cooperation is therefore characterized by conflict between the self-interests of cooperating individuals . This social conflict can lead to the evolution of complex social strategies and counterstrategies that exploit the cooperative behavior of others while minimizing the costs of cooperation . The social amoeba Dictyostelium discoideum provides a compelling model for studying the genetic basis of such conflict and cooperation [1]–[5] . Upon starvation , up to 100 , 000 amoebae aggregate and differentiate to form a fruiting body composed of dead stalk cells that hold aloft a sporehead bearing hardy spores . Different genotypes will aggregate to produce a chimeric fruiting body , resulting in potential social conflict over which genotypes will “sacrifice” themselves to produce the stalk and which will contribute to the sporehead , and hence have direct reproductive fitness . Naturally occurring D . discoideum isolates exhibit widespread variation in the total numbers of cells allocated to spores when developed clonally [1] . This has been termed a “fixed” strategy because it reflects inherent differences in allocation patterns among isolates . However , genotypes often show dramatic shifts in spore:stalk allocation in chimera ( from that expected based on clonal allocations ) , which are highly variable and dependent on the precise pairing of genotypes or social partner [1] , [6] . These changes in behavior have been termed “facultative” strategies as they produce a remarkable range of behaviors , with some genotypes showing self-promotion wherein they produce disproportionately more spores when in competition compared to that expected given their clonal allocation . Success can also be gained in chimera through coercion , where genotypes “force” other genotypes to produce more of the stalk at the expense of their own spore production . Such complexity within a small set of naturally co-occurring isolates is surprising , and it is intuitive to assume a complex underlying genetic basis such as an active recognition mechanism that causes a change in behavior in the presence of foreigners . Indeed , kin recognition has been demonstrated between geographically distant D . discoideum isolates [7] , [8] . However , it is important to note that the description of apparently fixed and facultative behavior in D . discoideum is based on observations of the outcomes of interactions in clones and chimeras . It is therefore actually unknown whether it is based on a truly facultative underlying mechanism ( i . e . an induced facultative shift in some underlying biological process in response to the social partner ) or simply appears facultative at the behavioral level . For this reason , and to avoid confusion over descriptions of the outcomes of interactions versus the nature of the interactions themselves , hereafter we refer to these simply as clonal and chimeric strategies . Understanding the mechanistic basis of social interactions , and more specifically , why behavior appears to change depending on social partner , is crucial for us to understand the evolution of social conflict and cooperation in D . discoideum , or any other social organism . Here we hypothesize that variation in clonal and chimeric social behavior in D . discoideum is modulated by a simple mechanism based on the production of and response to social signals that govern developmental differentiation in this system . To test this hypothesis , we examine social signaling in a collection of natural genetic isolates and also in a genotype in which we have disrupted social behavior through a mutation in a known gene . We integrate measurements of signal production and response in these genotypes with a mathematical model to examine whether we can explain the apparently complex partner-specific social behavior observed in these natural and lab-generated genotypes . Although social success in D . discoideum is phenotypically complex , with social success depending on the specific social partner , it is ultimately a consequence of a simple developmental “decision”: to produce either stalk or spore cells . Stalk and spore cell differentiation is regulated by the production of—and response to—an array of diffusible stalk-inducing factors ( StIFs ) [9]–[12] . We therefore reasoned that the regulation of StIF production and/or response could potentially be a major determinant of the variation in patterns of spore:stalk allocation observed in this system [6] , and potentially the outcomes of social interactions between genotypes . To address this , we first used a modeling approach to investigate the effect that varying StIF production and response ( which together are the StIF phenotype ) has on patterns of clonal spore allocation . We then extended this model to examine how this variation in StIF production and response , which produce differences in clonal allocation , influences spore allocation during chimeric development and thus social success . This model is then used to examine whether variation among genotypes in StIF production and/or response could explain the patterns of spore allocation observed in clonal and chimeric fruiting bodies . The model is based on two features of the biology of DIF-1 , which represents the best characterized StIF: ( 1 ) all cells in the aggregate experience the same StIF concentration due to a combination of high diffusibility and constant cell movement [13]–[15] and ( 2 ) StIF response is linear within the normal physiological range ( Figure 1 ) [10] , [11] . This linear response predicts that differences in StIF production and/or response will lead to changes in allocation patterns . Because fruiting bodies are comprised of only spore and stalk cells , the spore allocation of genotype i with genotype j ( aij ) when clonal ( i = j ) or in chimera ( i ≠ j ) is defined simply as the number of cells of genotype i that become spores divided by the total number of cells of genotype i . Another assumption of the model is that the proportion of spore and stalk cells is governed purely by StIF response ( r ) and production ( s ) . Because the response to StIFs is linear , spore allocation of genotype i when clonal ( aii ) can be expressed as: ( 1 ) Note that , because aii is a proportion , the values of si and ri are constrained between 0 and 1 . Therefore , si = 0 corresponds to no StIF production , whereas si = 1 corresponds to maximum possible StIF production . Likewise , when ri = 0 indicates that a genotype has no sensitivity to StIFs , while ri = 1 indicates complete sensitivity . It is also important to note that the production parameter ( si ) can also be interpreted as a “potency” parameter , in that it reflects the ability of a signal to induce a developmental change . This potency could , therefore , be due to the amount of signal or the relative ability of that signal to induce differentiation . For simplicity , we call this “production” since there is no evidence that individuals differ in the quality of the StIF signal produced , but we emphasize that this parameter encompasses general signal strength . The model also predicts that the spore allocation of i when in chimera with j will be dependent upon the response and production of i , as well as the production of StIFs by j . Spore allocation will therefore also depend on the relative proportion of each genotype in the chimera: ( 2 ) where p and q are the proportions of i and j , respectively . This means that there will only be a facultative change in spore allocation in chimera when si ≠ sj ( because ri does not depend on the chimeric partner ) . To explore this idea , we first derived an expression for the proportion of genotype i in the sporehead ( pt+1 ) in terms of StIF response and production: ( 3 ) where pt and qt are the proportion of genotype i and j before development ( for full development of the model , see Materials and Methods ) . Equation 3 predicts the representation in the sporehead if the mechanism of interaction is based on StIF phenotypes ( “interaction line” ) ( Figure 2A ) . This can be compared to the behavior that would be expected from the null hypothesis that there is no interaction and proportions are determined simply by clonal allocation ( “null line” ) ( Figure 2A ) . Importantly , the model predicts that to generate the patterns of behavior observed in natural isolates [1] , both genotypes must vary in StIF response and production ( Figure 2A ) . To extend this idea further we explored the range of facultative behaviors that can be generated by the model . As facultative change ( dij ) is most simply defined as the difference between chimeric and clonal allocation ( aij − aii ) , it can be expressed in terms of StIF production and response ( Equations 1 and 2 ) : ( 4 ) Therefore , facultative shifts in allocation in chimera compared to clonal are expected to depend upon ( a ) a genotype's own response to StIF , ( b ) the difference between a genotype's StIF production and that of its chimeric partner , and ( c ) the frequency of the two genotypes in the chimera . Using this , we found that the model is sufficient to generate a wide range of facultative behaviors from self-promotion to coercion ( Figure 2B ) . The model predicts that apparently complex “facultative” changes in behavior across interactions can be achieved through changes in developmental signaling in the absence of a recognition mechanism . To test this idea , we firstly devised a novel genetic selection experiment to identify single gene mutations that exhibit altered social behavior wherein they lose in competition ( loser mutants ) . Mutants were enriched that preferentially form prestalk cells at the slug stage of development when mixed with wild type cells ( Figure 3A ) . After six rounds of selection , mutants with disruption of the lsrA gene were by far the most strongly overrepresented and therefore chosen for further study ( Figure 3B and 3C ) . The lsrA gene is predicted to encode a member of the bHLH family of transcription factors and becomes strongly enriched in the nucleus in developing cells , consistent with a role in the regulation of developmental gene expression ( Figure 4 ) . Clonal growth and developmental timing of the lsrA− mutant is identical to wild type ( Figure S1 ) . However , as expected , lsrA− mutant cells are over-represented in the prestalk population when developed in chimera with wild type cells ( Figure 5A and Figures S2 and S3 ) . Importantly , quantification reveals that mutant cells are , as expected , under-represented in the spore population of chimeric fruiting bodies ( Figure 5B ) . We next tested whether the lsrA− mutant exhibits a difference in clonal spore allocation compared to wild type and shows a shift in allocation when in chimera [1] . During clonal development , the lsrA− mutant was found to produce fewer prespore cells at the slug stage ( Figure 6A ) and fewer spores after fruiting body formation ( Figure 6B ) , as well as exhibiting higher levels of prestalk gene expression ( Figure 6C ) , thus demonstrating an altered spore allocation strategy . If differences in spore allocation observed in clones account for the differences in chimeric spore production , clonal spore allocation values should predict the relative fitness of the two genotypes in chimera ( Figure 6D; “expected” line ) . To test this idea , lsrA− mutant cells were mixed with wild type cells at different input frequencies and the relative number of spores of each genotype quantified . Surprisingly , the relative number of lsrA− mutant spores in chimeric fruiting bodies was always lower than that predicted by a fixed strategy alone , demonstrating that mutation of a single gene can lead to shifts in behavior in chimera ( Figure 6D; “regression” line ) . If the shifts in clonal and chimeric spore allocation behavior seen in the lsrA− mutant are generated through changes in StIF production and response , as our model predicts , both must differ in the wild type and mutant . To measure StIF production , conditioned medium containing StIFs was isolated from developing wild type or lsrA− mutant cells and tested for its ability to induce the expression of representative prestalk marker genes . lsrA− conditioned medium was a less potent inducer than wild type ( Figures 7A and S4 ) . In contrast , when the responsiveness of each strain was compared , the lsrA− mutant was found to be more responsive ( Figures 7B and S4 ) . Consequently , as the model predicts , the lsrA− mutant differs from wild type in both StIF production and responsiveness . Most importantly , relative StIF production and response measurements can be used to test whether the model predicts clonal spore allocation and the shift in allocation in chimera . The value of response × production ( Equation 1 ) for the lsrA− mutant is 2 . 1 times higher than wild type ( Figures 7C and S4 ) , suggesting a 2 . 1-fold difference in prestalk cell number . Consistent with this prediction , measurements of prestalk cell number in dissociated slugs reveal a 2 . 0-fold difference between wild type ( 20 . 0% ±1 . 5% ) and lsrA− mutant ( 39 . 7% ±2 . 3% ) ( Figure 6A ) . Secondly , we tested whether the model can predict the shift in spore allocation observed in chimera . Using the response and production measurements , the model accurately predicts the spore:stalk allocations of both strains when chimeras formed from different frequencies ( Figure 7D and Materials and Methods ) . We next tested whether differences in StIF production and responsiveness could also account for variation in the behavior of five genotypes isolated from a natural population , which are known to exhibit different clonal spore allocations and partner-dependent shifts in behavior ( chimeric spore allocation ) [1] . The five isolates show significant differences in StIF production , with almost a 3-fold difference between the highest and lowest producer ( Figures 8A and S5 ) . Furthermore , when the responsiveness of each isolate was measured , significant differences were apparent with almost a 15-fold difference between the highest and lowest responder ( Figures 8B and S6 ) . Therefore , naturally occurring D . discoideum isolates exhibit , as predicted , widespread natural variation in StIF production and response . We next tested whether these differences in StIF production and response could account for the differences in clonal spore production ( i . e . fixed strategies ) that are responsible for the linear social dominance hierarchy seen in these isolates , with isolate A producing the least stalk and isolate E the most stalk [1] . We find that differences in StIF responsiveness alone are almost sufficient to account for this hierarchy , whereas no correlation is seen between the hierarchy and relative StIF production ( Figure 8A and 8B ) . Most importantly , however , when values of StIF production and response are considered together ( as in Equation 1 ) , the hierarchy is faithfully reproduced ( Figure 8C ) . The spore allocations predicted by the model using these measurements closely match the observed values ( Pearson correlation; r3 = 0 . 942 , p = 0 . 017 ) [1] . Finally , we tested whether these values could account for the changes in spore allocation behavior that genotypes exhibit across different chimeric combinations [1] , where genotypes show social context-dependent ( partner-specific ) changes in allocation behavior . We found that these partner-specific responses predicted by the model ( using the estimated StIF phenotype of each genotype ) accurately predict ( Pearson correlation; r18 = 0 . 8924 , p<0 . 001 ) the observed spore allocation behavior in chimeras previously described ( see Materials and Methods ) ( Figure 8D ) [1] , demonstrating that the StIF signaling system appears to account for the complex social context-dependent shifts in social behavior that have been reported for D . discoideum . Our findings suggest that seemingly complex social behavior can have a relatively simple underlying developmental mechanism , in this case the regulation of signal production and response . As a result , social behavior can be accurately predicted from measurements of the signal production and response phenotype using a simple linear model . This is at odds with the notion that partner-specific responses would require some partner recognition system for genotypes to invoke a partner-specific strategy [1] , [7] , [8] , [16] . Indeed , we find that apparent partner-specific responses occur because the signaling system is “interactive” or epistatic , where the response of a genotype in a social interaction depends on both its own signal sensitivity and the signal production of the social partner relative to its own production ( Equation 4 ) . As a result , genotypes respond differentially to the same social partner because they differ in either their sensitivity to StIFs or their own StIF production ( or both ) . Our results have implications for the definition of what has been described as fixed and facultative behavior in this system ( and more generally ) . Specifically , we demonstrate that apparently facultative outcomes of interactions do not necessarily imply facultative changes when viewed at a mechanistic level . In this case , fixed clonal differences in social signals result in seemingly unpredictable facultative outcomes . Therefore , “social strategies” may be manifested largely as a set of knowable parameters related to StIF production and response , making patterns of behavior predictable in this system . Previous work has characterized patterns of genetic variation in this system in terms of the genetic control of the outcome of interactions by partitioning variation in allocation patterns into direct genetic effects , attributable to the genotype of the focal genotype; indirect genetic effects , attributable to the genotype of the social partner genotype; and genotype-by-genotype ( G×G ) epistasis , attributable to the specific combination of genotypes in an interaction [6] . Our model is consistent with these ideas and would suggest that direct genetic effects are largely determined by signal sensitivity but also partly by signal production ( since individuals always determine part of the signaling environment they experience ) , while indirect genetic effects would be determined entirely by signal production , where genotypes influence each other as a function of the amount of StIFs that they produce . The G×G epistasis would , therefore , be a consequence of the interactive nature of the system , where the indirect genetic effect depends on the sensitivity of the focal genotype and on the difference in signal production of the interacting genotypes ( cf . Equation 4 ) . We have found that disruption of a single gene , lsrA− , is sufficient to generate changes in both clonal and chimeric behavior . This is because the lsrA gene exerts pleiotropic effects on both signal production and response . One explanation for these wide-ranging effects may come from the finding that lsrA encodes a protein with homology to bHLH family transcription factors , which could potentially regulate the expression of genes required for both normal signal production and response . Indeed , it has previously been demonstrated that production and response of DIF-1 , a well-characterized example of a StIF , are indeed coupled , with increased DIF-1 response resulting in decreased DIF-1 biosynthesis and increased DIF-1 breakdown [17] , [18] . One consequence of this idea , however , is that it would be expected to lead to runaway social evolution , where there is constant selection for increased signal production and reduced response , whereby genotypes coerce others to produce stalks , while simultaneously decreasing sensitivity , thereby decreasing the ability of individuals to be exploited by the social signal . Such a directional runaway process predicts the system would either be devoid of standing genetic variation in signal production and response because variation would be rapidly depleted by strong social selection or would only contain variation that shows antagonistic pleiotropy ( which , in this case , would be associated with a positive correlation in pleiotropic effects where those that are high producers are high responders and vice versa ) . Despite this expectation , however , we find that natural isolates show a wide range of signal productions and sensitivities , with an overall negative correlation between signal production and response ( i . e . those that produce more signals are less sensitive to it ) among natural isolates . These isolates therefore follow the same basic pattern seen for the single lsrA gene mutation . This observation suggests that pleiotropic effects of mutations may generally be negative due to some feature of the biology of the system . However , it is also possible that much of the variation in the StIF system is not an outcome of selection but , rather , is largely an outcome of the random processes of mutation and drift . The influence of social selection in determining patterns of variation could be restricted due to the fact that chimerism is limited [19] and the social phase only occurs rarely compared to the intervening free-living generations , both of which reduce the effectiveness of selection for success in chimera ( leading to the presence of more variation simply because of weak social selection ) [20] . The latter of these will also reduce the impact of natural selection ( i . e . “non-social” selection occurring among clones ) on patterns of variation for clonal development . Because natural selection must favor the successful production of a stalk that holds aloft a sporehead , there is a potential trade-off between dispersal , favoring a larger stalk , and fecundity , favoring a larger sporehead . Therefore , it is possible that the negative correlation between StIF production and response observed is determined by such a natural selection trade-off . In this scenario , variation occurs because the fecundity-dispersal trade-off leads to similar fitness for a range of different spore allocation values , producing weak selection on specific allocation values but selection for the coordination of signal production and response through negative pleiotropy . Importantly , although our studies reveal that complex behavior can be generated by a simple system output , it seems likely that the underlying pathways regulating signal production and response may be more complex [21] . For example , many genes can potentially modulate StIF production ( e . g . biosynthesis , breakdown ) and response ( receptor , signal transduction , transcriptional output ) . lsrA is likely to be just one of many such genes inputting into pathways and networks that ultimately determine the “summary statistics” of signal production and sensitivity . Evolution of social strategies , therefore , would operate through these potentially diverse underlying pathways while manifesting themselves at the level of the simple interaction of the StIF system . But the fact that interactions may be largely governed by the interface of StIFs suggests that there is a constraint on the patterns of social behavior we expect to observe . The simple linear model of the StIF system is expected to result in a linear ( transitive ) social dominance hierarchy . Such linearity has been observed in this system [1] , [22] and , therefore , may reflect a developmental constraint on the evolution of the dominance hierarchy structure imposed by the linearity of the StIF system itself . Taken together , our studies suggest that even though complex and seemingly unpredictable outcomes can result from social interactions , they can be governed by a set of simple rules . Therefore , our studies provide a novel solution to the generation of complex ( apparently unpredictable ) social behavior , in this case based on the production and response to social signals . This result is not , however , at odds with the occurrence of biological complexity in this system but , rather , implies that the underlying complexity of gene networks is ultimately played out in the social arena through a simplified interface that dictates the result of social encounters . We therefore suggest that our understanding of the evolution and maintenance of social behavior will be greatly aided by defining basic rules governing interactions , as much as identifying the genes and pathways underlying social behavior . Lab strains ( AX4 ) and North Carolina wild isolates [1] were maintained in liquid culture in HL5 medium or in association with Klebsiella aerogenes bacteria . Reporter gene plasmids were transformed by electroporation [23] . For REMI mutagenesis [24] , AX4 cells were grown to 2×106 cells/ml in liquid HL5 medium . Cells were resuspended at 1×107 cells/ml in electroporation buffer ( 10 mM Na2HPO4 , 50 mM sucrose , pH 6 . 1 ) and mixed with 10 µg of BamHI linearized pBSR1 and 10 units of DpnII restriction enzyme . Cells were electroporated at 1 . 0 kV and 3 µF before plating . Cells were selected in 10 µg/ml blasticidin . For prestalk sorting mutant selection , a pool of 1 , 000 insertional mutants was grown in shaken culture at 22°C in HL5 medium in the presence of glucose before developing in chimera at a 10:90 ratio with wild type AX4 cells grown in the absence of glucose . Cells were developed on sterile KK2 plates containing 1 . 5% L28 agar ( Oxoid ) until the slug stage ( 14–16 h ) , at which point the anterior 25% of the slug was cut off using a sterile sharpened insect pin . Cells were disaggregated in disaggregation buffer ( 20 mM EDTA in KK2 ) and grown in filter sterilized HL5 medium containing 86 mM glucose and 10 µg/ml blasticidin in order to kill off wild type AX4 cells . The surviving blasticidin resistant cells were then transferred to shaken culture in HL5 medium containing 86 mM glucose and subjected to six rounds of selection . Plasmid insertion sites were identified by inverse PCR [25] . 10 µg genomic DNA was digested with RsaI and purified . For the ligation , 5 µg of the digested DNA was added to 40 µl of 10× T4 DNA ligase buffer and 2 µl of T4 DNA ligase in a total reaction volume of 400 µl . The ligated DNA was precipitated and subjected to inverse PCR using primers specific to a region on the actin 15 promoter of the insertion vector . The products of the PCR reaction were purified and sequenced . For the disruption of the lsrA gene , a 7 kb genomic fragment including insertion cassette was amplified by PCR from the lsrA locus in the lsrA REMI mutant isolated from the screen . The linearized construct was transformed into AX4 cells by electroporation followed by blasticidin selection and confirmation of gene disruption by PCR . Wild clones were grown in association with Klebsiella aerogenes and co-transformed with actin15-RFP and lacZ reporter plasmids by electroporation [23] . Clones were selected in HL5 medium containing 20 µg/ml G418 for 1 wk before plating out clonally in association with bacteria . Fluorescent clones were picked and tested for lacZ expression . Total spore production and relative number of GFP labeled spores was measured in strains developed clonally or in chimera [1] . To detect changes in sorting behavior , GFP labeled strains were mixed with unlabeled cells and examined . For measurement of prespore:prestalk ratio , dissociated slug stage cells were fixed and stained with prespore-specific anti-psv antibody [26] . Cell type–specific marker transformants were selected in 20 µg/ml G418 . For development , cells in exponential growth phase were harvested and washed before plating at a density of 6 . 4×106 cells/cm2 on KK2 ( 16 . 1 mM KH2PO4 , 3 . 7 mM K2HPO4 ) plates in 1 . 5% purified agar . For quantification of lacZ expression , 1×107 cells from slugs and culminants were lysed in 100 µl lysis buffer ( 100 mM HEPES , 1 mM MgSO4 , 2% Triton X-100 , 5 mM DTT , pH 8 . 0 ) and the protein concentration measured against a BSA standard curve . The amount of β-galactosidase enzyme activity per µg of protein was measured by adding a known amount of protein to 100 µl lysis buffer containing 2 mM CPRG ( Roche ) . β-galactosidase enzyme activity was monitored by measuring the color change at 550 nm . For quantification of cell type–specific gene expression , cDNA was obtained from cells throughout development . Gene expression was measured using qPCR [27] . For the collection of conditioned medium and induction of lacZ reporter genes , cells were grown in the presence of Klebsiella aeorogenes . Mid-log phase cells were harvested , washed , and resuspended at 1×105 cells/ml in stalk medium ( 10 mM MES ( pH 6 . 2 ) , 1 mM CaCl2 , 2 mM NaCl , 10 mM KCl , 200 µg/ml streptomycin sulphate ) containing 5 mM cAMP . Conditioned medium was collected from plates after 20 h incubation . For the induction of lacZ [28] , cells were incubated for a further 4–6 h with or without StIF or DIF-1 . Cells were then lysed in 100 µl lysis buffer ( 100 mM HEPES , 1 mM MgSO4 , 2% Triton X-100 , 5 mM DTT , pH 8 . 0 ) containing 2 mM CPRG . β-galactosidase enzyme activity was monitored by measuring the color change at 550 nm . To obtain overall production values , response data from all genotypes were pooled and scaled by the average in order to remove differences in responsiveness . To obtain overall response values , production data from all genotypes were pooled and scaled by the average in order to remove differences in production . Experiments were performed three times . Because fruiting bodies are comprised of spores and stalk cells only , the spore allocation of genotype i ( aij ) when clonal ( i = j ) or in chimera ( i ≠ j ) is defined simply as the number of cells of genotype i that become spores divided by the total number of cells of genotype i . The behavior of a genotype when clonal can be considered the “fixed” component of its social strategy . As such , it can also be used to determine the “null” behavior of genotypes in chimera under the assumption that there is no facultative change in allocation when in chimera ( i . e . that clonal behavior predicts behavior in chimera ) . We assume that the proportion of cells of genotype i that become spore or stalk is determined by the level of StIF present and genotype i's response to that signal ( ri ) . When clonal , the StIF level is determined solely by the signal production of the genotype itself ( si ) , and therefore , clonal allocation of cells to spore is defined as: ( 5 ) Note that , because aii is a proportion , the values of si and ri are constrained between 0 and 1 . Therefore , si = 0 corresponds to no StIF production , whereas si = 1 corresponds to maximum possible StIF production . Likewise , when ri = 0 indicates that a genotype has no sensitivity to StIFs , while ri = 1 indicates complete sensitivity . Clonal spore allocation can be used to calculate the expected null fitness ( wij ( e ) ) or “social success” of genotype i in competition with j: ( 6 ) These fitness values are relative such that the higher spore allocator would have the higher fitness in a chimera and wij ( e ) + wji ( e ) = 1 . Therefore , wij ( e ) is a “coefficient of social success” because it is a constant that determines the proportion of genotype i after development ( pt+1 ( e ) ) with j from any initial frequency ( pt ) : ( 7 ) Because Equation 7 gives the proportion of genotype i present in the sporehead of a chimeric mixture in the absence of facultative social behavior by either genotype , it therefore represents the null ( non-facultative ) “expected” lines in Figures 2E and 3A . When in chimera , the StIF level is determined by the proportional representation of the two genotypes in the chimera and their individual levels of StIF production . Therefore following Equation 5 , the spore allocation of genotype i in chimera with genotype j is: ( 8 ) where p and q are the proportions of i and j , respectively . This means that when si ≠ sj there will be a facultative change in spore allocation chimera . When the behavior of genotypes is different to that expected under the null model , the behaviors are referred to as “interacting” behaviors . Following the conventions of Equation 6 , the actualized fitness of i with j ( wij ) is: ( 9 ) Substituting Equation 8 into 9 gives an expression for wij in terms of StIF response and production: ( 10 ) This means that the model predicts that the fitness of i with j will be frequency dependent . Following Equation 7 , observed proportion of genotype i ( p ( t+1 ) ) within the sporehead after development with genotype j is given by: ( 11 . 1 ) which , in terms of StiF response and production , is: ( 11 . 2 ) Equation 11 . 2 is therefore the equation for the “interacting” lines in Figures 2E and 3A . The model also predicts changes in behavior in chimera ( dij ) , defined simply as aij − aii ( i . e . deviation in allocation when in chimera compared to that seen clonally ) , as a function of StIF response and production: ( 12 ) which demonstrates that shifts in allocation in chimera are expected to depend upon ( a ) a genotype's own response to StIF , ( b ) the difference between a genotype's StIF production and that of its chimeric partner , and ( c ) the frequency of the two genotypes in the chimera . See Figure 3B for the expected range of facultative behaviors . If the estimate of spore allocation of the wild type is 80% and the mutant makes 0 . 72× the spores as wild type ( Figure 2C ) , then the spore allocation of wild type can be estimated to be 0 . 8×0 . 72 = 0 . 576 . This converts to a stalk allocation for wild type and mutant of 0 . 2 and 0 . 424 , respectively , i . e . the stalk allocation of lsrA− should be 2 . 12× that of wild type . To generate the fitness curves in Figure 4D , the proportion of lsrA− spores within the sporehead after development with wild type ( pt+1 ) , i . e . the “model fit” line , was calculated using Equation 11 . 2 . The fitness of the mutant ( wlsr . wt ) was frequency dependent as predicted in Equation 10 and declined with increasing frequency . Strikingly , the model presented here fit the observed data very well ( least-squares best-fit; F1 , 4 = 346 . 1 , p = 0 . 0003 ) and shows that the model not only successfully predicts general patterns but can also generate quantitative predictive data with some precision . Although fitness was frequency dependent , the model best fit and the fixed fitness model were statistically indistinguishable ( least-squares best-fit; F1 , 4 = 409 . 8 , p = 0 . 0003 ) . The spore allocation of each genotype ( aij ) in every pair was calculated in the same way as described above with the mutant and wild type ( Equation 11 . 2 ) , using the estimates for ri and si for the natural isolates ( Figure 4E and 4F ) . So that the expected chimeric behavior generated from the model could be directly compared to the observed behavior [1] , aij was calculated when genotypes were in equal proportions only . Facultative change was calculated using Equation 12 , where a value greater than zero means that a genotype increased its spore allocation in chimera ( i . e . it self-promoted ) and a value less than zero means that the genotype's spore allocation decreased in chimera ( i . e . it was coerced ) . We found the model's predicted social behavior to be highly correlated with observed data ( Figure 4H; Pearson correlation: r18 = 0 . 8924 , p<0 . 001 ) [1] .
Despite the appearance of cooperation in nature , selection should often favor exploitative individuals who perform less of any cooperative behaviors while maintaining the benefits accrued from the cooperative behavior of others . This conflict of interest among cooperating individuals can lead to the evolution of complex social strategies that depend on the identity ( e . g . genotype or strategy ) of the individuals with whom you interact . The social amoeba Dictyostelium discoideum provides a compelling model for studying such “partner specific” conflict and cooperation . Upon starvation , free-living amoebae aggregate and form a fruiting body composed of dead stalk cells and hardy spores . Different genotypes will aggregate to produce chimeric fruiting bodies , resulting in potential social conflict over who will contribute to the reproductive sporehead and who will “sacrifice” themselves to produce the dead stalk . The outcomes of competitive interactions in chimera appear complex , with social success being strongly partner specific . Here we propose a simple mechanism to explain social strategies in D . discoideum , based on the production of and response to stalk-inducing factors , the social signals that determine whether cells become stalk or spore . Indeed , measurements of signal production and response can predict social behavior of different strains , thus demonstrating a novel and elegantly simple underlying mechanistic basis for natural variation in complex facultative social strategies . This suggests that simple social rules can be sufficient to generate a diverse array of behavioral outcomes that appear complex and unpredictable when those rules are unknown .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "dictyostelium", "discoideum", "model", "organisms", "protozoan", "models", "biology", "evolutionary", "biology", "microbiology", "evolutionary", "genetics" ]
2011
A Simple Mechanism for Complex Social Behavior
Regenerating tissue must initiate the signaling that drives regenerative growth , and sustain that signaling long enough for regeneration to complete . How these key signals are sustained is unclear . To gain a comprehensive view of the changes in gene expression that occur during regeneration , we performed whole-genome mRNAseq of actively regenerating tissue from damaged Drosophila wing imaginal discs . We used genetic tools to ablate the wing primordium to induce regeneration , and carried out transcriptional profiling of the regeneration blastema by fluorescently labeling and sorting the blastema cells , thus identifying differentially expressed genes . Importantly , by using genetic mutants of several of these differentially expressed genes we have confirmed that they have roles in regeneration . Using this approach , we show that high expression of the gene moladietz ( mol ) , which encodes the Duox-maturation factor NIP , is required during regeneration to produce reactive oxygen species ( ROS ) , which in turn sustain JNK signaling during regeneration . We also show that JNK signaling upregulates mol expression , thereby activating a positive feedback signal that ensures the prolonged JNK activation required for regenerative growth . Thus , by whole-genome transcriptional profiling of regenerating tissue we have identified a positive feedback loop that regulates the extent of regenerative growth . The capacity to regenerate damaged or lost organs or limbs is significantly greater in some animals than others . The use of model organisms with varying degrees of regenerative capacity , from whole-body regeneration in planaria and hydra , to limb regeneration in amphibians , organ and fin regeneration in zebrafish , and the limited tissue regeneration that occurs in mammalian models , has advanced our understanding of this process [reviewed in 1] . The complementary tools available in different model organisms has enabled identification of conserved mechanisms and signaling pathways that are used in many regeneration contexts , such as WNT signaling [2–8] , Receptor Tyrosine Kinase ( RTK ) signaling [9–16] , Hippo signaling [17–22] , and Jun N-terminal Kinase ( JNK ) signaling [23–25] , as well as clear differences in regenerative mechanisms among organisms and tissues [26 , 27] . Assessing changes in gene expression in regenerating tissue is a powerful approach to identifying essential regeneration genes . Model organisms that are amenable to mutagenesis , transgenics , or RNAi-mediated gene knockdown also enable functional studies based on the results of transcriptional profiling . For example , analysis of the transcriptome of the cricket leg blastema identified upregulation of components of the Jak/STAT signaling pathway , which , when knocked down by RNAi , resulted in impaired leg regeneration [28] . The transcriptome from the anterior of the planarian Procotyla fluviatilis , which is capable of regeneration after amputation , was compared to the transcriptome from posterior areas of the planarian body that are incapable of regeneration , identifying upregulation of several WNT ligands and receptors after amputation in the tissue that does not regenerate . RNAi knockdown of the WNT effector β-catenin restored regenerative capacity to the posterior of the animal [29] . In zebrafish , genes regulating anterior-posterior patterning during fin regeneration were identified through transcriptional profiling of anterior and posterior portions of the blastema . Overexpression of one of these genes , hand2 ( SO:0000704 ) , affected patterning but not growth during regeneration [30] . Thus , transcriptional profiling followed by functional analysis is an effective approach to identification and validation of regeneration genes . Drosophila melanogaster is one of the most powerful model organisms for genetic and functional analysis of genes . Furthermore , Drosophila imaginal discs , the epithelial structures in the larva that will form the adult animal during metamorphosis , have been an important model system for tissue repair and regeneration for over 60 years [reviewed in 31] . This structure is a simple epithelium that contains complex patterning and determined cell fates . While classic imaginal disc regeneration experiments involved removal of the tissue from the larva before wounding and culturing in the abdomen of an adult host , the development of systems that use genetic tools to induce tissue ablation in situ has enabled high-throughput experimental approaches such as genetic screens [6 , 32] . In both methods of inducing damage , the tissue undergoes wound closure and forms a regeneration blastema , or zone of proliferating cells near the wound [6 , 32–35] . In addition , both methods of inducing damage activate signaling through the Wingless and JNK pathways [6 , 23 , 32 , 36–38] . Previous studies have identified genes differentially expressed during imaginal disc regeneration . Blanco et al . cut imaginal discs and then cultured them in the abdomens of adult female flies , before recovering the discs at various time points during regeneration for microarray analysis [39] . This study used the entire imaginal disc for the microarrays , including tissue not contributing to the blastema . To restrict their analysis to cells near the wound site that were contributing to regeneration , Katsuyama et al . similarly cut and cultured discs , but used GFP-labeling of cells with activated JNK signaling to mark the regeneration blastema for dissection prior to microarray profiling [40] . Together these studies used transcriptional profiling to identify several regeneration genes and mechanisms . However , they used relatively small numbers of cells from few regenerating discs due to the technical challenges inherent in the culture technique . Furthermore , culturing itself may induce high levels of stress in the tissue that may alter the transcriptional profile . We sought to generate a complete and accurate transcriptional profile of regenerating imaginal disc tissue using deep-sequencing techniques and avoiding ex vivo culture and microdissections . Induction of tissue ablation using genetic tools enables regeneration to proceed in vivo as it would if the tissue were to be damaged by a predator or parasite in the wild . Furthermore , use of a genetic tissue-ablation system facilitates ablation and regeneration of hundreds of imaginal discs simultaneously , enabling collection of sufficient material for mRNA-seq without needing amplification . Finally , functional validation of the differentially expressed genes can be carried out by quantifying the extent and quality of regeneration after in situ tissue ablation in mutants . Here we report the transcriptional profile of the regeneration blastema after ablation of the wing pouch in the Drosophila wing imaginal disc during the peak of regenerative growth . We have used a method that optimizes our ability to isolate fluorescently labeled blastema cells rapidly and efficiently from the disc [41] , enabling collection of material for mRNA-seq . Furthermore , we have functionally validated several of the genes that are differentially expressed during regeneration as novel regulators of regeneration . Importantly , we have identified the mechanism through which regeneration signaling is sustained to ensure regrowth . This mechanism involves a positive feedback loop that requires the DUOX-maturation factor NIP , which is encoded by the gene moladietz ( mol ) ( FBgn0086711 ) [42] . The JNK signaling pathway , which is essential for regeneration [23] and is activated by ROS at the damage site [43] , also upregulates mol , which activates Duox , thereby sustaining production of ROS and JNK signaling . This positive feedback loop sustains the regenerative response for several days after tissue damage . Thus , by whole-genome transcriptional profiling of regenerating tissue we have identified the changes in gene expression that control a key regulatory mechanism of regenerative growth . We induced ablation of most of the primordial wing by expressing the pro-apoptotic gene reaper ( rpr ) ( FBgn0011706 ) [44] in the expression domain of the wing-patterning gene rotund ( rn ) ( FBgn0267337 ) [45] , which comprises most of the wing pouch region of the wing imaginal disc , via rnGAL4 , UASrpr [6] ( Fig 1A and 1B ) . To control the onset and completion of tissue ablation temporally , we used temperature shifts to regulate the temperature-sensitive repressor Gal80ts [46] . We expressed rpr in the wing primordium for 24 hours at the beginning of the third larval instar , which removed most of the rn-expressing cells by the end of ablation to a reproducible extent ( Recovery time 0 hrs or R0 ) ( Fig 1B ) ( S1 Fig ) . Wing pouch cells express the wing determinant nubbin ( nub ) ( FBgn0085424 ) during both normal development and regeneration [6 , 47] . Thus , nub expression was a convenient way to label blastema cells in these damaged discs as well as control cells in undamaged discs . To label the regeneration blastema cells , we identified a publicly available MiMIC transposon insertion that expresses GFP under the control of the nub locus [48] . Expression of GFP via this insertion occurs in the same cells that are immunostained with an anti-Nub antibody ( Fig 1C ) [41 , 47] . The wing primordium continues to express the nub-GFP after ablation and throughout different stages of regeneration ( Fig 1D–1F ) . The GFP-expressing cells also encompass the regeneration blastema at R24 as marked by EdU incorporation ( Fig 1G ) , confirming its suitability as a marker for blastema and control wing pouch cells . To identify the differentially expressed genes in the blastema , we carried out transcriptional profiling of the GFP-labeled and isolated blastema cell population from R24 wing imaginal discs ( Fig 1H ) . The R24 time point was chosen as it shows a clear blastema , whereas at earlier time points some discs had not yet formed the blastema , and at later time points some discs were beginning to repattern the regrown tissue . Dissociation and fluorescence–activated cell sorting ( FACS ) of imaginal disc cells is a well-established but lengthy procedure that may affect gene expression and cell viability [49 , 50] . We therefore optimized our cell dissociation process so that it was rapid and gentle , taking approximately 15 minutes , to minimize changes in transcription and loss of cell viability due to the manipulation of the tissue [41] . We have previously confirmed the accuracy of the sorting by using qPCR to measure expression of pouch and non-pouch genes in the sorted cells [41] . After using this protocol to dissociate and sort regeneration blastema cells and control wing pouch cells , mRNA was prepared and pooled such that each biological replicate produced sufficient mRNA for deep sequencing ( Fig 1H ) . To identify genes that are differentially expressed during imaginal disc regeneration , we collected three independent samples of nub-GFP-expressing blastema cells from regenerating discs and three independent samples of nub-GFP-expressing cells from undamaged ‘mock-ablated’ control discs after 24 hours of recovery from the thermal shift ( R24 ) . While the mock-ablated controls were taken through the thermal shift , they lacked UAS-rpr so did not ablate any tissue . Through deep sequencing we obtained approximately 27 million reads per replicate . Reads were aligned using Tophat2 [51 , 52] against the Drosophila melanogaster genome ( NCBI , build 5 . 41 ) . A total of 3 , 798 differentially expressed genes ( p<0 . 05 ) were identified using Cuffdiff [51] , with a false discovery rate of 0 . 05 . While a log2 fold change of 1 . 5 is often set as an arbitrary cutoff threshold for differentially expressed genes , our transcriptional profile showed a log2 fold change of 1 . 3 for the gene puckered ( FBgn0243512 ) , which is the phosphatase that is both a target and a negative regulator of JNK signaling in the regeneration blastema [23 , 53] , prompting us to set our cutoff at 1 . 3 . Thus , by selecting a cutoff of log2 fold change ≥ 1 . 3 or ≤ -1 . 3 , p<0 . 05 , we have identified 660 statistically significant differentially expressed genes , 504 of which are upregulated and 156 of which are downregulated in the regeneration blastema ( S1 and S2 Tables ) . Several genes previously identified as imaginal disc regeneration genes were upregulated in our transcriptional profile , including dilp8 [54] , rgn and mmp1 [55] , puckered [23] , and myc [6] . In addition , we found some overlap between our gene list and the differentially regulated genes noted in two previously reported transcriptional profiles of regenerating imaginal discs ( S2 Fig ) [39 , 40] . We compared the genes that were at least log2 1 . 3-fold up- or down-regulated in our dataset and those similarly at least 1 . 3-fold up- or down-regulated in the microarray analysis of posterior regenerating tissue 24 hours after damage presented in Katsuyama et al . , in which they cut and cultured imaginal discs , and used GFP-labeling of cells with activated JNK signaling to mark the regeneration blastema for dissection prior to microarray profiling [40] . There were 32 differentially expressed genes in common with this report ( S2 Fig ) . This profile led them to explore the role of JAK-STAT signaling in disc regeneration [40] . Importantly , we also identified the JAK/STAT signaling ligand upd/os ( FBgn0004956 ) as highly upregulated in the regenerating blastema . We also compared the genes that were at least log2 1 . 3-fold up- or down-regulated in our dataset and those listed as similarly up- or down-regulated in the figures and tables reporting the microarray analysis of whole regenerating discs 24 hours after damage presented in Blanco et al . , as the whole list of 1 , 183 genes they identified as differentially expressed was not published [39] . There were 10 differentially expressed genes in common with this report ( S2 Fig ) . For this analysis , they cut and cultured imaginal discs , and used whole discs for microarray profiling [39] . The minimal overlap with previous studies may be due to several factors , including differences in method of wounding ( cut vs . tissue ablation ) , the discs used ( leg vs . wing ) , regeneration conditions ( culture vs . in situ ) and method of transcriptional profiling ( microarray using few discs/blastemas vs . mRNA-seq using cells isolated from hundreds of blastemas ) . Furthermore , we have set a 1 . 3-fold threshold to define differentially expressed genes , and a reduction in this threshold would identify more overlap among these three studies . Strikingly , only one gene was upregulated in all three transcriptional profiles when using the 1 . 3-fold threshold: yellow-b ( FBgn0032601 ) , which is a target of JNK signaling during dorsal closure [56] . Therefore , the current transcriptional profile will enable the study of previously unidentified regeneration genes and pathways . To confirm that our transcriptional profile identified genes that were indeed differentially regulated in the imaginal disc blastema , we used antibodies , enhancer-trap lines , and protein-trap lines to visualize gene expression in undamaged and damaged wing discs . The “undamaged” control discs depict the expression of these genes during normal development . Of the 22 genes we tested , 16 ( 73% ) were differentially expressed as predicted . Validated upregulated genes were Alkaline phosphatase 4 ( Alp4/Aph4 ) ( FBgn0016123 ) [57] , Atf3/A3-3 ( FBgn0028550 ) [58] , chronologically inappropriate morphogenesis ( chinmo ) ( FBgn0086758 ) [59] , Ets21C ( FBgn0005660 ) [60] , and moladietz ( mol ) [42] ( Fig 2A–2E ) . Other genes had expression patterns that changed from ubiquitous to restricted to the blastema , such as fruitless ( fru ) ( FBgn0004652 ) [61] , LaminC ( FBgn0010397 ) [62] , AdoR ( FBgn0039747 ) [63] , and kayak ( kay ) ( FBgn0001297 ) [64] ( Fig 2F and 2G , S3 Fig ) . A third class of genes showed strong upregulation around the blastema and slight upregulation in the blastema including pickled eggs ( pigs ) ( FBgn0029881 ) [65] and a reporter for Stat92E ( FBgn0016917 ) activity that reflects upd-stimulated signaling [66] ( Fig 2H and 2I ) . The genes Thor ( FBgn0261560 ) [67] , corto ( FBgn0010313 ) [68] , Nlaz ( FBgn0053126 ) [69] , twist ( twi ) ( FBgn0003900 ) [70] , and zfh1 ( FBgn0004606 ) [71] showed upregulation in the transcriptional profile but did not show elevated expression with antibody staining ( twist ) or enhancer-trap expression ( zfh1 , Thor and Nlaz ) or protein-trap expression ( corto ) ( S3 Fig ) . Some of these genes may be upregulated in the transcriptional profile if , in the course of regeneration , hinge cells convert to pouch cells and begin expressing nub while still expressing some hinge-specific genes such as zfh1 . Such hinge-to-pouch conversion has been reported during compensatory proliferation [72 , 73] , and gene expression in these transitioning cells may still be important for regeneration . We also confirmed three of the upregulated genes using qPCR of whole wing discs ( S3 Fig ) . While whole-disc qPCR often fails to detect differences in expression that occur only in the blastema , because the blastema consists of very few cells relative to the rest of the disc , changes in expression of genes that are largely not expressed in the disc prior to damage , such as puckered , can be observed [74] . Thus , we further validated the upregulation of Ets21C , mol , and Nox as representatives of the differentially expressed genes ( S3 Fig ) . Validated downregulated genes were defective proventriculus ( dve ) [75] , Hormone receptor 78 ( Hr78 ) ( FBgn0015239 ) [76] , NC2β ( FBgn0028926 ) [77] , smooth ( sm ) ( FBgn0003435 ) [78] , and Catalase ( Cat ) ( FBgn0000261 ) [79] ( Fig 3 ) . Thus , this transcriptional profile successfully identified genes that are differentially expressed in the regeneration blastema that forms after mass tissue ablation . A strong advantage to using a genetically tractable model organism is the ability to assess the functional role of genes of interest that are identified in a transcriptional profile . To assess regenerative capacity in the Drosophila imaginal wing , we induced tissue ablation as described above in animals that were heterozygous mutant for the gene in question . The regenerating animals were then allowed to develop to adulthood , and wing size was measured to assess the extent of regeneration . To measure a population of these wings efficiently , they were sorted into classes that were approximately <25% , 25% , 50% , 75% , and 100% the size of a normal wing ( Fig 4A ) . The distribution of mutant regenerated wings in these classes was then compared to the distribution of regenerated wings generated by control animals . With our system , we observe some heterogeneity in the extent of regeneration within a genotype and also between control experiments conducted at different times . The variation within each genotype was due to variation in each individual animal’s time to pupariation , with animals that had longer to regenerate having larger wings ( S1 Fig ) [6] . Variation between experiments was due to changes in environmental conditions such as humidity and food quality [74 , 80 , 81] . Despite this apparent heterogeneity , we find reproducible differences between mutant and control animals using this method of screening and have successfully identified genes that regulate specific aspects of regeneration [6 , 74 , 81 , 82] . Using this method , we tested available mutants in genes that were strongly upregulated after tissue damage . Twelve out of 16 or 75% of the genes we tested showed a regeneration phenotype , which is unsurprising given that not all important regeneration genes will have a phenotype when only heterozygous mutant , and not all differentially expressed genes will be essential for regeneration . One example of an upregulated gene that was required for regeneration is Ets21c , which encodes a transcription factor that is a known target of JNK signaling and is important for JNK activity in the innate immune response [83] , during tumor formation [84 , 85] and at epidermal wounds [86] . After ablation and regeneration of the imaginal tissue , adult wings in Ets21cf03639/+ animals were smaller than controls ( Fig 4B ) . A second example of an upregulated gene that was required for regeneration is CG9336 ( FBgn0032897 ) , which is annotated in the Drosophila genome and has closely related homologs in other Drosophila species but not in vertebrates , and does not appear to have protein domains of known function . After ablation and regeneration of the wing primordium in CG9336MI03849/+ animals , the resulting adult wings were smaller than controls , indicating a requirement for this gene during regeneration ( Fig 4C ) . Additional genes required for regeneration included alkaline phosphatase 4 ( Alp-4 ) [57] , the 4E-BP gene Thor [67] , moladietz ( mol ) [42] , as well as the collagen components Collagen type IV alpha 1 ( Col4a1/Cg25C ) ( FBgn0000299 ) [87] and viking ( vkg ) ( FBgn0016075 ) [88] ( Fig 4D–4G ) . Interestingly , several of the mutants tested did not have the predicted effect on regeneration . Rather than leading to poor regeneration , mutations in a subset of upregulated genes enhanced regeneration when heterozygous . These genes included heartless ( htl ) ( FBgn0010389 ) [89] , and fru [61] when assessed in males ( S4 Fig ) . After ablation and regeneration , wing sizes in these mutants were larger than control wings . The mechanisms through which these genes restrict regeneration are not yet understood . To identify the biological processes that might be affected during regeneration we carried out gene ontology ( GO ) enrichment analysis . Transcripts that were significantly upregulated or downregulated were analyzed according to GO categories using DAVID v6 . 7 [90 , 91] . Representative GO terms from the most significantly enriched GO clusters describing biological processes are listed in Table 1 . Terms that were enriched among the upregulated genes included imaginal disc development and imaginal disc pattern formation , likely because the regenerating tissue was rebuilding what had been ablated . The enrichment of GO terms cell morphogenesis , tissue morphogenesis , cell adhesion , morphogenesis of an epithelium , and cell migration may occur because the cells at the wound edge change shape in order to close the wound [32] . In addition , discontinuity in marked clones in regenerating tissue suggests that cells intercalate and shift relative to each other during imaginal disc regeneration [92] . The GO term regulation of transcription likely contains transcription factors necessary for carrying out the regeneration program , as well as the development and patterning of the regenerating tissue . Interestingly , the GO term open tracheal system development was highly enriched . Two possible reasons for this apparent enrichment include contamination of our sorted cells with tracheal cells , or upregulation in the blastema of the same RTK signaling pathway genes that play critical roles in tracheal system morphogenesis , as has been observed in compensatory proliferation [93] . Another highly enriched GO cluster included the terms negative regulation of cell differentiation , regulation of cell fate commitment , and regulation of cell fate specification . Interestingly , we and others have shown that imaginal disc damage causes a transient loss of markers of cell-fate specification [6 , 94] . Many of the biological process GO terms enriched among the downregulated genes describe general cellular processes , including intracellular transport and vesicle-mediated transport , RNA processing , and catabolism . Interestingly , several classes of genes that affect cellular metabolism were downregulated , including the GO terms mitochondrial ATP synthesis coupled electron transport , acetyl-CoA metabolic process , tricarboxylic acid cycle , and aerobic respiration . While a transcriptional profile of the Xenopus tropicalis tadpole tail regenerative bud has similarly suggested changes in cellular metabolism after tissue damage [95] , a broad , functional role for cell-autonomous changes in oxidative phosphorylation , glycolysis or other cellular energetics during regeneration has yet to be demonstrated . An additional downregulated GO category was cell redox homeostasis , suggesting changes in levels of enzymes that regulate Reactive Oxygen Species ( ROS ) in the regeneration blastema . Indeed , ROS provide important signaling in other model systems of wound healing and regeneration [reviewed in 96] . For example , ROS serve as an attractant for immune cells in larval zebrafish tails after amputation [97] and in Drosophila cuticle wounds [98] , and are required for proliferation and regeneration after Xenopus tadpole tail amputation [99] as well as fin and axon regrowth after zebrafish tail amputation [100 , 101] . Furthermore , ROS stimulate JNK signaling in regenerating zebrafish fins and Drosophila imaginal discs [43 , 102 , 103] . During wing imaginal disc regeneration ROS are released by the dying cells , and then taken up by the living cells at the wound edge immediately after physical damage or induction of tissue ablation [43] . However , the extent to which ROS are produced and propagated in the regeneration blastema , as well as the mechanism that underlies ROS production in the regrowing tissue , are unclear . We examined the expression of genes that regulate ROS production and removal in our transcriptional profile of the imaginal disc regeneration blastema , and found that in addition to the downregulated genes identified by the GO analysis , there were also ROS-regulating factors among the upregulated genes ( Table 2 ) . Drosophila has two NADPH oxidases that produce ROS , NADPH Oxidase ( Nox ) ( FBgn0085428 ) and Dual oxidase ( Duox ) ( FBgn0283531 ) [104–107] . Interestingly , Nox expression was upregulated , while Duox expression remained unchanged . However , the Duox-maturation factor DUOXA/NIP , which is encoded by the gene moladietz ( mol ) [42] , showed a high level of induction after damage , representing one of the strongest hits in the profile . To reduce ROS , superoxide and hydrogen peroxide are scavenged by superoxide dismutases ( Sods ) and Catalase ( Cat ) , respectively . Expression of the CuZn-dependent cytoplasmic Sod1 ( FBgn0003462 ) [108] and the Mn-dependent mitochondrial Sod2 ( FBgn0010213 ) [109] was reduced in the regeneration blastema , while the extracellular Sod3 ( FBgn0033631 ) [110] remained unchanged . Furthermore , expression of Cat [79] was strongly reduced . Thus , generation and propagation of ROS in the regeneration blastema could be explained in part by transcriptional upregulation of Nox and mol/NIP , and downregulation of Sod1 , Sod2 , and Cat . While regenerating zebrafish tails exhibit ROS production for at least 24 hours after amputation [102] , and Xenopus tadpole tails produce ROS for days after amputation [99] , ROS production in damaged wing discs has only been assessed for 30 minutes after physical damage and 11 hours after induction of tissue ablation [43] . To determine whether ROS persist in regenerating wing discs , we used dihydroethidium ( DHE ) staining to detect ROS . Importantly , we observed DHE fluorescence in the cellular debris and in the regeneration blastema at R24 ( Fig 5A and 5B ) and R48 ( Fig 6F ) . We confirmed this finding with the ROS detector H2DCFDA ( S6 Fig ) . Thus , ROS persist in the living , regenerating cells for at least 24 hours after the completion of tissue ablation , suggesting an active mechanism that sustains the production of ROS in the regenerating tissue . To determine the extent to which changes in ROS levels impact regeneration , we overexpressed Sod1 , Sod2 , or Cat in ablated discs using a UAS-Sod1 [111] , UAS-Sod2 [112] , or UAS-Cat [113] transgene under the control of rn-GAL4 , which induced expression in the ablated tissue as well as in the few surviving rn-expressing cells that contributed to the blastema . This limited overexpression was intended to reduce ROS levels in the debris and partially reduce ROS levels in the blastema , as not all blastema cells expressed the transgenes . According to a prior report , similar overexpression of Sod1 or Cat individually or together reduced the ability of wing discs to recover from tissue ablation [43] . In our ablation system , overexpression of Sod1 or Sod2 during ablation similarly led to smaller adult wings compared to controls , although overexpressing Cat alone did not , confirming that manipulation of levels of ROS-regulating enzymes impact regeneration ( Fig 5C and 5D ) . This reduction in regeneration was likely due to a combination of reduced regenerative growth , as UAS-Sod1 regenerating wing primordia lagged behind controls in size ( Fig 5E–5I ) , and reduced time for regeneration , as UAS-Sod1 regenerating animals failed to delay pupariation in response to the tissue damage as long as the controls ( Fig 5J and 5K ) . The damaged discs with transiently overexpressed Sod1 also had reduced JNK signaling at R24 , as observed by expression of the TRE-red transcriptional reporter for JNK pathway activity [114] ( Fig 5L–5P ) . In damaged eye imaginal discs , ROS recruit hemocytes to the site of damage , which then stimulate JNK signaling in the recovering epithelium [103] . To determine whether hemocytes are recruited to the wing disc in response to ablation of the rn-expressing domain , we observed hemocytes using Hemolectin-RFP ( FBgn0029167 ) [115] and anti-Nimrod ( FBgn0259896 ) [116] . In control discs , small clusters of hemocytes were observed in the folds of 1 of 15 discs ( S5 Fig ) . In damaged and regenerating tissue , clusters of hemocytes were observed in 4 of 15 discs along the peripodial epithelium . These hemocytes were present in close proximity to the debris , but were not in direct contact with the debris , which was trapped between the two epithelial layers ( S5 Fig ) . Thus , in contrast to the eye disc , recruiting hemocytes is unlikely to be the main mechanism through which ROS induce JNK signaling in the wing disc . The striking upregulation of mol in the regeneration blastema by R24 and its continued expression through R48 ( Fig 2E , S8 Fig ) suggested that its protein product NIP may have an important role in regulating regeneration . Importantly , mol is normally expressed at low levels in the wing disc during development ( Fig 2E , S6 Fig ) . The vertebrate homolog of NIP , DUOX maturation factor ( DUOXA ) ( HGNC:26507 ) , is essential for moving DUOX through the endoplasmic reticulum and the golgi to the cell surface [117] . Once at the cell surface , DUOXA remains in a stable complex with DUOX and enhances the rate and specificity of ROS production [118] . Thus , transcriptional regulation of mol could have a profound effect on ROS production in the regenerating epithelium . To determine the extent to which the transcriptional upregulation of mol promotes ROS production in the blastema , we assessed ROS levels in heterozygous mol null mutant animals . Duox can produce both hydrogen peroxide and superoxide [118] . As DHE was the reagent that worked best in imaginal discs ( Fig 5A and 5B , S6 Fig ) , we used it as a representative assay for overall ROS levels . Interestingly , production of ROS in both the cellular debris and the regeneration blastema was significantly reduced in the mole02670/+ damaged discs ( Fig 6A–6F ) , indicating that mol is required for overall ROS production after tissue damage . To confirm that the response to ROS is reduced in the mole02670/+ regenerating tissue , we assessed expression of a reporter transgene , gstD1-GFP ( FBgn0001149 ) , that responds to ROS-induced activation of transcription [119] . Interestingly , gstD1-GFP expression was significantly reduced in the mutant regeneration blastemas , but not until two days after tissue damage ( Fig 6G and 6H; S6 Fig ) . Our initial genetic assay showed that NIP was required for regeneration ( Fig 4F ) . To quantify the effect of reduction of NIP further , we measured adult wing size in mole02670/+ females and males after imaginal disc ablation and regeneration . Importantly , while normal wings were the same size in controls and mole02670/+ animals , regenerated mole02670/+ wings were significantly smaller than regenerated controls , indicating that regeneration in these mole02670/+ animals was impaired ( Fig 6I ) . To confirm the requirement for mol we also quantified regeneration using discs expressing molRNAi in the regenerating wing pouch using a UAS-molRNAi transgene . While such RNAi expression was limited temporally and spatially , we have found it to be effective at generating phenotypes in our system [74] , possibly due to the propagation of knockdown after limited RNAi expression observed in imaginal discs [120] . Importantly , discs expressing molRNAi also regenerated worse than controls as assessed by adult wing size ( S6 Fig ) . To understand how reduced expression of mol impairs regeneration , we monitored regrowth of the ablated tissue by measuring the area of the wing primordium at specific times after the completion of ablation . We found that mole02670/+ regenerating discs were slightly smaller than controls beginning in early regeneration , and significantly lagged behind controls in size by two days after tissue damage ( Fig 6J–6P ) . Given that the difference in regrowth was more apparent later in regeneration , we speculated that reduction of NIP levels might be particularly important for the later stages of regeneration . Indeed , expression of the growth-promoter Myc ( FBgn0262656 ) , which is important for regenerative growth [6] was comparable to controls at R24 but reduced at R48 ( S6 Fig ) . Because ROS stimulate JNK signaling in damaged imaginal discs [43] , we examined JNK signaling levels in mole02670/+ regenerating discs . Importantly , expression of the JNK signaling reporter TRE-red , which reflects the activity of the AP-1 transcriptional complex , was slightly reduced during early and mid regeneration ( R0 , R24 , and R48 ) and markedly reduced during the late stages of regeneration in mole02670/+ discs ( R72 ) ( Fig 7A–7J ) . To determine whether increasing JNK signaling could compensate for the reduction of NIP levels and ROS production , we examined adult wings after damage and regeneration in animals heterozygous mutant for both mol and the negative regulator of JNK signaling puckered ( puc ) [53] . These mole02670/+; pucE69/+ regenerated wings were significantly larger than the mole02670/+ regenerated wings , indicating that increased JNK signaling could bypass the requirement for mol and rescue the poor regeneration phenotype of the mole02670/+ mutants ( Fig 7K ) . Thus , upregulation of mol is required for ROS propagation in the regeneration blastema and for sustaining JNK signaling , particularly during the later stages of regeneration . The importance of the Duox-maturation factor in regeneration implies that Duox itself is also important for regeneration , even though it is not transcriptionally upregulated according to our profile . To assess the importance of Duox , we quantified regeneration in UAS-DuoxRNAi animals . Indeed , wing discs expressing DuoxRNAi regenerated poorly compared to control animals ( S7 Fig ) . Another important regulator of ROS that was upregulated in the transcription profile is the NADPH oxidase Nox . To determine whether Nox is also required for wing disc regeneration , we compared adult wings after damage and regeneration in control animals and animals heterozygous for a Nox mutant ( NoxMI15634 ) or expressing NoxRNAi . Interestingly , both the Nox mutation and the NoxRNAi caused improved regeneration as assessed by adult wing size ( S7 Fig ) . To understand why reduction of Nox led to enhanced regeneration , we assessed pouch size throughout regeneration and rate of pupariation . Interestingly , wing discs with reduced Nox regrew at the same rate as control discs through R48 , and pupariation timing was not altered ( S7 Fig ) . Thus , the constraint Nox places on regeneration must occur after R48 , possibly during the pupal phase . These results suggest that the ROS produced by Nox and by the Duox/NIP complex are likely functionally , spatially , or temporally different , with Nox-produced ROS acting to inhibit regeneration during the pupal phase . Given that mol upregulation after tissue damage was important for ROS production in the regenerating epithelium and sustained regenerative signaling , we wanted to identify the upstream signal that regulates mol expression . We hypothesized that regeneration signaling itself , specifically JNK signaling , could induce the upregulation of mol . Canonical JNK signaling acts through the transcription factor AP-1 , which is a heterodimer of Jun ( FBgn0001291 ) and Fos ( FBgn0001297 ) [121] . Downstream genes are regulated through AP-1 binding to the conserved TPA-responsive element ( TRE ) sequence ( TGAC/GTCA ) [122] . Indeed , there are three consensus TRE sites at the mol locus: one 2 Kb upstream of the transcription start site , one in the first intron , and one in the fifth intron ( Fig 8A ) . To determine the extent to which JNK signaling is required for mol expression after tissue damage , we inhibited JNK signaling by expressing a dominant-negative JNK ( UAS-JNKDN ) ( FBgn0000229 ) [123] under the control of rn-GAL4 during wing pouch ablation . Interestingly , expression of the reporter mol-lacZ was significantly decreased upon reducing JNK signaling through UAS-JNKDN ( Fig 8B–8D ) , suggesting that JNK signaling is important for mol upregulation after tissue damage . To confirm this finding , we also examined mol-lacZ expression in regenerating wing discs that were heterozygous mutant for hemipterous ( hep ) ( FBgn0010303 ) , which encodes a JNK kinase [124] . Expression of the mol-lacZ reporter was also significantly decreased in female hepr75/+ regenerating wing discs ( Fig 8E and 8F ) . Thus , JNK regulation of mol expression constitutes a positive feedback loop that sustains JNK signaling . ROS activates both JNK and p38a ( FBgn0015765 ) in the regenerating wing disc [43] . To determine whether p38a signaling also induces a positive feedback loop through mol , we examined mol-lacZ expression in regenerating discs that were heterozygous mutant for p38a1 . Interestingly , reduction of p38a did not affect mol-lacZ expression ( S8 Fig ) . Thus , JNK signaling is required for upregulation of mol expression after tissue damage , which is in turn required for sustaining ROS production in the regenerating epithelium and maintaining JNK signaling during late regeneration ( Fig 8G ) . This work has identified a novel mechanism that sustains regeneration signaling and ensures that regrowth of damaged tissue continues beyond the initial burst of damage signaling . While elevated ROS levels are sustained in other regeneration models such as amputated zebrafish fins and Xenopus tails , where they promote signaling and the later stages of regenerative growth [99 , 100 , 102] , the mechanism through which elevated ROS levels are maintained has remained elusive . Our work has provided insight into this puzzle in Drosophila by discovering a key positive feedback loop that uses JNK-induced upregulation of the Duox-maturation factor encoded by mol to sustain ROS production , JNK signaling , and late regeneration . Similar damage-induced regulation of the Duox-maturation factor may facilitate long-term regeneration signaling in many animals . We were able to identify this mechanism through generation of a transcriptional profile of actively regenerating tissue , made possible by our genetically induced tissue ablation system [6] and our technical advances enabling isolation of sufficient numbers of blastema cells [41] . This is the first report of upregulation of a Duox maturation factor as a key aspect of the regeneration response . Other cellular functions that are regulated by DUOXA/NIP have only recently been identified . For example , DUOXA/NIP affects differentiation in murine skeletal muscle myoblasts [125] , murine thyroid hormone production and cerebellar development [126] , and the response to bacterial infections in the murine gut [127] , as well as development of the exoskeleton in C . elegans [128] , and recruitment of hemocytes to wounds in the Drosophila embryo epidermis and neutrophils to airways in mice [129 , 130] . Here we describe a role for mol during wing disc regeneration and show that while mol is transcriptionally upregulated , Duox levels do not change according to our transcriptional profile , indicating that fine-tuning of ROS levels can be achieved by changes in expression of the maturation factor rather than the enzyme itself . This regulative strategy may be deployed in many other cases in which ROS act as crucial signaling molecules . In addition to the transcriptional changes observed in regulators of ROS , many of the other changes in gene expression can be combined with our current understanding of tissue regeneration to identify novel and interesting relationships between developmental genes and signals and tissue regeneration . For example , our data indicated downregulation of the hormone receptor Hr78 in regenerating tissue . The expression of Hr78 in the wing disc appeared to be in some of the pro-vein regions ( Fig 3B ) . Tissue damage in the wing disc leads to a transient loss of cell-fate gene expression , including in the pro-veins , during regeneration [6 , 94] . Thus , Hr78 may be a novel wing vein fate gene whose expression is downregulated along with the other known vein fate genes after tissue damage . As an additional example , we observed differential regulation of various nuclear hormone receptor genes that are transcriptionally regulated by the hormone ecdysone [131] . Regenerating animals delay metamorphosis to accommodate regrowth of the damaged tissue by regulating ecdysone signaling , which controls developmental transitions [132] . Ecdysone targets that we found downregulated in regenerating wing discs include Hormone receptor 46 ( Hr46/Hr3 ) ( FBgn0000448 ) , Hormone receptor 4 ( Hr4/CG42527 ) ( FBgn0264562 ) , and Ecdysone-induced protein 78C ( Eip78C ) ( FBgn0004865 ) ( S2 Table ) . Interestingly , we also see upregulation of Cyp18a1 ( FBgn0010383 ) , a cytochrome P450 enzyme that exerts negative feedback regulation on ecdysone signaling by decreasing intracellular levels of ecdysone [133] . Thus , Cyp18a1 may be upregulated to ensure that ecdysone signaling stays low in the regenerating tissue to reinforce the developmental checkpoint induced by tissue damage . Regeneration involves orchestration of various cellular processes to repair and replace the damaged body part . It requires coordination of proliferation , growth , patterning , and changes in cell architecture and movement in a highly regulated manner . These dramatic changes could be coordinated by key transcription factors . Several transcription factors are differentially expressed in our profile , including chinmo , Ets21C , AP-2/TfAP-2 ( FBgn0261953 ) , fru , Atf3/A3-3 , dve and Blimp-1 ( FBgn0035625 ) . These transcription factors could lie at the center of regulatory networks that bring about key cellular changes . For example , Ets21C is a known downstream target of JNK signaling in wound healing [86] , and EGFR signaling in the intestinal stem cells [134] , and is also required as a co-factor for the JNK pathway transcription factor AP-1 in regulating transcriptional targets during tumor formation [84 , 85] . Thus , its expression in the regenerating wing disc could result from integration of multiple signals , and its requirement in regeneration may be due to its role in promoting expression of JNK targets . Further investigation into the mechanisms of these transcription factors will lead to a better understanding of regeneration . Regeneration is a tightly controlled process , requiring a balance between positive and negative regulators so that growth is stimulated but not deregulated . Indeed , our functional analysis demonstrated that several of the upregulated genes , including heartless and Nox , serve to restrict regeneration , as regeneration improved in heterozygous mutant animals . Therefore , functional analysis is critical for interpretation of gene expression data , as drawing conclusions based on differential expression alone can be misleading . Indeed , it was through functional analysis that we identified mol , and not Nox , as the critical regulator that promotes sustained ROS production and JNK signaling , completing the positive feedback loop that sustains regeneration . Further functional analysis of differentially expressed genes will likely reveal additional mechanisms that control tissue regeneration . Tissue ablation was carried out as described previously [6 , 82] using rnGal4 , UAS-rpr , and tubGAL80ts to regulate cell death spatially and temporally , with a thermal shift from 18° to 30° C for 24 hours during the early third larval instar . To synchronize development , eggs were collected for four hours on grape juice plates , first-instar larvae were collected shortly after hatching at two days after egg laying and transferred to vials , and the vials underwent the thermal shift at 7 days after egg laying , which was determined to be just after molting by counting mouth hooks . Flies were reared on standard molasses medium at 25° C except during regeneration experiments . The following Drosophila lines were obtained from the Bloomington Stock Center or were gifts as noted: w1118; rnGAL4 , UAS-rpr , tubGAL80ts/TM6B , tubGAL80 and w1118; rnGAL4 , tubGAL80ts/TM6B [6] , w1118; y1 , w*; Mi{MIC}nubMI05126 ( BL37920 ) [48] , y1 , w67c23; P{lacW}chinmok13009/CyO ( BL10440 ) [135] , y1 , w* Mi{MIC}pigsMI11007 ( BL56274 ) [48] , P{PZ}Alp407028 , ry506 ( BL12285 ) [135] , w1118; PBac{Ets21C-GFP . FLAG}VK00033/TM3 , Sb1 ( BL38639 ) , P{PZ}osp00865; ry506 P{PZ}zfh100856/TM3 , ryRK Sb1 Ser1 ( BL11515 ) [136] , y1 w67c23; P{lacW}molk11524a/CyO ( BL12173 ) [135] , ry506 P{PZ}fru3/MKRS ( BL684 ) [135] , w;;pBAC[atf3::EGFP]/TM6B ( gift from M . Uhlirova ) [137] , nlaZ:GFP[R2] ( gift from M . Ganfornina ) [69] , w1118; P{10xStat92E-GFP}1 ( BL26197 ) [66] , cn1 P{PZ}dve01738/CyO; ry506 ( BL11073 ) [135] , cn1 P{PZ}sm05338/CyO; ry506 ( BL11403 ) [78] , y1 w*; P{PTT-GB}LamCCB04957 ttvCB04957/SM6a ( BL51528 ) [138] , y1 w*; Mi{PT-GFSTF . 1}AdoRMI01202-GFSTF . 1/TM6C , Sb1 Tb1 ( BL60165 ) [139] , y1 w*; P{lacW}Thork13517 ( BL9558 ) [67] , y1 w*; Mi{PT-GFSTF . 0}kayMI05333-GFSTF . 0 ( BL63175 ) [139] , w1118; PBac{corto-GFP . FPTB}VK00037 ( BL42268 ) , w1118; PBac{Hr78-GFP . FLAG}VK00037 ( BL38653 ) , w1118;PBac{NC2β-GFP . FPTB}VK00033 ( BL56157 ) , y1 w*; Mi{PT-GFSTF . 0}CatMIO4522-GFSTF . 0 ( BL60212 ) [139] , HmlΔRFP ( gift from K . Bruckner ) [115] , TRE-red and gstD-GFP ( gifts from D . Bohmann ) [114] , Ets21Cf0369 ( BL18678 ) [140] , y1 w*; Mi{MIC}CG9336MI03849 ( BL36397 ) [139] , y1 w67c23; P{lacW}Col4a1K00405/CyO ( BL10479 ) [135] , y1 w67c23; P{lacW}vkgk00236 ( BL10473 ) [135] , P{PZ}Thor06270 cn1/CyO; ry506 ( BL11481 ) [141] , w1; P{UAS-Sod1 . A}B36 ( BL24754 ) , w1; P{UAS-CatA}2 ( BL24621 ) , w1; P{UAS-Sod2 . M}UM83 ( BL24494 ) , w1118; PBac{RB}mole02670/CyO ( BL18073 ) [140] , y1 sc* v1; P{TRiP . HMS02560}attP40 ( UAS-molRNAi ) ( BL42867 ) , y1 v1; P{TRiP . GL00678}attP40 ( UAS-DuoxRNAi ) ( BL38907 ) , y1 v1; P{TRIP . GL00678}attP40 ( UAS-NoxRNAi ) ( BL32902 ) , y1 w*; Mi{MIC}NoxMI15634/SM6a ( BL61114 ) [139] , pucE69 [53] , UAS-JNKDN [142] , w* hepr75/FM7C ( BL6761 ) [124] , w*; P{neoFRT}82B p38a1 ( BL8822 ) [143] . Immunostaining was carried out as previously described [6] . Anitbodies and dilutions used were Anti-Nubbin ( 1:500 ) ( gift of S . Cohen ) [47] , mouse anti-βgal ( 1:100 ) ( DSHB; 40-1a-s ) , rabbit anti-βgal ( 1:500 ) ( MP Biomedicals ) , mouse anti-GFP ( 1:10 ) ( DSHB 12E6 ) , rabbit anti-Myc ( 1:500 ) ( Santa Cruz Biotech d1-717 sc-28207 ) , rabbit anti-PH3 ( 1:500 ) ( Millipore ) , mouse anti-Nimrod ( 1:1000 ) ( gift from I . Ando ) [116] and anti-Twist ( 1:200 ) ( gift from A . Stathopoulos ) [144] . Alexa Fluor ( AF ) secondary antibodies from Molecular Probes were AF488 , AF555 and AF633 ( used at 1:500 ) . Nuclei were labeled with DAPI ( Sigma ) ( 1:5000 ) . EdU incorporation was carried out using the click-it EdU Alexa Fluor 594 Imaging kit ( Molecular Probes ) as previously described [145] . Samples were mounted in Vectashield ( Vector Labs ) . Immunostained samples were imaged on a Zeiss LSM 700 confocal microscope and images were processed using ZenLite , Adobe Photoshop , and Image J software . Bright-field imaging of adult wings was done on an Olympus SZX10 microscope using the CellSens Dimension software , and images were processed using Image J . ROS were detected in imaginal discs using Dihydroethidium ( DHE ) ( D11347 , Molecular Probes ) using the protocol described in Owusu-Ansah et al . [146] , with slight modifications . Briefly , larvae were dissected in Schneider’s medium ( SM ) . DHE was reconstituted in DMSO and then added to SM at a concentration of 30nM . Samples were incubated in this DHE solution for 5 minutes ( mins ) on a shaker followed by three quick washes in SM . The samples were then fixed in 7% paraformaldehyde made in 1X phosphate buffer saline ( PBS ) for 7 mins . Samples were rinsed once in 1X PBS and imaginal discs immediately dissected out to mount in Vectashield with DAPI . The samples were imaged on the confocal immediately to avoid oxidation of the DHE by the environment . Fluorescence intensity analysis was performed using single confocal slices . Average intensity was calculated by measuring intensity values in three equal-sized boxes in the pouch region of the wing disc in Image J , except for the gstD-GFP , whose expression was not uniform and thus was quantified by measuring GFP intensity in the entire pouch area . Average intensities of multiple wing discs were combined to calculate the final average intensity plotted in the graphs . For measuring the pouch area , a maximum projection of all the confocal slices was taken and the Nubbin-expressing area measured in Image J . Graphs were plotted in Excel , R , and GraphPad Prism 7 . 0 . For imaginal disc measurements and immunofluorescence quantifications , the Welch’s t-test was performed using R and GraphPad Prism 7 . 0 . For the adult wing size assay , chi-squared tests were performed using GraphPad online tools . Statistical analyses for adult wing measurements were performed using Welch’s t-test . The ablated regenerating discs had the genotype nub-GFP/+; rn-Gal4 , GAL80ts , UAS-rpr /+ , while the mock-ablated controls had the genotype nub-GFP/+; rn-Gal4 , GAL80ts/+ . Cells were isolated for the transcriptional profile as previously described [41] . Briefly , discs were dissected using teams of 4 researchers dissecting simultaneously to maximize the number of discs obtained per sample . TrypLE Select ( Life Technologies ) was used to achieve rapid dissociation of the disc cells . The GFP+ cells were sorted via FACS . mRNA from the isolated cells was prepared using an RNeasy Mini Kit ( #74104 , Qiagen ) . Multiple days of dissections and RNA preparation were pooled such that each biological replicate consisted of approximately 600 regenerating imaginal discs , 86 , 000 GFP+ cells , and up to 900ng RNA . The undamaged controls consisted of 120 discs per replicate , which produced approximately 106 , 500 GFP+ cells and 1000ng RNA . The accuracy of the sorting was previously confirmed [41] . RNA quality was confirmed using a Bioanalyzer ( Agilent 2100 ) . Library generation was carried out using Illumina's TruSeq Stranded RNA Sample Prep kit . Sequencing was carried out on a HiSeq2000 using a TruSeq SBS sequencing kit version 3 . The Roy J . Carver Biotechnology Center at the University of IIlinois at Urbana-Champaign performed the library preparation and sequencing . Fastq reads were trimmed using FASTQ Quality Trimmer ( v . 1 . 0 . 0 ) and adaptor sequences were removed using Clip ( v . 1 . 0 . 1 ) in Galaxy [147] . Reads were aligned through Tophat2 ( v . 0 . 6 ) [51 , 52] against the Drosophila melanogaster genome ( NCBI , build 5 . 41 ) with a maximum of 2 mismatches permitted . Intron length was set between 20 and 150 , 000 , and a gene model was provided as GTF ( NCBI , build 5 . 41 ) . FPKM estimation was done using Cufflinks ( v . 0 . 0 . 7 ) [51] , and both bias-correction and multi-read correction were performed . Differential expression analysis was performed using Cuffdiff [51] , geometric library normalization was performed and the False Discovery Rate was set at 0 . 05 . Furthermore , aligned reads were counted using HTSeq ( v . 0 . 3 . 2 ) [51] . All bioinformatics analysis was performed using the Galaxy suite [147] . The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus [148] and are accessible through GEO Series accession number GSE101797 ( https://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE101797 ) .
Regenerating tissue must initiate the signaling that drives regenerative growth , and then sustain that signaling long enough for regeneration to complete . Drosophila imaginal discs , the epithelial structures in the larva that will form the adult animal during metamorphosis , have been an important model system for tissue repair and regeneration for over 60 years . Here we show that damage-induced JNK signaling leads to the upregulation of a gene called moladietz , which encodes a co-factor for an enzyme , NADPH dual oxidase ( Duox ) , that generates reactive oxygen species ( ROS ) , a key tissue-damage signal . High expression of moladietz induces continuous production of ROS in the regenerating tissue . The sustained production of ROS then continues to activate JNK signaling throughout the course of regeneration , ensuring maximal tissue regrowth .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "invertebrates", "medicine", "and", "health", "sciences", "reactive", "oxygen", "species", "gene", "regulation", "animals", "animal", "models", "c-jun", "n-terminal", "kinase", "signaling", "cascade", "developmental", "biology", "drosophila", "melanogaster", "model", "organisms", "organism", "development", "experimental", "organism", "systems", "morphogenesis", "drosophila", "research", "and", "analysis", "methods", "gene", "expression", "biological", "tissue", "imaginal", "discs", "insects", "arthropoda", "biochemistry", "signal", "transduction", "regeneration", "cell", "biology", "anatomy", "genetics", "epithelium", "biology", "and", "life", "sciences", "oxidative", "damage", "cell", "signaling", "organisms", "signaling", "cascades" ]
2017
The Drosophila Duox maturation factor is a key component of a positive feedback loop that sustains regeneration signaling
While considered solely an extracellular pathogen , increasing evidence indicates that Pseudomonas aeruginosa encounters intracellular environment in diverse mammalian cell types , including macrophages . In the present study , we have deciphered the intramacrophage fate of wild-type P . aeruginosa PAO1 strain by live and electron microscopy . P . aeruginosa first resided in phagosomal vacuoles and subsequently could be detected in the cytoplasm , indicating phagosomal escape of the pathogen , a finding also supported by vacuolar rupture assay . The intracellular bacteria could eventually induce cell lysis , both in a macrophage cell line and primary human macrophages . Two bacterial factors , MgtC and OprF , recently identified to be important for survival of P . aeruginosa in macrophages , were found to be involved in bacterial escape from the phagosome as well as in cell lysis caused by intracellular bacteria . Strikingly , type III secretion system ( T3SS ) genes of P . aeruginosa were down-regulated within macrophages in both mgtC and oprF mutants . Concordantly , cyclic di-GMP ( c-di-GMP ) level was increased in both mutants , providing a clue for negative regulation of T3SS inside macrophages . Consistent with the phenotypes and gene expression pattern of mgtC and oprF mutants , a T3SS mutant ( ΔpscN ) exhibited defect in phagosomal escape and macrophage lysis driven by internalized bacteria . Importantly , these effects appeared to be largely dependent on the ExoS effector , in contrast with the known T3SS-dependent , but ExoS independent , cytotoxicity caused by extracellular P . aeruginosa towards macrophages . Moreover , this macrophage damage caused by intracellular P . aeruginosa was found to be dependent on GTPase Activating Protein ( GAP ) domain of ExoS . Hence , our work highlights T3SS and ExoS , whose expression is modulated by MgtC and OprF , as key players in the intramacrophage life of P . aeruginosa which allow internalized bacteria to lyse macrophages . Pathogenic bacteria are commonly classified as intracellular or extracellular pathogens [1] . Intracellular bacterial pathogens , such as Mycobacterium tuberculosis or Salmonella enterica , can replicate within host cells , including macrophages . In contrast , extracellular pathogens , such as Yersinia spp . , Staphylococcus aureus , Pseudomonas aeruginosa or streptococci , avoid phagocytosis or exhibit cytotoxicity towards phagocytic cells , to promote their extracellular multiplication . However , recent data have emphasized that several extracellular pathogens can enter host cells in vivo , resulting in a phase of intracellular residence , which can be of importance in addition to the typical extracellular infection . For example , although Yersinia spp . subvert the functions of phagocytes from the outside , these bacteria also subvert macrophage functions within the cell [2] . Once considered an extracellular pathogen , it is now established that S . aureus can survive within many mammalian cell types including macrophages [3 , 4] and the intramacrophage fate of S . aureus has been deciphered [5 , 6] . Moreover , an intracellular phase within splenic macrophages has been recently shown to play a crucial role in initiating dissemination of Streptococcus pneumoniae , providing a divergence from the dogma that considered this bacterial pathogen a classical example of extracellular pathogens [7] . The environmental bacterium and opportunistic human pathogen P . aeruginosa is responsible for a variety of acute infections and is a major cause of mortality in chronically infected cystic fibrosis ( CF ) patients . The chronic infection of P . aeruginosa and its resistance to treatment is largely due to its ability to form biofilms , which relies on the production of exopolysaccharides ( EPS ) , whereas the type III secretion system ( T3SS ) is reported to play a key role in the pathogenesis of acute P . aeruginosa infections [8] . Four T3SS effectors ( ExoU , ExoS , ExoT , ExoY ) have been identified so far , ExoS being nearly always mutually exclusive with the potent cytotoxin ExoU and more prevalent than ExoU [9–11] . ExoS has a dual function as it contains a GTPase activating protein ( GAP ) domain as well as an ADP ribosyltransferase ( ADPRT ) domain [10] . An intracellular step in airway epithelial cells has been proposed to occur before the formation of biofilm during the acute phase of infection [12 , 13] and the intracellular stage of P . aeruginosa within cultured epithelial cells has been fairly studied [14–16] . The principle that P . aeruginosa is not exclusively an extracellular pathogen has been convincingly established by the recent use of advanced imaging methods to track bacteria within epithelial cells [17] . The T3SS , more specifically its effector ExoS , has been implicated in the formation of membrane blebs-niche and avoidance of acidified compartments to allow bacterial multiplication within epithelial cells [17–19] . Concordantly , T3SS genes were recently shown to be expressed in P . aeruginosa internalized in epithelial cells [17] . Regarding the interaction with macrophages , P . aeruginosa has developed mechanisms to avoid phagocytosis [20] . However , P . aeruginosa has been shown to be phagocytosed by macrophages in an acute model of infection in zebrafish embryos [21 , 22] and has been reported to be engulfed by alveolar macrophages in the lungs of mice early after pulmonary infection [23] , suggesting that P . aeruginosa may need strategies to escape macrophage killing . Although P . aeruginosa has been localized within cultured macrophages during gentamicin protection assays [24–26] , the intramacrophage fate of the bacteria has not been characterized and bacterial factors involved in this step remain largely unexplored . Bacterial survival in a particular niche requires the development of an adaptive response , generally mediated by regulation of the bacterial genes involved in physiological adaptation to the microenvironment . The identification of mutants lacking the ability to survive within macrophages and the study of P . aeruginosa gene expression inside macrophages is critical to determine bacterial players in this step . We have previously uncovered MgtC as a bacterial factor involved in the intramacrophage survival of P . aeruginosa [25 , 27] . In agreement with this intramacrophage role , expression of Pseudomonas mgtC ( PA4635 ) gene is induced when the bacteria reside inside macrophages [25] . MgtC is known to promote intramacrophage growth in several classical intracellular bacteria , including Salmonella typhimurium where it inhibits bacterial ATP synthase and represses cellulose production [28–30] , and is considered as a clue to reveal bacterial pathogens adapted to an intramacrophage stage [30 , 31] . In addition , a recent study has implicated the outer membrane protein OprF in the ability of otopathogenic P . aeruginosa strains to survive inside macrophages [26] . OprF is an outer membrane porin that can modulate the production of various virulence factors of P . aeruginosa [32 , 33] . In the present study , we investigated the fate of P . aeruginosa within macrophages using wild-type PAO1 strain , which lacks ExoU , along with isogenic mgtC and oprF mutants . We also explored , for the first time , the regulation of T3SS genes when P . aeruginosa resides inside macrophages . The T3SS and ExoS effector , whose expression was found to be modulated by MgtC and OprF intracellularly , were seemingly involved in this intracellular stage , playing a role in vacuolar escape and cell lysis caused by intracellular bacteria . We previously visualized fluorescent P . aeruginosa residing within fixed macrophages [25] . To investigate the fate of P . aeruginosa after phagocytosis in a dynamic way , we monitored macrophages infected with fluorescent bacteria using time-lapse live microscopy . J774 macrophages were infected with wild-type PAO1 strain expressing GFP grown exponentially in LB medium ( Multiplicity of infection or MOI = 10 ) . After 25 minutes of phagocytosis , several washes were performed to remove non-internalized bacteria and gentamicin was added to kill the remaining extracellular bacteria . Microscopic observation of infected macrophages up to 3 hours showed cell lysis with increasing time ( Fig 1 ) , starting between 1 . 5 and 2 hours post-phagocytosis , which can be attributed to intracellular bacteria as gentamicin was retained throughout the experiment . No lysis of uninfected cells present in the same field was observed ( Fig 1 and S1 Fig ) , as expected from an event due to intracellular bacteria rather than extracellular bacteria . The cell lysis appeared to take place within a rapid time frame of few seconds , as shown by the movie ( S1 Movie ) , after which the bacteria seemed to be released from the host cell . We also infected human monocyte-derived macrophages ( HMDMs ) with GFP producing PAO1 strain under similar conditions and found lysed infected cells after 2 hours of phagocytosis ( S2 Fig ) . Hence , the phenomenon of lysis of macrophages by intracellular PAO1 is not restricted to J774 murine cell line , but is extendable to primary human macrophages . We further examined intracellular P . aeruginosa within macrophages in more detail using transmission electron microscopy ( TEM ) . J774 macrophages infected with wild-type PAO1 strain , were subjected to fixation at early time post-infection ( 30 min after phagocytosis ) or at later time of infection ( 3 hrs after phagocytosis ) . After phagocytosis , P . aeruginosa was present in membrane bound vacuoles inside macrophages ( Fig 2A ) . At a later time point , some bacteria could be found in the cytoplasm with no surrounding membrane , suggesting disruption of the vacuole membrane ( Fig 2B ) . The infected macrophage was damaged , displaying highly condensed chromatin and membrane blebbing , and lacking pseudopodia . Healthy infected cells were also observed , where bacteria were mostly found in vacuoles partially or totally filled with heterogeneous electron dense material , suggesting that the vacuole has fused with lysosomes ( Fig 2C ) . To confirm this , we examined the association between fluorescent PAO1 bacteria and the LysoTracker probe during infection using fixed macrophages . Bacteria colocalizing with LysoTracker could be visualized ( S3 Fig ) , thereby corroborating the TEM observation of fusion of vacuoles with lysosomes and the localization of bacteria in acidified compartment . TEM analyses allowed us to conclude that wild-type PAO1 strain has the ability to reside within vacuoles and possibly escape from the phagosome into the cytoplasm , and promote cell damage . A rapid cell lysis event caused by intracellular P . aeruginosa visualized by live microscopy revealed that phagocytosed bacteria can escape from macrophage through cell lysis . Our previous results based on gentamicin protection assay on J774 infected macrophages and counting of colony forming units ( CFU ) indicated that mgtC mutant ( generated in the PAO1 background ) survived to a lesser extent than the wild-type strain [25] . More recently , an oprF mutant of an otopathogenic strain of P . aeruginosa was also found to be defective in intracellular survival in mouse bone marrow macrophages based on gentamicin protection assay [26] . To analyze the phenotypes of oprF mutant in the PAO1 background towards J774 macrophages and compare that with mgtC mutant , we used here a previously described oprF mutant generated in PAO1 strain [25 , 34] . Based on the finding that intracellular P . aeruginosa can cause macrophage lysis , we developed a suitable assay using fluorescent microscopic analysis to quantify cell damage caused by intracellular bacteria . Macrophages were infected with fluorescent bacteria , treated with gentamicin for 2 hours after phagocytosis , fixed and stained with phalloidin-TRITC to label F-actin and visualize macrophage morphology . A clear cortical red labeling was seen in most cells , which is indicative of the plasma membrane-associated cortical actin . Few infected cells appeared lysed due to the loss of cortical actin staining ( Fig 3A ) , which agrees with the observation of lysed macrophages in time lapse fluorescence microscopy ( Fig 1 ) . The loss of cortical actin staining was found to be due to internalized bacteria because upon arresting phagocytosis , by treating macrophages with cytochalasin D , bacteria were not internalized and loss of cortical actin staining was not observed ( S4 Fig ) . Hence , any delayed effect of extracellular bacteria occurring before gentamicin treatment or a contribution of extracellular bacteria that would resist gentamicin treatment can be ruled out . Quantification of the number of cells without phalloidin labelling showed highest value for cells infected with wild-type strain , intermediate with mgtC mutant and lowest with oprF mutant ( Fig 3B ) . Thus , both intracellular mgtC and oprF mutants appeared compromised for cell lysis . This feature is not linked to a lower internalization rate of the mutant strains , because mgtC mutant is known to be more phagocytosed than wild-type strain [25] and a similar trend was found for oprF mutant ( not shown ) . Since T3SS has been involved in the intracellular life of P . aeruginosa in other cell types [17] , we next monitored the expression of T3SS genes during the residence of bacteria within macrophages . The P . aeruginosa oprF mutant was reported to be defective in the secretion of T3SS effectors in liquid culture and in the production of PcrV , the T3SS needle tip protein [32 , 34] , but the effect of OprF on transcription of T3SS genes has not been tested so far . We thus investigated the expression of the effector gene exoS along with the gene pcrV in oprF mutant strain in comparison to wild-type strain upon macrophage infection . As a control , we tested flagellin coding gene fliC , which is not part of the T3SS regulon , but was proposed to be secreted by the T3SS [35] . Expression of both pcrV and exoS genes was found to be remarkably reduced in the oprF mutant ( Fig 4 ) . Strikingly , the mgtC mutant also exhibited significantly reduced expression of these two T3SS genes ( Fig 4 ) , although to a lesser extent than the oprF mutant , indicating an unexpected interplay between MgtC and T3SS . On the other hand , fliC expression was not altered in both mutants . Since we observed a decreased transcriptional level of T3SS genes in the oprF mutant , we further examined the link between intramacrophage expression of T3SS and cell lysis in this mutant . A recombinant plasmid allowing IPTG-inducible overproduction of ExsA , a master transcriptional activator of T3SS genes [36] , was introduced in the oprF mutant . Upon induction of exsA expression with 0 . 01 mM IPTG , oprF mutant promoted macrophage lysis like the wild-type strain ( S5 Fig ) , supporting a model whereby the effect of OprF is the result of its positive regulatory effect on T3SS expression . To address the mechanism behind the downregulation of transcription of T3SS in oprF and mgtC mutant strains , we evaluated the level of the second messenger c-di-GMP , as it is known to participate in T3SS repression in P . aeruginosa [37] . The oprF mutant was already reported to have high production of c-di-GMP in liquid culture [34] . We used a fluorescence-based reporter ( Fig 5A ) that has been validated to gauge c-di-GMP level inside P . aeruginosa [38] . The pCdrA::gfp plasmid was introduced into wild-type and mutant strains , and fluorescence was measured in infected macrophages ( Fig 5B ) . Both oprF and mgtC mutants exhibited significantly increased activity of the cdrA promoter comparatively to wild-type strain , indicative of higher levels of c-di-GMP than the wild-type strain . To better appreciate the differences monitored within macrophages , we also measured fluorescence of strains grown in culture medium with various magnesium concentrations ( Fig 5C ) . The oprF mutant exhibited a two to three-fold increase in the activity of the cdrA promoter comparatively to wild-type strain , which is in the same range as the increase observed within macrophages ( Fig 5B ) , and agrees with published data obtained with this indirect strategy and direct c-di-GMP measurement [34] . Under magnesium limitation , a condition known to induce mgtC expression , the mgtC mutant also showed increased activity of the cdrA promoter comparatively to wild-type strain , with a two-fold increase in the absence of Mg2+ , and a minor , but significant , increase in the presence of 10 μM Mg2+ ( that is similar to what is observed within macrophages ) . On the other hand , the level of fluorescence of wild-type strain and mgtC mutant was identical in medium supplemented with 1 mM Mg2+ , a condition that prevents mgtC expression [25] . Taken together , these results indicate that the production of c-di-GMP is increased relatively to wild-type strain in both oprF and mgtC mutants , with a more pronounced effect for oprF , when bacteria reside within macrophages , thus providing a mechanistic clue for the negative effect on T3SS gene expression . Given the effect of both oprF and mgtC deletions on the expression of T3SS genes within macrophages , we investigated the fate of a T3SS mutant upon phagocytosis . We first used a pscN mutant that is defective for the ATPase function of the T3SS machinery [36] . Intracellular T3SS mutant did not induce loss of cortical phalloidin staining , as shown by fluorescent imaging and subsequent quantification , indicating lack of cell lysis ( Fig 6A and 6B ) . Thus , the phenotype of T3SS mutant is consistent with that of mgtC and oprF mutants and is in correlation with their level of T3SS gene expression . We further examined the relevance of our findings to primary human macrophages , by assessing the lysis of HMDMs driven intracellularly by wild-type P . aeruginosa or oprF and pscN mutants . The count of intracellularly lysed cells was significantly different between wild-type and each mutant strain ( Fig 7 ) , with a similar trend to that of J774 macrophages ( Fig 3 and Fig 6 ) , thus confirming the importance of T3SS in intracellularly driven lysis of primary human macrophages as well . To address the implication of T3SS effector proteins in this process , we used mutant strains for individual effector genes exoS , exoT and exoY , and exoSTY triple mutant . The intracellular lysis of macrophages was found to be reduced for the exoSTY triple mutant and to a similar extent for the exoS mutant ( Fig 6A and 6B ) , suggesting a major contribution of ExoS . Accordingly , exoT and exoY mutants behave similarly to wild-type strain ( Fig 6B ) . Moreover , complementation of the exoSTY mutant with exoS restored the wild-type phenotype ( Fig 6C ) . Although the lysis by exoS mutant strain was substantially higher than that of pscN mutant , these results suggest that the T3SS-mediated intracellular lysis of macrophages by P . aeruginosa relies mainly on the T3SS effector ExoS . Thus , this ExoS-dependent cytotoxic effect mediated by intracellular bacteria differs from the classical T3SS-dependent cytotoxicity driven by extracellular bacteria towards macrophages that has been reported to be mostly independent of ExoS [39–41] . To confirm this difference between intracellular and extracellular bacteria mediated lysis , we measured the lactate dehydrogenase ( LDH ) release when infection was carried out without removing extracellular bacteria . As expected , similar values were obtained for wild-type strain and exoS mutant , whereas a pscN mutant showed significantly reduced LDH release ( S6 Fig ) , which agrees with the reported T3SS-dependent but ExoS independent cytotoxicity caused by extracellular bacteria . This is also consistent with trypan blue exclusion assay , which monitors cell death based on penetration of a membrane impermeable dye , when the assay is done immediately after phagocytosis ( S7 Fig , panel A ) . ExoS possesses GAP domain as well as ADPRT domain and complementing strains retaining only one of these two domains have been constructed earlier [42] . To determine which domain of ExoS plays a role in intracellular cytotoxicity , we carried out the phalloidin-based lysis assay using the exoSTY mutant producing either ADPRT ( GAP- ) or GAP ( ADPRT- ) domain of ExoS . Our results clearly showed that the strain retaining GAP activity of ExoS but lacking ADPRT activity ( ΔexoSTY + exoS ADPRT- ) could complement the phenotype to an extent similar to the strain complemented with exoS ( Fig 6C ) , which is also equivalent to the wild-type . To strengthen our findings , we performed trypan blue exclusion assay after 2hrs of gentamicin treatment post-phagocytosis . The results are consistent with phalloidin assay , supporting the implication of ExoS , and more specifically its GAP domain , for macrophage death induced by intracellular bacteria ( S7 Fig , panel B ) . This contrasts with the results of trypan blue exclusion assay performed immediately after phagocytosis , where a low level of T3SS-dependent cell death is observed , but not linked to ExoS function ( S7 Fig , panel A ) . Hence , our results indicate that , in contrast to extracellular P . aeruginosa , intracellular P . aeruginosa uses an ExoS-dependent T3SS mediated mechanism to promote macrophage lysis . Moreover , only the GAP activity of ExoS is required for this process . The phagosomal environment of the macrophage is hostile for bacterial pathogens and TEM analysis indicated that PAO1 can be found in the cytoplasm , suggesting escape from the phagosomal vacuole ( Fig 2B ) . We decided to address the intracellular role of T3SS , OprF and MgtC in the phagosomal escape of P . aeruginosa to the cytoplasm of macrophages . To monitor P . aeruginosa escape from phagosome , we used the CCF4-AM/β-lactamase assay that has been developed for tracking vacuolar rupture by intracellular pathogens [43] . This assay takes advantage of the natural production of β-lactamase by P . aeruginosa [44] , which can cleave a fluorescent β-lactamase substrate , CCF4-AM , that is trapped within the host cytoplasm . CCF4-AM emits a green fluorescence signal , whereas in the presence of β-lactamase activity , a blue fluorescence signal is produced . The detection of blue fluorescent cells at 2 hrs post-phagocytosis indicated bacterial escape from the phagosome to the cytoplasm ( Fig 8A ) . The escape of wild-type strain was compared to that of mgtC , oprF and pscN mutants by quantifying the percentage of blue fluorescent cells out of total green fluorescent cells . Wild-type strain showed significantly higher percentage of phagosomal escape than all mutants tested ( Fig 8B ) . No significant difference in terms of cleavage of CCF4-AM was measured for the mutants with respect to wild-type in liquid cultures ( S8 Fig ) , indicating that the lower amount of blue fluorescent cells with the mutants is not due to reduced production of endogenous β-lactamase . In agreement with the finding of phagosomal escape by CCF4-AM/β-lactamase assay , ruptured phagosomal membrane could be visualized by TEM in macrophages infected with PAO1 wild-type strain ( Fig 8C ) . Both exoS and exoSTY effector mutants also displayed a low percentage of phagosomal escape , which appeared similar to that of pscN mutant ( S9 Fig ) . These results indicate that the T3SS , through the ExoS effector , plays role in the escape of P . aeruginosa from the phagosome to the cytoplasm . The effect of MgtC and OprF in this process may as well be mediated by their effect on T3SS gene expression ( Fig 4 ) . Cumulatively , our results support a T3SS-dependent vacuolar escape for P . aeruginosa , leading to the localization of bacteria in the cytoplasm and cell lysis as depicted in the proposed model ( Fig 9 ) . The ability of professional phagocytes to ingest and kill microorganisms is central to innate immunity and host defense . P . aeruginosa is known to avoid being killed by phagocytes through the destruction of immune cells extracellularly as well as avoidance of phagocytosis [20] . However , P . aeruginosa has been reported to be engulfed by macrophages in animal infection models [21–23] . In addition , P . aeruginosa has been visualized in phagocytes in cell culture models in several studies , where MgtC and OprF have been shown to be involved in the ability of P . aeruginosa to survive in cultured macrophages [25 , 26] . The virulence of P . aeruginosa mgtC mutant can be restored in zebrafish embryos upon macrophages depletion , suggesting that MgtC acts to evade phagocytes [25] . Interestingly , a similar behavior has been reported for a T3SS mutant in the same infection model [21] . We show here that MgtC and OprF regulate T3SS when P . aeruginosa resides in macrophages and we describe a novel strategy used by P . aeruginosa to escape from macrophages that relies on a T3SS-dependent cell lysis induced by intracellular bacteria ( Fig 9 ) . Using electron microscopy , we demonstrate that upon phagocytosis , P . aeruginosa PAO1 strain resides in membrane bound vacuoles , whereas a cytosolic location can be observed at later time of infection , which corroborates the observation of an otopathogenic P . aeruginosa clinical strain in HMDMs [26] . Microscopic analysis of live and fixed cells revealed macrophage lysis driven by intracellular bacteria , with J774 macrophage cell line as well as HMDMs . This cell lysis is a rapid process associated with the loss of cortical actin from plasma membrane . We propose that the cell lysis induced by intracellular P . aeruginosa is linked to the phagosomal escape of bacteria as indicated by the observation of cytosolic bacteria and ruptured phagosomal membrane by TEM as well as CCF4-AM/β-lactamase based phagosomal rupture assay . To better characterize the P . aeruginosa factors involved in its intramacrophage fate , we investigated intracellular expression of T3SS genes in mgtC and oprF mutants . Expression of T3SS genes upon macrophage infection was significantly decreased in mgtC mutant and abrogated in oprF mutant . The production of T3SS effectors or needle component was previously known to be altered in the oprF mutant [32 , 34] , but a direct effect at the transcriptional level was not investigated before . This regulation could be mediated by c-di-GMP , a known negative regulator of T3SS expression [37] , as the reporter assay revealed an increased level of c-di-GMP in both oprF and mgtC mutants upon monitoring infected macrophages , with a more pronounced effect for oprF mutant . An increased level of c-di-GMP in oprF mutant is consistent with previous results obtained in vitro [34] . The moderate , but significant , increase in the level of c-di-GMP in mgtC mutant in macrophages with respect to wild-type strain is equivalent to the fold increase obtained in low-Mg2+ cultures . It is of interest to note that a Salmonella mgtC mutant also exhibited increased c-di-GMP level intracellularly and under low-Mg2+ condition [29] . The P . aeruginosa mgtC and oprF mutants showed a moderate and a more pronounced decrease , respectively , in cytotoxicity driven by intracellular bacteria and phagosomal escape . These phenotypes could be linked to the pattern of T3SS expression in mgtC and oprF mutants because a T3SS mutant appeared to lack cytotoxicity driven by intracellular bacteria and showed reduced phagosomal escape . Accordingly , inducing expression of exsA gene , a master activator of T3SS , in oprF mutant promoted macrophage lysis driven by intracellular bacteria to a similar level to that of wild-type strain , supporting the model whereby the phenotype of oprF mutant is the result of a negative regulation of T3SS expression . Our data indicate that the T3SS-mediated cytotoxicity driven by intracellular P . aeruginosa is largely dependent on the ExoS effector . ExoS , which has a dual function [10] , was known to play a role in the intracellular life of P . aeruginosa in cell types other than macrophages . The T3SS and ExoS are indeed key factors for intracellular replication of P . aeruginosa in epithelial cells , with a main role of the ADPRT domain in the formation of replicative niche in membrane blebs [18 , 19 , 45] . ExoS and ExoT ADPRT domains also promote bacterial survival in neutrophils [46] , by having a protective role against NADPH-oxidase activity [47] . However , the effect of T3SS towards macrophages was so far restricted to the well-known cytotoxicity caused by extracellular P . aeruginosa [39 , 48–50] . In P . aeruginosa strains lacking ExoU toxin , such as PAO1 , this cytotoxicity is due to inflammasome activation , which is dependent on T3SS translocation apparatus , but is independent of the ExoS effector [39–41 , 51] . Accordingly , this T3SS-dependent ExoS-independent cytotoxity was observed in our assays when extracellular bacteria were not removed . In contrast , upon removal of extracellular bacteria , a T3SS-mediated cytotoxicity implicating ExoS was uncovered . Hence , ExoS appears to be associated with cell damage only when it is secreted from internalized bacteria . Moreover , phagosomal rupture assay indicated that ExoS plays role in the escape of P . aeruginosa from the phagosome to the cytoplasm and we propose that upon phagosomal rupture , the cytoplasmic location of P . aeruginosa induces inflammasome , possibly through the release of bacterial lipopolysaccharides ( LPS ) in the cytoplasm , which would promote cell death . Therefore , in addition to the inflammasome activation caused by extracellular P . aeruginosa and , as very recently described , by intracellular T3SS-negative P . aeruginosa in the context of long-term infection [52] , our study suggests that inflammasome and subsequent macrophage death can also be caused by intracellular T3SS-positive P . aeruginosa . Further studies will be required to characterize inflammasome activation and pathways that lead to cell death . The intracellular implication of ExoS in both macrophages and epithelial cells suggests that the intracellular life of P . aeruginosa in macrophages shares features with the intracellular life of the pathogen in epithelial cells , even though the outcome is different . While bacteria actively replicate in epithelial cells , within bleb niches or in the cytosol [17] , replication of bacteria is barely seen within macrophages resulting instead in cell lysis and bacterial escape from macrophages . Our results further indicate that the macrophage damage caused by intracellular P . aeruginosa is due to ExoS GAP domain , which thus differs from the reported role of the ADPRT domain of ExoS in blebs formation associated with intracellular replication of P . aeruginosa within epithelial cells [18 , 19 , 45] . On the other hand , the implication of GAP domain of ExoS towards epithelial cells in promoting cell rounding , actin reorganization or cell death has not been specifically associated with intracellular bacteria [53 , 54] . Although ExoS and ExoT GAP domain have similar biochemical activities , these effectors may differ in their localization inside host cells or they may interact with different host factors to bring about their effect . This is supported by the fact that apoptosis is induced in epithelial cells by ExoT GAP domain , a feature that was not reported for ExoS GAP domain [55] and by our finding that , unlike ExoS , ExoT is not involved in the intramacrophage phenotypes . Importantly , we show that the extent of phagosomal escape of pscN and exoSTY mutants was similar to that of exoS mutant alone , suggesting that ExoS is the main effector protein involved in the exit of P . aeruginosa from the phagosome . In epithelial cells , ExoS has been involved in avoidance of acidified compartment [18 , 19] . Considering our findings , ExoS may allow avoidance of acidification in macrophages and may also contribute to the vacuolar escape in epithelial cells . Further studies will be required to decipher in more detail , the function of ExoS inside macrophages , including a better understanding of its role in phagosomal escape and identification of its host targets within macrophages . ExoS-positive strains represent a large number of clinical isolates but the number of ExoS-negative strains is nevertheless substantial ( about one third of isolates ) , especially among strains associated with bacteremia [10 , 11 , 56] . However , strains lacking ExoS usually encode the potent cytotoxin ExoU , thus exhibiting high toxicity towards eukaryotic cells from outside and less susceptibility to encounter an intracellular stage . In conclusion , our results indicate that P . aeruginosa shares common feature with other so-called extracellular pathogens , such as S . aureus , which can reside transiently within macrophages [4] and require bacterial factors to survive this stage [57] . The present study uncovered bacterial factors allowing internalized P . aeruginosa to lyse macrophages . This should let bacteria to evade macrophages and an important issue now is to better evaluate the contribution of intramacrophage stage to disease outcome during P . aeruginosa infection . Survival of P . aeruginosa within macrophages and subsequent bacterial release may play a role in the establishment and dissemination of infection . There is also evidence that intracellular survival may contribute to persistence of the infection by creating a niche refractory to antibiotic action [24] , highlighting the potential importance of this overlooked phase of P . aeruginosa infection . Bacterial strains and plasmids are described in Table 1 . P . aeruginosa mutant strains ( all in the PAO1 background ) have been described and phenotypically characterized previously ( Table 1 ) . The oprF mutant ( strain H636 ) is derived from PAO1 wild-type strain H103 [34] , which exhibits the same level of ExoS secretion under T3SS-inducing conditions as PAO1 , the isogenic strain for mgtC and T3SS mutants ( S10 Fig ) . P . aeruginosa was grown at 37°C in Luria broth ( LB ) . Growth in magnesium-defined medium was done in NCE-minimal medium [58] supplemented with 0 . 1% casamino acids , 38 mM glycerol , without MgSO4 or containing 10 μM or 1mM MgSO4 . Plasmid pMF230 expressing GFP constitutively [59] ( obtained from Addgene ) , was introduced in P . aeruginosa by conjugation , using an E . coli strain containing helper plasmid pRK2013 . Recombinant bacteria were selected on Pseudomonas isolation agar ( PIA ) containing carbenicillin at the concentration of 300 μg/ml . J774 cells ( murine macrophage cell line J774A . 1 , gifted by Gisèle Bourg , Inserm U 1047 , Nîmes , France ) were maintained at 37°C in 5% CO2 in Dulbecco's modified Eagle medium ( DMEM ) ( Gibco ) supplemented with 10% fetal bovine serum ( FBS ) ( Gibco ) . The infection of J774 macrophages by P . aeruginosa was carried out essentially as described previously [25] . Mid-log phase P . aeruginosa grown in LB broth was centrifuged and resuspended in PBS to infect J774 macrophages ( 5×105 cells/well ) at an MOI of 10 . After centrifugation of the 24-well culture plate for 5 min for synchronization of infection , bacterial phagocytosis was allowed for 25 min . Cells were washed three times with sterile PBS and fresh DMEM medium supplemented with 400 μg/ml gentamicin was added and retained throughout the infection . Purified monocytes isolated as described from blood of healthy donors were frozen in liquid nitrogen [60 , 61] . Cells were thawed for experiment and seeded onto 24-well plates at a density of 7x105 per well in complete culture medium ( RPMI containing 10% FCS ) and differentiated into macrophages with rh-M-CSF ( 10 ng/ml ) ( purchased from Al-Immuno tools ) for 7 days . HMDMs were infected with exponentially growing P . aeruginosa cultures ( OD600 = 0 . 8 ) at an MOI of 10 , as described above . J774 macrophages were seeded in ibidi μ-slide ( 8 wells ) in DMEM medium supplemented with 10% FBS and infected with P . aeruginosa PAO1 expressing GFP as described in the previous section . Imaging started after 30 min of phagocytosis , when the media was changed to DMEM supplemented with 400 μg/ml gentamicin until 3 hrs post phagocytosis . Cells were imaged using an inverted epifluorescence microscope ( AxioObserver , Zeiss ) , equipped with an incubation chamber set-up at 37°C and 5% CO2 and a CoolSNAP HQ2 CCD camera ( Photometrics ) . Time-lapse experiments were performed , by automatic acquisition of random fields using a 63X Apochromat objective ( NA 1 . 4 ) . The frequency of acquisition is indicated in figure legends . Image treatment and analysis were performed using Zen software ( Zeiss ) . Macrophages were seeded on glass coverslips and infected as described above . Infected cells were fixed for 4 hrs at room temperature with 2 . 5% gluteraldehyde in cacodylate buffer 0 . 1 M pH 7 . 4 with 5mM CaCl2 , washed with cacodylate buffer , post-fixed for 1 hr in 1% osmium tetroxide and 1 . 5% potassium ferricyanide in cacodylate buffer , washed with distilled water , followed by overnight incubation in 2% uranyl acetate , prepared in water . Dehydration was performed through acetonitrile series and samples were impregnated in epon 118: acetonitrile 50:50 , followed by two times for 1 hr in 100% epon . After overnight polymerization at 60°C , coverslips were detached by thermal shock with liquid nitrogen . Polymerization was then prolonged for 48 hrs at 60°C . Ultrathin sections of 70 nm were cut with a Leica UC7 ultramicrotome ( Leica microsystems ) , counterstained with lead citrate and observed in a Jeol 1200 EXII transmission electron microscope . All chemicals were from Electron Microscopy Sciences ( USA ) and solvents were from Sigma . Images were processed using Fiji software . Macrophages were infected with GFP labelled P . aeruginosa as described above . After 2 . 5 hrs of gentamicin treatment , infected J774 cells were washed twice with PBS and incubated with 50 nM Lysotracker red DND-99 ( Molecular Probes ) in DMEM for 10 min to stain lysosomes . Cells were then washed with PBS and fixed with 4% paraformaldehyde in PBS and mounted on glass slides in Vectashield ( Vector Laboratories , Inc ) with 4′ , 6-diamidino-2-phenylindole ( DAPI ) to stain the nucleus . The slides were examined using an upright fluorescence microscope ( Axioimager Z2 , Zeiss ) equipped with an Apotome 1 for optical sectioning . A 63X Apochromat Objective ( NA 1 . 4 ) was used , transmitted light was acquired using differential interference contrast ( DIC ) , Fluorescein isothiocyanate ( FITC ) filter was used to visualize GFP expressing bacteria and Lysotracker red fluorescence was acquired using a texas red filter set . J774 macrophages were seeded on glass coverslips and infected with GFP expressing bacteria as described in the previous sections . For cytochalasin treatment , DMEM containing 2 μM cytochalasin D ( Sigma ) was added to the macrophages 1 hour before infection and maintained during phagocytosis . After phagocytosis , the cells were maintained in 1 μM cytochalasin D till the end of the experiment . For untreated control , 0 . 2% DMSO ( solvent control ) in DMEM was added to the cells before and during phagocytosis . After phagocytosis , cells were maintained in 0 . 1% DMSO . After fixation with 4% paraformaldehyde ( EMS , USA ) in PBS for 5 min , cells were washed once with PBS and permeabilized by adding 0 . 1% triton X-100 for 1 min 30 sec . Cells were then washed once with PBS and incubated with 1 μg/ml Tetramethylrhodamine B isothiocyanate ( TRITC ) -labeled phalloidin ( Sigma-Aldrich ) in PBS for 30 min in dark . Cells were washed twice with PBS and coverslips were mounted on glass slides in Vectashield with DAPI ( Vector Laboratories , Inc ) . The slides were examined using an upright fluorescence microscope ( Axioimager Z1 , Zeiss ) equipped with an Apotome 1 for optical sectioning . A 63X Apochromat Objective ( NA 1 . 4 ) was used and transmitted light was acquired using DIC . FITC and texas red filters were used to visualize GFP expressing bacteria and phalloidin respectively . Cell nuclei were visulalized using DAPI filter . Images were processed using ZEN software ( Zeiss ) . Cells were counted manually , where infected cells lacking the phalloidin stain were considered as lysed . Percentage of such lysed cells with intracellular bacteria out of total number of infected cells was calculated and plotted for each strain . Strains containing pSBC6 plasmid ( expressing exsA under the control of tac promoter ) were grown before infection in LB or in LB supplemented with 0 . 01 mM IPTG . Because these strains did not harbor GFP producing plasmid , the number of total cells without phalloidin label was counted and percentage out of total number of cells was plotted . The percent of lysed cells for wild-type strain was similar to that found with GFP positive PAO1 strain . The cytotoxicity was assessed by release of LDH from infected J774 macrophages infected , using the Pierce LDH cytotoxicity assay kit ( Thermo Scientific ) . Macrophages were infected for 2 hrs at an MOI of 10 as described above , except that cells were seeded in a 96 well plate and extracellular bacteria were not removed . The assay was performed on 50 μl of the culture supernatant according to manufacturer’s instructions . LDH release was obtained by subtracting the 680 nm absorbance value from 490 nm absorbance . The percentage of LDH release was first normalized to that of the uninfected control and then calculated relatively to that of uninfected cells lysed with Triton X-100 , which was set at 100% LDH release . The membrane impermeable dye Trypan Blue was used to quantify cell viability after phagocytosis or after 2 hrs of gentamicin treatment following phagocytosis . Trypan Blue stain ( 0 . 4% ) was added in 1:1 ratio with PBS for 3 min at room temperature , replaced by PBS and the cells were imaged using an optical microscope in bright field mode . Dead cells appear blue as they take up the stain , in contrast to healthy cells that appear transparent because of the exclusion of the dye . Cells were counted and the percentage of dead cells out of total cells ( blue + colorless ) was calculated . For bacterial RNA extraction from infected J774 , 6 . 5x106 macrophages were seeded into a 100 cm2 tissue culture dish and infected at an MOI of 10 as described above . 1 hour after phagocytosis , cells were washed three times with PBS , lysed with 0 . 1% Triton X100 and pelleted by centrifugation at 13000 rpm for 10 min at 15°C . Bacteria were resuspended in 500 μl PBS and the non resuspended cellular debris was discarded . 900 μl of RNA protect reagent ( Qiagen ) was added and incubated for 5 min . The sample was centrifuged at 13000 rpm for 10 min . Bacteria in the pellet were lysed with lysozyme and RNA was prepared with RNeasy kit ( Qiagen ) . Superscript III reverse transcriptase ( Invitrogen ) was used for reverse transcription . Controls without reverse transcriptase were done on each RNA sample to rule out possible DNA contamination . Quantitative real-time PCR ( q-RT-PCR ) was performed using a Light Cycler 480 SYBR Green I Master mix in a 480 Light Cycler instrument ( Roche ) . PCR conditions were as follows: 3 min denaturation at 98°C , 45 cycles of 98°C for 5 sec , 60°C for 10 sec and 72°C for 10 sec . The sequences of primers used for RT-PCR are listed in S1 Table . The strains were transformed by electroporation with the plasmid pCdrA::gfp [34 , 38] , which expresses GFP under the control of the promoter of cdrA , a c-di-GMP responsive gene , and carries a gentamicin resistance gene . Overnight cultures , grown in LB with 100 μg/ml gentamicin , were subcultured in LB . These cultures were used to infect J774 cells seeded in a 96 well plate ( Greiner , Flat-Bottom ) , containing 105 cells per well with an MOI of 20 after normalizing the inoculum to their OD600 . After phagocytosis , DMEM containing 300 μg/ml of amikacin , instead of gentamicin , was added to eliminate extracellular bacteria , as these strains are resistant to gentamicin . At the required time point , Tecan fluorimeter ( Spark 20M ) was used to measure fluorescence ( excitation , 485 nm and emission , 520 nm ) of cells at the Z point where emission peak could be obtained in comparison to the blank . Fluorescence was plotted for each strain in terms of arbitrary units ( AU ) . CdrA activity of all strains was also measured in liquid cultures under changing concentrations of magnesium . All strains , grown overnight in LB , were diluted in LB and grown until OD600 of 0 . 6 , washed in NCE medium without magnesium and resuspended in NCE medium containing 1 mM , 10 μM or no magnesium for 1 hour in 96 well plate ( Greiner , Flat-Bottom ) . Their fluorescence ( excitation , 485 nm and emission , 520 nm ) and OD600nm were measured . Fluorescence ( AU520nm ) was normalized to OD600nm and plotted for each strain . The vacuole escape assay was adapted from the CCF4 FRET assay [43] using the CCF4-AM LiveBlazer Loading Kit ( Invitrogen ) and an image-based quantification [62] . Briefly , J774 macrophages were seeded in 96 well plate ( Greiner , Flat-Bottom ) , containing 5x104 cells per well . Overnight bacterial cultures were subcultured in LB with 50 μg/ml of ampicillin to enhance the expression of beta-lactamase , present naturally in P . aeruginosa . Infection was carried out as mentioned in the previous sections at the MOI of 10 . After phagocytosis , the cells were washed thrice with PBS to remove extracellular bacteria . 100 μl of HBSS buffer containing 3 mM probenecid and gentamicin ( 400 μg/ml ) , was added in each well . The substrate solution was prepared by mixing 6 μl of CCF4-AM ( solution A ) , 60 μl of solution B and 934 μl of solution C . 20 μl of the substrate solution was added to each well and the plate was incubated in dark at 37°C with 5% CO2 . After 2 hrs , the cells were imaged as described in the Live Imaging section , using a 10X objective . FITC and DAPI channels were used to visualize CCF4-FRET ( Green ) and loss of FRET ( Blue ) respectively . Each sample was taken in triplicate and image acquisition was performed by automated random acquisition . Images were analyzed by Cell Profiler software to calculate the number of blue and green cells . The threshold for detection of blue signal by the software was normalized to uninfected control i . e . no blue cells could be detected in the uninfected control . The percentage of blue cells , representing the cells with cytosolic bacteria , out of total green cells was plotted . All strains were tested for their ability to cleave CCF4 in vitro , before carrying out the vacuole rupture assay . Overnight cultures grown in LB were subcultured at the ratio of 1:20 in LB with 100 μg/ml of ampicillin . After 2 hours of growth , the cultures were centrifuged and resuspended in PBS . 100 μl of this was aliquoted in 96 well plate ( Greiner , Flat-Bottom ) and 20 μl of CCF4 substrate solution ( A+B+C ) was added . Tecan fluorimeter ( Spark 20M ) was used to measure fluorescence ( excitation , 405 nm and emission , 450 nm ) using PBS as blank . Blue fluorescence ( AU450nm ) was observed for all strains and none of the mutants exhibited significantly lower value than the wild-type strain . Monocytes were issued from blood of anonymous donors obtained from the French blood bank ( Etablissement Français du Sang , approval EFS-OCPM n° 21PLER2018-0057 ) .
The ability of professional phagocytes to ingest and kill microorganisms is central to host defense and Pseudomonas aeruginosa has developed mechanisms to avoid being killed by phagocytes . While considered an extracellular pathogen , P . aeruginosa has been reported to be engulfed by macrophages in animal models . Here , we visualized the fate of P . aeruginosa within cultured macrophages , revealing macrophage lysis driven by intracellular P . aeruginosa . Two bacterial factors , MgtC and OprF , recently discovered to be involved in the intramacrophage survival of P . aeruginosa , appeared to play a role in this cytotoxicity caused by intracellular bacteria . We provided evidence that type III secretion system ( T3SS ) gene expression is lowered intracellularly in mgtC and oprF mutants . We further showed that intramacrophage P . aeruginosa uses its T3SS , specifically the ExoS effector , to promote phagosomal escape and cell lysis . We thus describe a transient intramacrophage stage of P . aeruginosa that could contribute to bacterial dissemination .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "blood", "cells", "medicine", "and", "health", "sciences", "immune", "cells", "pathology", "and", "laboratory", "medicine", "intracellular", "pathogens", "pathogens", "immunology", "cell", "processes", "microbiology", "light", "microscopy", "pseudomonas", "aeruginosa", "physiological", "processes", "microscopy", "bacteria", "bacterial", "pathogens", "research", "and", "analysis", "methods", "pseudomonas", "specimen", "preparation", "and", "treatment", "staining", "white", "blood", "cells", "tissue", "repair", "animal", "cells", "medical", "microbiology", "fluorescence", "microscopy", "microbial", "pathogens", "phagocytosis", "lysis", "(medicine)", "cell", "staining", "cell", "biology", "physiology", "biology", "and", "life", "sciences", "cellular", "types", "macrophages", "organisms" ]
2019
Killing from the inside: Intracellular role of T3SS in the fate of Pseudomonas aeruginosa within macrophages revealed by mgtC and oprF mutants
Transcriptional regulators can specify different cell types from a pool of equivalent progenitors by activating distinct developmental programs . The Glass transcription factor is expressed in all progenitors in the developing Drosophila eye , and is maintained in both neuronal and non-neuronal cell types . Glass is required for neuronal progenitors to differentiate as photoreceptors , but its role in non-neuronal cone and pigment cells is unknown . To determine whether Glass activity is limited to neuronal lineages , we compared the effects of misexpressing it in neuroblasts of the larval brain and in epithelial cells of the wing disc . Glass activated overlapping but distinct sets of genes in these neuronal and non-neuronal contexts , including markers of photoreceptors , cone cells and pigment cells . Coexpression of other transcription factors such as Pax2 , Eyes absent , Lozenge and Escargot enabled Glass to induce additional genes characteristic of the non-neuronal cell types . Cell type-specific glass mutations generated in cone or pigment cells using somatic CRISPR revealed autonomous developmental defects , and expressing Glass specifically in these cells partially rescued glass mutant phenotypes . These results indicate that Glass is a determinant of organ identity that acts in both neuronal and non-neuronal cells to promote their differentiation into functional components of the eye . Cell fate specification is achieved by integrating extrinsic signals with intrinsic transcriptional and epigenetic networks [1–3] . Certain transcription factors have been described as “master regulators” for their ability to specify entire organs [4–6] , while downstream “terminal selectors” activate genes necessary to confer a specific cellular identity [7–9] . At intermediate levels of the hierarchy , other transcription factors endow progenitor cells with the ability to give rise to broad categories of cell types distinguished by their function or position [4 , 10 , 11] . In general , these mechanisms are thought to gradually narrow the fate choices available to each progenitor cell . It is not known whether distinct cell types within the same organ may share a common transcriptional signature . The Drosophila eye consists of photoreceptor neurons and non-neuronal support cells that develop from a single field of uncommitted progenitor cells in the larval eye imaginal disc [12 , 13] , which is specified by a network of transcription factors encoded by the retinal determination genes [14] . Differentiation of the eye disc proceeds in a posterior to anterior wave driven by Hedgehog ( Hh ) signaling and led by an indentation known as the morphogenetic furrow [12 , 15 , 16] . This process gives rise to regularly spaced clusters of cells in which progenitor cells are sequentially specified as photoreceptors R1-R8 and the four lens-secreting cone cells [17 , 18] . The remaining cells rearrange their positions and reduce their numbers during pupal development to produce a lattice of optically insulating pigment cells and mechanosensory bristles [19 , 20] . Signaling between these differentiating cells , most notably through the Epidermal Growth Factor Receptor ( EGFR ) and Notch pathways , plays an important role in assigning uncommitted cells to photoreceptor , cone or pigment cell fates [21] . Each cell’s transcription factor content is also critical in determining how it responds to these signals [22–24] . The zinc finger transcription factor Glass ( Gl ) has been assigned a central role in specifying photoreceptor identity downstream of the retinal determination gene network [25–27] . In gl mutants , presumptive photoreceptors acquire neuronal characteristics , but fail to differentiate and do not express Rhodopsins or the phototransduction machinery [25 , 27 , 28] . These studies support the model that Gl drives the transition from a neuronal to a photoreceptor cell fate . Nevertheless , Gl expression is not confined to photoreceptors; it is present in all cells in the eye disc posterior to the morphogenetic furrow , and is dynamically expressed in all cell types during pupal development [26 , 29] . While cone cells and pigment cells are still present in gl mutants , their numbers and morphology are abnormal , giving rise to the “glassy” phenotype that was the basis for the original identification of gl , and pigmentation is reduced [25 , 30] . These defects have been considered to be a secondary consequence of abnormal photoreceptor development , as early studies suggested that Gl function was negatively regulated in non-neuronal cells [29]; however , its possible autonomous role in the development of these cell types has not been addressed . Misexpression of Gl in the larval central nervous system has been shown to induce the expression of a subset of photoreceptor-specific genes [27] . As a first step towards investigating whether Gl function is restricted to neuronal lineages , we compared the effects of misexpressing it in different developmental contexts . We found that Gl was able to induce expression of the photoreceptor-specific gene chaoptin ( chp ) both in neuroblasts in the brain and in non-neuronal epithelial cells of other imaginal discs , independently of the retinal determination gene network . Transcriptomic analysis revealed distinct but overlapping sets of genes induced in these two cellular contexts , including genes characteristic of non-neuronal cone and pigment cells . Gain-of-function , rescue and loss-of-function experiments all supported autonomous roles for Gl in the normal differentiation of these non-neuronal cells of the eye as well as of photoreceptors . Furthermore , we identified several elements of a transcription factor network that cooperates with Gl to induce genes characteristic of cone and pigment cells . These results indicate that Gl is not a photoreceptor-specific factor , but a determinant of organ identity that is reiteratively used to promote the terminal differentiation of multiple cell types in the eye . Gl is expressed in differentiating cells in the eye imaginal disc ( Fig 1A ) and is required for the expression of photoreceptor-specific genes such as chaoptin ( chp ) ( Fig 1B and 1D ) in cells that have been specified to become neurons [25] . However , Gl expression has also been noted in the non-neuronal cone cells and pigment cells of the eye [26 , 29] . To test whether Gl activity is limited to neuronal cells , we generated two transgenic lines , UAS-gl-RA and UAS-gl-RB , in which the UAS promoter drives each of the gl isoforms annotated in Flybase ( Fig 1C ) . gl-RA encodes a protein of 604 amino acids , containing five zinc fingers of which only the final three are essential for DNA binding [26 , 31] , and could also produce a 679 amino acid protein , Gl-RC , by readthrough of the stop codon . gl-RB is predicted to retain an intron that would introduce a frameshift leading to protein termination in the middle of the last zinc finger . However , our RNA-seq data indicated that the intron in gl-RB was spliced out in vivo ( Fig 1C ) , suggesting that its apparent retention was an artifact of cDNA preparation . Expressing either Gl isoform in gl mutant clones restored Chp expression , confirming that both transgenes are functional ( Fig 1E and 1F ) . We used the two transgenes interchangeably in subsequent experiments . As Gl was thought to drive the transition from a neuronal to a photoreceptor cell fate , we first tested the effects of misexpressing it in neural progenitors in the developing embryo and the larval brain . Endogenous Chp expression in the embryo is confined to larval photoreceptors in the Bolwig organ ( S1A Fig ) , and the protein is present in photoreceptor axons and their terminals in the optic lobes of the third instar larval brain ( Fig 2A ) . We found that misexpressing Gl in neuroblasts using asense ( ase ) -GAL4 , deadpan ( dpn ) -GAL4 or inscuteable ( insc ) -GAL4 drivers , together with a temperature-sensitive form of GAL80 to bypass early lethality , led to induction of Chp in some cells in the central nervous system ( CNS ) of the developing embryo ( S1B Fig ) and in the central region of the larval brain and ventral nerve cord ( Fig 2B , 2C and 2E ) . The expression of Chp and Gl was not confined to cells that expressed UAS-CD8-GFP from the neuroblast driver ( S2B–S2D Fig ) . As Gl can autoregulate its expression [26 , 32] , this observation suggested that Gl could be maintained in differentiating cells derived from the neuroblast lineage , and continue to induce ectopic Chp expression in these cells . To determine whether target gene induction in differentiating neuroblast progeny required sustained expression of Gl , we expressed Gl in neuroblasts but blocked its expression in differentiating neurons with GAL80 driven by the pan-neuronal elav promoter . Under these conditions , we no longer observed ectopic Chp expression in the ventral nerve cord ( Fig 2F ) , indicating that Gl expression must be maintained to induce Chp in this region . Driving Gl expression specifically in differentiated neurons with elav-GAL4 also led to ectopic expression of Chp in the embryonic and larval CNS ( Fig 2G , S1C Fig ) . In contrast , misexpressing Gl in glial cells with reversed polarity ( repo ) -GAL4 or in sensory organ precursors with atonal ( ato ) -GAL4 did not result in ectopic Chp expression ( Fig 2H and 2I , S1D and S1E Fig ) . These results indicate that Gl is not sufficient for chp transcription , but acts in combination with other sequence-specific transcription factors or chromatin regulators that are present in a subset of neuronal cell types . A previous study suggested that Gl function was negatively regulated in non-neuronal cells , as ubiquitous Gl expression activated a reporter driven by Gl binding sites derived from the proximal enhancer of Rhodopsin 1 ( Rh1 ) specifically in neurons [29] . However , during normal eye development Gl is expressed earlier than neuronal markers such as Elav [26] ( S4B Fig ) , and its expression is maintained in non-neuronal cone and pigment cells through early pupal stages [26 , 29] . We therefore tested the effect of misexpressing Gl in developing leg and wing imaginal disc cells , which are epithelial progenitors similar to the first cells that express Gl in the eye disc . When we used Ultrabithorax ( Ubx ) -FLP and the MARCM system to express Gl in clones of epithelial cells in the wing imaginal disc ( Fig 3A ) , we detected Chp expression within the clones ( Fig 3B ) . Although not all of the clones misexpressing Gl activated Chp , we did not observe any consistent positional bias; the variability may have been related to the timing of Gl induction , as Ubx-FLP is active throughout wing disc development [33] . The cells that expressed Gl and Chp did not misexpress Elav ( Fig 3A and 3B ) , indicating that they were neither originally fated to become neurons , nor converted to a neuronal fate by Gl . Similarly , when we misexpressed Gl in the leg disc using the Distal-less ( Dll ) driver , we observed ectopic Chp expression in Elav-negative cells ( Fig 3E ) . Gl is thus capable of activating the transcription of photoreceptor-specific genes in non-neuronal epithelial cells . During normal eye development , gl expression is under the direct transcriptional control of Sine oculis ( So ) , a retinal determination factor that forms a compound transcription factor with Eyes absent ( Eya ) [27 , 34]; gl can also be induced by the combination of Eya and Dachshund [35] . Consistent with the absence of Eya expression in the wild type wing disc epithelium [36] , we found that Gl was still able to induce Chp when expressed in eya mutant clones ( Fig 3C ) . This result is consistent with Gl acting as a downstream effector of the retinal determination gene network . To determine how a neuronal or non-neuronal cell context might influence Gl activity , we used RNA-Seq to examine changes in the transcriptome induced by Gl misexpression . For the neuronal misexpression condition , we used gl mutant third instar larval brains in which Gl expression was driven in neuroblasts by insc-GAL4 in combination with tubulin ( tub ) -GAL80ts ( Fig 2D ) . Using a gl mutant removed the contribution of clock cells in the brain that express Gl [37] and of mRNAs present in the photoreceptor axons that innervate the optic lobes . For epithelial misexpression , we used larval wing discs in which clones of cells generated with Ubx-FLP expressed Gl under the control of tubulin-GAL4 ( Fig 3A and 3B ) . For comparison , we also sequenced the transcriptomes of wild-type larval eye discs , wing discs , wild-type and gl mutant brains . Fig 4A shows a heat map of 188 genes that were induced at least two-fold ( with p<0 . 01 ) in Gl-misexpressing wing discs and/or brains , with additional cutoffs to eliminate genes that were expressed at very low levels or had a large variance between the triplicate samples ( S1 Table ) . A core set of Gl target genes were induced in both tissues , enriched in wild-type eye discs compared to wing discs or brains , and reduced in gl mutant eye discs [38] . These include genes involved in photoreceptor differentiation , phototransduction , neurotransmitter reception , and pigment synthesis . In addition , we detected induction of genes with no previously described function in eye development ( Table 1 , S1 Table ) , but that are highly enriched in photoreceptors or cone cells in the developing or adult Drosophila eye [39] . Surprisingly , Gl induced many more genes in the wing disc than in the brain ( Fig 4A and 4B ) . Some of the genes induced only in the wing disc are already as highly expressed in wild-type brains as in eye discs ( Fig 4C ) . However , other genes were induced in only one of the two tissues even though endogenous expression was low in both ( Fig 4C; Table 1 ) , presumably reflecting regulation by tissue-specific activators or repressors . Two previous studies predicted a set of genes likely to be direct targets of Gl activation based on the presence of clustered Gl binding sites in their regulatory regions and either reduced expression in gl mutant eye discs , or covariation with Gl across a variety of cell types and genetic conditions [38 , 40] . Although some of these predicted target genes were induced by Gl misexpression in one or both tissues , many were not . We found only 13 of the 89 Gl targets predicted by [40] were significantly induced in either condition ( Fig 4B , S3 Fig , S1 Table ) . One reason for this could be that the region searched for Gl binding sites included the first intron [38] , which varies dramatically in length across different genes . The presence of potential Gl binding motifs is more likely to be significant in short than long sequences , and among the predicted target genes the length of the first intron was inversely correlated with the probability that the gene was induced in our experiments ( S3A and S3B Fig ) . We also note that this prediction method missed the validated direct target genes PvuII-PstI homology 13 ( Pph13 ) and prospero ( pros ) [27 , 28 , 30] . The ability of Gl to induce genes that contain Gl binding motifs is also likely to depend on their responsiveness to other transcriptional activators and repressors present in the cell . A search for motifs that were enriched in the regulatory regions of genes induced by Gl , relative to predicted targets that were not induced , identified a motif matching the binding site for Grainyhead ( Grh ) ( Fig 4D ) , a transcription factor that correlates with sites of open chromatin in the eye disc [40] . This suggests that chromatin structure controls the access of Gl to its binding sites . Our observation that Gl could activate gene expression in non-neuronal cells raised the possibility that its expression in the non-neuronal cell types in the eye [26 , 29] might correlate with a functional role there . Further evidence suggesting a function for Gl in cone and pigment cells came from the nature of the genes that were induced by Gl misexpression . While many of these genes are known to act in photoreceptors , including Pph13 , Eye-enriched kainate receptor ( Ekar ) and the phototransduction component inactivation no afterpotential C ( inaC ) [41–43] , Gl also induced genes that are highly enriched in cone cells , such as sallimus ( sls ) , obstructor-B ( obst-B ) , peste ( pes ) and the glial marker wrapper [39 , 44] . We confirmed that Gl-expressing clones in the wing disc autonomously induced Cut , a transcription factor specific to cone cells and bristle cells in the retina [45] ( Fig 5A ) , and Sls ( Fig 5C ) , which is enriched in cone cell feet in the pupal retina and lost from them in gl mutant clones ( Fig 6G ) . Expression of these markers was not due to secondary induction of cone cells by Gl-expressing photoreceptors through Notch signaling [46] , as it did not require the function of the Notch ligand Delta ( Dl ) in the Gl-expressing cells ( Fig 5B and 5D ) . In addition to inducing cone cell markers , Gl misexpression led to the induction of pigment synthesis genes such as cardinal ( cd ) and rosy ( ry ) [47 , 48] . Consistent with induction of these genes , misexpression of Gl in clones of cells with eyeless ( ey ) -FLP or Ubx-FLP led to the appearance of ectopic red pteridine pigment , normally only produced by pigment cells in the eye [19] , on the adult legs and abdomen ( Fig 5E–5G ) . gl mutants exhibit numerous defects in cone and pigment cell differentiation . The number of cone cells is reduced ( Fig 6C and 6D ) , there is significantly less eye pigmentation ( Fig 7D and 7F ) and the morphology of cone and pigment cells is abnormal [25 , 28] ( Fig 6C ) , giving the eye a glassy appearance . However , these defects have been thought to arise as a secondary consequence of abnormal photoreceptor differentiation , and a possible autonomous requirement for Gl in these cells has not been examined . To test whether endogenous Gl has an autonomous function in cone and pigment cells , we used our UAS-gl transgene to restore Gl to specific cell types in a gl mutant background . Expressing gl in cone cells and primary pigment cells with sparkling ( spa ) -GAL4 [49] or in interommatidial secondary and tertiary pigment cells with 54-GAL4 [50] each produced a partial rescue of the mutant phenotype . Restoring Gl only in cone and primary pigment cells increased the number of cone cells per ommatidium ( Fig 6B and 6D ) , consistent with an autonomous function of Gl within the cone cells that is independent of its role in photoreceptors . Restoring Gl only in the interommatidial pigment cells increased the level of pteridine eye pigments compared to gl mutant eyes with no rescue construct ( Fig 7C , 7D and 7F ) . These results support an autonomous effect of Gl on the differentiation of the non-neuronal cell types of the eye . Restoring Gl specifically to photoreceptors with elav-GAL4 produced a similar partial rescue of cone cell number and pigmentation ( Fig 6D , Fig 7B and 7F ) , indicating that Gl also acts upstream of the signals produced by photoreceptors that induce the differentiation of other cell types . We next wished to remove gl function from specific cell types . As the gl transgenic RNAi lines available did not fully reproduce the gl phenotype even when expressed ubiquitously throughout eye development , we used the CRISPR-Cas9 method to generate somatic gl mutations in a cell-type specific manner [51] . We generated a transgenic line that expressed two synthetic guide RNAs ( sgRNAs ) targeting gl ( S4A Fig ) , and crossed it to UAS-Cas9 in a heterozygous gl mutant background . Expression of Cas9 throughout the eye disc beginning early in development with ey3 . 5-FLP and Act>CD2>GAL4 [52] resulted in mosaic eyes with patches resembling the gl mutant phenotype ( S4C and S4D Fig ) . A weaker phenotype was obtained when we removed Gl specifically from photoreceptors using elav-GAL4 ( S4E–S4G Fig ) . A majority of Elav+ photoreceptors lost Gl expression , but Gl was still detected in the interommatidial cells , confirming that our CRISPR approach was cell type-specific ( S4E and S4F Fig ) . Defects in the development of the non-neuronal cells were nevertheless observed ( S2 Table ) , again consistent with reduced non-autonomous signaling by gl mutant photoreceptors . To test the role of Gl in cone cells and primary pigment cells we used spa-GAL4 to express Cas9 . Although Gl is not detectable in cone cells by 42h after puparium formation ( APF ) in the wild-type pupal retina , it is present during cone cell specification and in pupal primary pigment cells [29] . Gl expression was lost from a subset of presumptive cone cells marked by Pax2 in the third instar larval eye disc in spa-driven CRISPR mutagenesis ( S4I Fig ) . At 42h APF we observed defects in the number and arrangement of cone cells and primary pigment cells , and perhaps as a secondary consequence , defects in the interommatidial cells ( Fig 6E and 6H , S5A–S5E Fig , S2 Table ) . Although the expression of cone cell markers such as N-cadherin ( Ncad ) [53] and Fasciclin III ( FasIII ) [39] was unaffected ( Fig 6E ) , Sls was depleted from cone cell feet when gl was mutated in these cells by driving Cas9 with spa-GAL4 ( Fig 6F ) . Expression of Cas9 with 54-GAL4 resulted in loss of Gl from the interommatidial cells ( S4K and S4L Fig ) , defects in the pigment cell lattice ( Fig 7G and 7H , S5F–S5J Fig , S2 Table ) , and loss of pigment in patches in the adult eye ( Fig 7E ) . These GAL4 lines were specific to the non-neuronal cells , as very few photoreceptor defects were observed ( S5K Fig ) . These results demonstrate that Gl autonomously promotes the differentiation of all the cell types of the eye . Our finding that Gl acts autonomously in photoreceptors , cone cells and pigment cells raises the question of how it activates a different set of genes in each cell type . Gl has been shown to cooperate with the downstream transcription factor Pph13 to induce and maintain photoreceptor-specific gene expression [27 , 32] , and Orthodenticle also plays a role in regulating terminal differentiation of photoreceptors [41] . We therefore focused on identifying transcription factors that might help Gl to activate cone or pigment cell genes . Pax2 is a transcription factor that is specifically expressed in cone and primary pigment cells [54] , independently of Gl ( S4J Fig ) , and is required for their development [24 , 54] . It also shares many predicted target genes with Gl [40] . We found that coexpressing Pax2 with Gl in clones in the wing disc prevented induction of the photoreceptor-specific gene chp ( Fig 3D ) , consistent with the previously reported anti-neuronal function of Pax2 [24] , and enabled the induction of eya , which was induced in very few cells by either factor alone ( Fig 8A–8C ) . Eya is specifically expressed in non-neuronal cells at pupal stages [55] and has a late function in their terminal differentiation , independent of its early role in retinal determination [56 , 57] . Consistent with this function , coexpressing Eya with Gl enabled it to induce lozenge ( lz ) ( Fig 8D–8F ) , which encodes a transcription factor that is expressed in late-differentiating cells including the cone and pigment cells and is necessary for their differentiation [23 , 58 , 59] . Gl is necessary for lz expression [60] but not alone sufficient to induce it in the wing disc ( Fig 8D ) . Gl and Lz are known to cooperatively activate the expression of Pros , which cooperates with Pax2 to promote cone cell differentiation [24 , 30] , and are predicted to co-regulate many additional targets [40] . We found that in combination but not individually , Gl and Lz were able to induce ectopic pros and homothorax ( hth ) expression in the wing disc ( Fig 8G–8I ) . Interestingly , Pros staining appeared largely cytoplasmic , a localization seen in mature cone cells but not in R7 photoreceptors , where it is nuclear [39 , 61] . Hth is specific to pigment cells at pupal stages [62] . In clones misexpressing both Gl and Lz , Pros-expressing cells were often surrounded by Hth-expressing cells ( Fig 8I ) , reflecting the relative positions of cone and pigment cells in normal development . Gl was still able to induce ectopic pigment when expressed in hth mutant clones ( Fig 8L ) ; however , Escargot ( Esg ) , another transcription factor specific to pupal pigment cells [63] that is also predicted to coregulate Gl target genes [40] , showed a clear cooperative interaction with Gl . Coexpressing Esg with Gl in clones generated with Ubx-FLP strongly enhanced ectopic pigment formation ( Fig 8M–8O ) , while Gl failed to induce pigment when expressed in esg mutant clones ( Fig 8K ) . Esg is generally thought to be a repressor [64] , so its effect on the induction of pigment synthesis genes is likely to be indirect . Together , these results show that other transcription factors influence the set of target genes that Gl is able to activate , and suggest a preliminary model for the transcriptional control of cell type differentiation in the eye ( Fig 8P ) . Context-dependent effects on transcription factor activity have been well documented [65–71] . Our transcriptomic analysis shows that Gl can activate some of its target genes in cells that have either a neuronal or an epithelial identity , while others are activated in only one of the two contexts . As Gl is expressed earlier than neuronal markers [26] , it may act in epithelial progenitors in the eye disc prior to their neuronal differentiation . The developing eye and wing discs are distinguished by the expression of the retinal determination genes in the eye disc primordium [14] . One important function of this gene network is to induce Gl , which then directs eye disc cells to differentiate as components of the retina [27 , 52] . The wing disc shares common signaling pathways with the eye disc , such as Hh , EGFR and Notch , which may enable Gl to activate some of its target genes in this context . Similarly , Decapentaplegic ( Dpp ) pathway activity appears to aid the ability of the “master transcriptional regulator” Eyeless/Pax6 to induce ectopic eye formation [35 , 72] . The effect of Gl also depends on other cell type-specific transcription factors . A Gl binding site from the Rh1 proximal enhancer drives more restricted reporter expression when adjacent sequences are included , supporting the existence of a repressor that can counteract activation by Gl [29] . The presence of such repressors or the absence of coactivators probably explains why only a few of the previously predicted Gl target genes [40] were induced by Gl misexpression in the wing disc or brain , and tissue-specific cofactors are likely to contribute to differential induction in the two contexts . We identified Pax2 , Eya , Lz and Esg as transcription factors that can alter the spectrum of genes induced by Gl misexpression in the wing disc . In addition , the chromatin landscape may affect the availability of Gl binding sites . The enrichment of a Grh binding motif in genes that were induced by Gl suggests that Gl requires an open chromatin state to activate transcription [40] , and is thus not a pioneer transcription factor [73] . Similarly , the C . elegans Gl homologue CHE-1 , which is required for the expression of genes specific to the ASE gustatory neurons [74] , can reprogram other cells into ASE neurons only when factors that promote chromatin-mediated repression are removed , indicating that its ability to activate target genes is influenced by their chromatin state [71 , 75–77] . The duration of Gl expression may also influence its ability to activate target genes . Previous studies which concluded that Gl was not sufficient to activate photoreceptor-specific genes in non-neuronal cells used transient misexpression from a heat shock promoter [29] . However , we found that maintenance of Gl expression in the differentiated progeny of neuroblasts was necessary to induce ectopic chp expression . Extended expression may allow Gl to induce its target gene Pph13 , which is necessary for the ectopic induction of genes such as Rh1 and the phototransduction components inactivation no afterpotential D and Arrestin 1 [27] . This feed-forward mechanism could contribute to the specificity of photoreceptor determination . In general , cell fate specification is viewed as a series of decision points at which the expression of different transcription factors directs cells towards progressively restricted fates [10] . Downstream of factors that define broad spatial or temporal identities [78] , “master regulators” such as Pax6 specify a field of multipotent progenitors within which patterned differentiation of all the cell types of the organ can occur [6] . Terminal selector genes are thought to be confined to specific cell types and directly induce their differentiated properties [8] . Gl was previously viewed as a terminal selector gene for photoreceptor identity [25 , 27 , 28] . However , Gl is present in cone and pigment cell precursors in addition to photoreceptors [26 , 29] and regulates the expression of genes such as lz and pros that are expressed in both photoreceptors and cone cells [30 , 60] . Our cell type-specific rescue and loss-of-function experiments show that the abnormal arrangement and differentiation of non-photoreceptor cells in gl mutant eyes is not simply a secondary consequence of the effect of gl on photoreceptors; instead , gl also acts autonomously in cone and pigment cells to regulate their number , arrangement and gene expression . In addition , ectopic Gl is capable of inducing genes specific to cone cells and the synthesis of red pteridine pigments that are normally made by secondary and tertiary pigment cells [19] . Gl thus appears to be a terminal differentiation factor for multiple cell types of the eye rather than a photoreceptor determinant . Few factors that confer organ identity on multiple distinct cell types have been described; for instance , differentiation of endocrine and exocrine cells in the pancreas appears to involve entirely distinct transcriptional regulatory networks [79] . In plants , however , different combinations of transcription factors produce different floral components , such that each transcription factor contributes to specifying multiple cell types of the flower [80] . As Gl itself does not distinguish photoreceptors from non-neuronal eye cells , its transcriptional targets must depend on other factors that control the identity of each cell type . The EGFR and Notch signaling pathways are important for recruiting both photoreceptor and non-photoreceptor cell types , and the transcription factors downstream of these pathways directly regulate cell type-specific genes [24 , 81] . Although EGFR signaling has a direct or indirect effect on the differentiation of all cell types except R8 [17 , 82 , 83] , the level of signaling can influence cell fate specification . For example , activation of the Sevenless receptor increases Ras-MAPK signaling in R7 relative to cone cells; this allows the repressor Tramtrack to be degraded , leading to high level expression of genes that promote neuronal identity [23 , 84 , 85] . Combinatorial effects of the two pathways contribute to cell type-specific expression of genes such as Pax2 [59] . Our experiments suggest that Pax2 and Esg can modify the effects of Gl to promote the induction of cone and pigment cell genes respectively through a network of other downstream transcription factors . The level of Gl could also affect which target genes it activates; Gl expression is reduced in cone cells during pupal development [29] , and different levels of a transcription factor can specify different cell fates in other systems [86 , 87] . In addition , the time of cell differentiation could play a role; for instance , neuroblasts express a temporal series of transcription factors that specify different identities in their progeny [88 , 89] . Lz , a transcription factor that contributes to specifying R1 , R6 , R7 and the cone and pigment cells [22 , 23 , 58 , 59] , is a target of Gl regulation and is also predicted to act in combination with Gl to control many common target genes , suggesting that it functions as a feed-forward temporal determinant [40 , 60 , 90] . We found that Lz can indeed bias transcriptional activation by Gl towards genes expressed in later-differentiating cell types . The distinct effects of different combinations and levels of transcription factors and signaling pathways demonstrate how unique cell fates can be specified from a common pool of progenitors using few factors . Nevertheless , our understanding of cell type specification in the eye is probably still incomplete; for instance , analysis of the spa enhancer that drives Pax2 expression in cone cells revealed many essential inputs in addition to the previously established regulation by EGFR signaling , Notch signaling and Lz [59 , 91] . A fuller understanding of the network that modifies the transcriptional activity of Gl may hold the key to the problem of cell fate specification . UAS-gl-RB was made by cloning the gl cDNA from clone GH20219 ( Drosophila Genomics Resource Center ) into pUASTattB using EcoRI and XhoI . A 1 . 5 kb NdeI/XhoI fragment lacking the intron was generated by overlap PCR and used to replace the corresponding region of UAS-gl-RB to generate UAS-gl-RA . Both constructs were integrated into the VK37 attP site at position 22A3 . The gl sgRNA sequences identified on www . flyrnai . org/crispr2/ [92] , GCAGGATAGGCAGCCGACGC ( gl gRNA 1 ) and TACCCACCGCTGCTGAGTCC ( gl gRNA 2 ) were cloned into pCFD4 [51] by PCR and Gibson assembly , and the construct was integrated into the attP40 site at 25C6 . Injections and screening of transgenic flies were carried out by Genetivision . Stocks used to generate clones were ( 1 ) UAS-gl-RA; FRT82 , gl60j ( 2 ) UAS-gl-RB; FRT82 , gl60j ( 3 ) UAS-CD8-GFP , ey-FLP; tub-GAL4 , FRT82 , tub-GAL80/TM6B ( 4 ) UAS-CD8-GFP , Ubx-FLP; tub-GAL4 , FRT82 , tub-GAL80/TM6B ( 5 ) UAS-gl-RB; FRT82 , P ( w+ ) ( 6 ) FRT82 , gl60j ( 7 ) UAS-glRB; FRT82 , DlRevF10 ( 8 ) FRT42; UAS-Pax2 ( 9 ) FRT42 , UAS-glRB; UAS-Pax2 ( 10 ) UAS-CD8-GFP , Ubx-FLP; FRT42 , tub-GAL80; tub-GAL4/TM6B ( 11 ) FRT42 , UAS-glRB ( 12 ) FRT42 , UAS-glRB; UAS-eya ( 13 ) FRT42; UAS-eya ( 14 ) UAS-glRB; FRT82 , UAS-lz ( 15 ) FRT82 , UAS-lz ( 16 ) FRT42 , UAS-glRB; UAS-esg ( 17 ) UAS-esg; FRT82 ( 18 ) UAS-glRB; FRT82 , hthB2 ( 19 ) esg66B , FRT40 , UAS-glRB ( 20 ) eyaE18B , FRT40 , UAS-glRB ( 21 ) UAS-CD8-GFP , Ubx-FLP; FRT40 , tub-GAL80; tub-GAL4/TM6B . Stocks used for misexpression were ( 1 ) dpn-GAL4 ( 2 ) elav-GAL80; dpn-GAL4 ( 3 ) elav-GAL4 ( 4 ) repo-GAL4 ( 5 ) ase-GAL4 ( 6 ) ato-GAL4 ( 7 ) insc-GAL4 ( 8 ) UAS-CD8-GFP; UAS-gl-RB; tub-GAL80ts ( 9 ) Dll-GAL4 ( 10 ) insc-GAL4; tub-GAL80ts , gl60j . Stocks used for rescue were ( 1 ) spa-GAL4; gl60j ( 2 ) 54-GAL4 , UAS-lacZ; gl60j ( 3 ) UAS-gl-RB , UAS-lacZ; gl2 . Stocks used for CRISPR were ( 1 ) ey3 . 5-FLP , Act>CD2>GAL4; UAS-Cas9P2 , gl60j/TM6B ( 2 ) elav-GAL4; UAS-Cas9P2 , gl60j/SM6-TM6B ( 3 ) spa-GAL4; UAS-Cas9P2 , gl60j/TM6B ( 4 ) 54-GAL4 , UAS-lacZ; UAS-Cas9P2 , gl60j/SM6-TM6B ( 5 ) gl sgRNAs ( attP40 ) . Transgenic lines other than UAS-gl and gl sgRNAs are described in Flybase . Embryos and larval eye discs , wing discs and brains were stained as described [93 , 94] , fixing 30 min in 4% formaldehyde in 0 . 1M PIPES pH 7 . 0/2mM MgSO4/1mM EGTA for most antibodies but 45 min in 2% formaldehyde in 75mM lysine/370mM sodium phosphate pH 7 . 2/10mM NaIO4 for anti-Gl . Pupal retinas were fixed and stained as described [95] . Antibodies used were mouse anti-Gl ( 1:10; Developmental Studies Hybridoma Bank ( DSHB ) , mouse anti-Chp ( 1:50; DSHB ) , chicken anti-GFP ( 1:300; Aves ) , rat anti-Elav ( 1:100; DSHB ) , mouse anti-Cut ( 1:10; DSHB ) , rabbit anti-β-galactosidase ( 1:5000; Cappel ) , rat anti-Ecad ( 1:10; DSHB ) , mouse anti-FasIII ( 1:10; DSHB ) , rat anti-Ncad ( 1:10; DSHB ) , rat anti-Kettin/Sls ( 1:200; Abcam ) , mouse anti-Eya ( 1:10; DSHB ) , mouse anti-Lz ( 1:10; DSHB ) , mouse anti-Pros ( 1:10; DSHB ) , rabbit anti-Hth ( 1:200 ) [96] , rat anti-Pax2 ( 1:500 ) [24] and mouse anti-Arm ( 1:10; DSHB ) . Secondary antibodies were from Jackson Immunoresearch ( Cy3 or Cy5 conjugates used at 1:200 ) or Invitrogen ( Alexa488 conjugates used at 1:1000 ) . Images were captured on a Leica SP5 confocal microscope and processed using ImageJ and Adobe Photoshop . Cone cell counts were performed using ImageJ . Pigment quantification was performed as described [97] with the following modification: for each sample , 30 heads from 3–5 day old adult females were homogenized in 0 . 5mL of 0 . 1M HCl in ethanol . OD480 values were obtained using the homogenizing solution as a blank . Larval tissue was isolated from 30 animals of each genotype in triplicate and RNA was extracted in Trizol ( Invitrogen ) . Library preparation and sequencing was carried out by the NYU Genome Technology Center . RNA-Seq library preps were made using the Illumina TruSeq RNA sample Prep Kit v2 ( Cat #RS-122-2002 ) , using 500 ng of total RNA as input , amplified by 12 cycles of PCR , and run on an Illumina 2500 ( v4 chemistry ) , as single read 50 . For each RNA-seq sample , sequence quality was assessed with FastQC ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc ) and sequencing adapters were removed with Trimmomatic [98] . Cleaned reads were aligned to the Drosophila reference genome ( dm3 ) with Tophat2 v2 . 1 . 1 1 . The Picard CollectRnaSeqMetrics program ( https://broadinstitute . github . io/picard/picard-metric-definitions . html#RnaSeqMetrics ) was used to generate QC metrics including ribosomal RNA content , median per-gene coverage , bases aligned to intergenic regions , 5’/3’ biases , and the distribution of the bases within exons , UTRs , and introns . Per sample gene expression profiles were computed using Cufflinks v2 . 2 . 1 1 and the RefSeq genome annotation for the Drosophila reference genome dm3 [99] . For multi-sample comparison , Principal Component Analysis and hierarchical clustering were used to verify that the expression profiles of the sequenced samples clustered as expected by sample tissue and genotype . Differential gene expression was computed for various contrasts between genotypes with the Cufflinks protocol [100] with default thresholds . Reads on the gl gene were visualized with Integrative Genomics Viewer ( IGV , Broad Institute ) . Genes were considered significantly changed and included in the heat map if the log2 fold change for either wing or brain misexpression was >1 , p<0 . 01 , average cpm for that misexpression condition was >1 , and standard deviation/mean of the three replicates was <0 . 5 . Intron sizes were obtained from Flybase and compared for targets predicted with high confidence by [40] that were induced ( log fold change >1 in either or both tissues ) or not induced ( log fold change <0 . 1 in both tissues ) . Homer was used to identify motifs enriched in the genes included in the heat map compared to predicted targets that were not induced in either tissue , using a region that extended 2 kb upstream and downstream of each gene . RNA-Seq data have been submitted to NCBI GEO ( reference number GSE99303 ) .
Distinct cell types within an organ are specified by the activity of cell type-specific transcription factors , which activate distinct gene networks that confer the appropriate cellular identities . The Drosophila eye is derived from a field of equivalent progenitors that develop into photoreceptor neurons as well as non-neuronal cone and pigment cells . The zinc finger transcription factor Glass was thought to solely determine the photoreceptor identity . Here we show that Glass acts not only in photoreceptors , but also in the non-neuronal support cells of the eye , promoting the normal differentiation of each cell type . Loss of Glass in non-neuronal cells results in developmental defects , and these defects can be rescued by restoring Glass specifically to those cell types . We used misexpression assays to show that Glass is sufficient to induce markers of photoreceptors , cone cells and pigment cells , and we identified certain transcription factors that may cooperate with Glass to specify these non-neuronal cells . These results suggest that the role of Glass is to give each cell type its identity as a component of the eye . The transcriptional code that defines cell identities must thus include factors such as Glass that mark the cell as belonging to a specific organ .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "medicine", "and", "health", "sciences", "gene", "regulation", "regulatory", "proteins", "neuronal", "differentiation", "dna-binding", "proteins", "social", "sciences", "cloning", "neuroscience", "pigments", "cell", "differentiation", "dna", "transcription", "developmental", "biology", "materials", "science", "transcription", "factors", "molecular", "biology", "techniques", "eyes", "research", "and", "analysis", "methods", "animal", "cells", "proteins", "gene", "expression", "materials", "by", "attribute", "sensory", "receptors", "head", "molecular", "biology", "biochemistry", "signal", "transduction", "cellular", "neuroscience", "psychology", "anatomy", "cell", "biology", "neurons", "genetics", "photoreceptors", "biology", "and", "life", "sciences", "ocular", "system", "physical", "sciences", "cellular", "types", "afferent", "neurons", "sensory", "perception" ]
2018
Glass promotes the differentiation of neuronal and non-neuronal cell types in the Drosophila eye
Animal tungiasis is believed to increase the prevalence and parasite burden in humans . Animal reservoirs of Tunga penetrans differ among endemic areas and their role in the epidemiology of tungiasis had never been investigated in Uganda . To identify the major animal reservoirs of Tunga penetrans and their relative importance in the transmission of tungiasis in Uganda , a cross sectional study was conducted in animal rearing households in 10 endemic villages in Bugiri District . T . penetrans infections were detected in pigs , dogs , goats and a cat . The prevalences of households with tungiasis ranged from 0% to 71 . 4% ( median 22 . 2 ) for animals and from 5 to 71 . 4% ( median 27 . 8% ) for humans . The prevalence of human tungiasis also varied among the population of the villages ( median 7% , range 1 . 3–37 . 3% ) . Pig infections had the widest distribution ( nine out of 10 villages ) and highest prevalence ( median 16 . 2% , range 0–64 . 1% ) . Pigs also had a higher number of embedded sand fleas than all other species combined ( p<0 . 0001 ) . Dog tungiasis occurred in five out of 10 villages with low prevalences ( median of 2% , range 0–26 . 9% ) . Only two goats and a single cat had tungiasis . Prevalences of animal and human tungiasis correlated at both village ( rho = 0 . 89 , p = 0 . 0005 ) and household ( rho = 0 . 4 , p<0 . 0001 ) levels . The median number of lesions in household animals correlated with the median intensity of infection in children three to eight years of age ( rho = 0 . 47 , p<0 . 0001 ) . Animal tungiasis increased the odds of occurrence of human cases in households six fold ( OR = 6 . 1 , 95% CI 3 . 3–11 . 4 , p<0 . 0001 ) . Animal and human tungiasis were closely associated and pigs were identified as the most important animal hosts of T . penetrans . Effective tungiasis control should follow One Health principles and integrate ectoparasites control in animals . Tungiasis is an ectoparasitosis that accrues from the penetration of female sand fleas into the skin . Tunga penetrans [1] and Tunga trimamillata [2] are the only species known to cause tungiasis in both humans and animals . Currently , zoonotic tungiasis is endemic in southern America , the Caribbean and sub-Saharan Africa . While T . penetrans occurs in all endemic areas , T . trimamillata has only been reported in a few countries in South America [3 , 4] . In the endemic areas , tungiasis in humans is heterogeneously distributed [5–7] . In Uganda , human tungiasis occurs in all regions but the prevalence appears to be particularly high in the Busoga sub-region , South Eastern , and Karamoja in North Eastern , Uganda [8] . These regions are among the poorest in the country . Epidemiological studies carried out in resource-poor communities in Africa and South America have reported point prevalence of up to 60% among humans [6 , 7 , 9] . Hitherto , no systemic investigations have been carried out in Uganda but an impromptu outbreak investigation in some parishes of Busoga sub-region in 2010 reported prevalences of up to 73% in the general population [8] . For Karamoja , a study conducted in Napak District in different seasons , reported prevalences ranging from 18 . 4% at the end of the rain season to 56 . 6% in the dry season [10] . In poor communities , tungiasis is associated with severe morbidity [11] leading to physical disability and immobility [12] . In addition , in non-vaccinated individuals , tungiasis predisposes to tetanus and may contribute to transmission of blood borne pathogens such as Hepatitis B Virus ( HBV ) and HIV if non-sterile instruments are used to remove embedded sand fleas and are subsequently shared between household members [13] . Deaths from tungiasis-related complications are commonly reported in Uganda [14] . T . penetrans infects a wide range of domestic , peri-domestic and wild mammals such as pigs , dogs , cats , goats , cattle , rodents , elephants , jaguars , monkeys and even armadillos . The relevance of each of the animal species in the epidemiology of human tungiasis varies from one endemic area to another . While in urban Brazil , dogs , rodents and cats are the species most frequently infected by T . penetrans , in West Africa pigs appear to be the important animal reservoirs [3 , 15–17] . In Brazil , infected animals seem to increase the risk of infection in humans and are associated with a high prevalence of tungiasis at a community level [15] . Although the economic significance of T . penetrans infections in animal production has not been systematically studied , existing literature points out a significant effect on growth rate , secondary bacterial infections and defects of limbs [3] . Tungiasis may also lower product quality and hence , marketability of animals . In sows , it has been reported to cause agalactia with subsequent starvation of piglets if it affects their mammary glands [18] . Obviously , poor production and decreased marketability perpetuate community impoverishment . To date no systematic studies have been conducted to describe the epidemiology of tungiasis in animals in East Africa . In order to identify the major animal reservoirs of T . penetrans in rural Uganda and to investigate the association between animal and human disease , a cross sectional study was carried out in ten endemic villages located in Bugiri District , Busoga sub-region . The study revealed that the prevalence of animal tungiasis was high and that the disease prevalence and parasite loads in humans and animals correlated . Pigs were identified as the most important domestic animal hosts for T . penetrans . The study was carried out in ten villages situated in Bulidha sub-county , Bugiri district , Busoga sub-region in South Eastern Uganda . Bugiri district was purposively selected amongst the ten districts of Busoga because of the high prevalence of human tungiasis reported and confirmed during a preliminary survey . Bugiri district is about 178 km in the South Eastern direction away from the capital Kampala and lies between longitude 33°10’ and 34°00’ East and latitudes 0°6’ and 1°12’ North [19] . The ten villages were; Masolya , Makoma 1 , Busakira , Busano , Isakabisolo , Namungodi , Matyama and Busindha situated in Makoma parish; Kibuye and Nagongera in Wakawaka and Bulidha parishes , respectively . These were purposively selected because human tungiasis was reported to be highly prevalent by the local health personnel , a fact which was also verified during a preliminary visit . The study area and study sites with infected hosts are illustrated in Fig 1 . Since there were no estimates regarding the size of the animal populations and prevalence of T . penetrans infections in the various animal species , a relatively large number of villages was included in the study . All households in the villages with at least a pig , a dog or a cat were selected for the study . All mammals accessible in the selected households were examined . Poultry were examined whenever available . The communities were constituted by seven tribes belonging to three ethnic groups , namely Luo ( Japadhola ) , Bantu and Nilo-hamites ( Itesot ) . People depend on rain-fed subsistence crop and livestock agriculture . Other economic activities such as fishing in Lake Victoria and temporary work in sugar and tree plantations also contribute to households’ incomes . The major crops grown in the area were maize , cassava , rice , coffee and bananas while goats , pigs and some cattle were the major livestock reared . Dogs , cats , sheep and rabbits were other domestic animal species found in the villages . In addition , a variety of poultry especially chicken and ducks , and to some extent pigeons , turkeys as well as guinea fowls are raised . Dogs , cats and poultry roam freely on compounds throughout the year . With the exception of unweaned young animals , which roam on compounds unrestricted , other livestock are tethered on or near compounds during the crop production seasons . However , they are released intermittently after harvest with minimum food supplementation . Homesteads are located on relatively large compounds that are close to gardens or bushes where household waste is dumped . All roads and paths are made of murram . The area experiences two rainy seasons; one between April and June and the other from August to November with an average annual rain fall of 1200 mm . Average daily temperatures range from 16 . 7°C to 25 . 1°C . Water is mainly obtained from communal boreholes , springs and shallow wells . Electricity is limited to major social facilities and less than 1% of the households have electricity . A cross sectional study was conducted between January 22 and March 28 , 2014 which coincided with the middle and end of the dry season when the attack rate of T . penetrans usually peaks [20] . Initially , a mission was undertaken to explain the study objectives to the local medical and veterinary health personnel as well as to the local leaders . Since the study aimed to compare the significance of different animal reservoirs , only animal rearing households were included . All households with at least one pig , dog or cat were included as these species have been reported to be the most important animal hosts of T . penetrans in sub-Saharan Africa [15 , 17] . Households meeting the selection criteria were located with the guidance of local leaders . In each consenting household , first a census of the animals and humans was performed . Then all mammals ( dogs , pigs , cats , cattle , sheep , goats and rabbits ) as well as all humans present on the compound during the investigator’s visit were examined for tungiasis . Only the poultry that were accessible were examined . If the household leader was not around , the household was visited again . Households were also revisited ( up to three times ) when any household member was not present; when some pigs , dogs or cats identified in the census could not be traced or when they ran away during the first investigation . In Masolya and Makoma 1 , which were randomly selected among the ten study villages , all remaining households with at least one goat were also sampled to obtain an unbiased sample of goats . Wherever residents claimed to have seen rats with T . penetrans , it was attempted to trap rats in cages placed in household premises and close to the entrances of termite moulds . The study objectives were explained to the household heads and informed written consent was obtained . Thereafter , data was collected on social , environmental , behavioral and animal management practices through interviewing the household head and observations . Then humans and animals were examined for T . penetrans-associated lesions . Diagnosis was made clinically and humans were examined by means of a rapid assessment method [21] . To estimate the intensity of T . penetrans in humans , lesions of a randomly selected foot of up to three randomly selected children between three and eight years of age per household were counted since this is the age group with the highest intensity of infection [6 , 7] . To perform a thorough clinical examination , mammalian and avian species were restrained physically . However , most dogs and cats could only be examined after sedation with ketamine ( Umedica Laboratories PVT . LTD , India ) and xylazine ( Xyla , Interchemie Werken , Netherlands ) . Vomiting during sedation was prevented using atropine ( Gland Pharma , M . L . 103/AP/RR/97/F/R ) . Examination of animals was systematically performed from the head , along the trunk to the tail including the lower abdomen and the limbs through observation , hair parting and palpation . Particular emphasis was given to the paws and digits for canines and ungulates , respectively . To increase the visibility of T . penetrans lesions , the distal body parts were scrubbed with a brush and water . Sex , age and breed together with the findings of a complete clinical examination of infected animals were recorded on a standardized form . Detailed information regarding infected animals such as age was obtained by asking the owners since none of the households kept written animal records . All trapped rats were euthanized by wrapping the cages in a piece of cloth immersed in diethyl-ether . Staging of lesions was performed according to the Fortaleza classification [22] . Viable stages were characterized by: presence of a dark brown to black spot surrounded by a reddened or swollen area ( stage II ) and a raised yellow to white nodule of 2–13 mm in diameter with a dark center in the skin ( stage III ) . A brown to black , circular , raised patch in the middle of a necrotic area with or without erosions or ulcers ( stage IV ) and an epidermal circular shallow crater with necrotic edges ( stage V ) were the features considered to reflect dying or dead sand fleas [22] . In humans and animals , sores indicating that an embedded parasite had been manipulated were also documented . Photographs were taken to document the findings . A total of 16 ( two , four and ten ) embedded sand fleas were carefully extracted from some goats , dogs and pigs respectively . Animals were chosen from different villages and extraction was performed by enlarging the flea pore with tweezers . Sand fleas from humans were obtained from consenting humans who were transported by car , for treatment to Bulidha Health Center III , which was the nearest Health Unit . All extracted sand fleas were preserved in 70% ethanol and examined at the College of Veterinary Medicine , Animal Resources and Biosecurity ( COVAB ) using a light stereo-microscope by looking for characteristic features as described before [3] . Some alcohol-fixed sand fleas were exported to Germany , Freie Universität Berlin for scanning electron microscopy . Before electron microscopy , sand fleas were cleaned as described previously [23] . Briefly , sand fleas were dehydrated in ethanol for two hours and then kept overnight in acetone . The following day they were transferred to individual glass containers containing xylene before sonication for 30 minutes . Then , the sand fleas were washed in acetone for two hours before they were mounted on stubs , sputtered with gold and examined with the aid of a Zeiss Supra 40 VP scanning electron microscope at the Institute of Geological Sciences , Freie Universität Berlin . Studies involving humans were conducted according to the “National Guidelines for Research involving Humans as Research Subjects” were approved by the Ministry of Health , Vector Control Division ( reference no . : VCD-IRC/054 ) . The ethical committee of the College of Veterinary Medicine , Animal Resources and Biosecurity ( reference no . : VAB/REC/14/101 ) approved the studies involving animals . In addition , approval for both animal and human studies was obtained from the National Council of Science and Technology Uganda ( reference no . : HS1621 ) . Animal studies adhered to the “Animals ( Prevention of Cruelty ) act” , chapter 39 , constitution of Uganda . Participation of humans was optional and written consent was obtained from household heads who also consented on behalf of their children as parents or guardians . All other adult household members ( from 18 years and above ) orally consented to the study , always obtained in the presence of the health workers from the nearest public health units . Only oral consent was obtained for these persons since the vast majority of participants were below 18 years and management of too many data forms was difficult under field conditions . Oral consent of the adult participants was documented on the evaluation sheets . This procedure was approved by the Ministry of Health and the National Council of Science and Technology , Uganda in the above stated documents . All humans with tungiasis were given a basic health kit consisting of a basin , a bar of soap , a sachet of detergent , individual towel , safety pins , cotton wool and an antiseptic ( Dettol , Reckitt Benchiser , Dubai ) . Such a health kit is routinely supplied by the Ministry of Health of Uganda to affected households . Severely affected humans were transported by car to the nearest health unit for medical attention . Wounds on infected dogs , goats and pigs were cleaned with clean water and soap while antiseptic treatment was conducted using iodine tincture ( SEV Pharmaceuticals Ltd , Kampala , Uganda ) or a wound spray ( Supona aerosol , Pfizer Laboratories ( Pty ) Ltd , South Africa ) . Data was entered into an Excel database ( Microsoft Office , 2007 ) and validated by checking all entries again using the data collection tools before exportation to Stata Software package , Version 13 ( Stata corporation , College Station , Texas 77845 USA ) or R 3 . 1 . 2 in R Studio 0 . 98 . 1103 via a csv text file . Either Chi-square or Fisher’s exact tests were used to determine the significance of differences between proportions . In case of multiple testing , p values were corrected with the Bonferroni-Holm method as implemented in the p . adjust function of R . The Spearman’s rank correlations coefficient was calculated to establish the relationship between pairs of continuous variables . The Wilcoxon rank sum test was used to compare differences in the number of lesions between animals and/or humans groups . Household prevalence was calculated as the proportion of households with at least one infected household member or animal to that of the total households sampled . Tungiasis prevalence among animals and humans was computed as the proportion of the number of infected animals/humans to the respective number examined . For risk factor analysis , initially , bivariate logistic regression was performed to calculate odds ratios ( ORs ) to assess the association between the occurrence of the infection in animals and exposure variables . Confidence intervals ( 95% ) with no continuity correction for the prevalence [24] were computed as Wilson score intervals using www . vassarstats . net/prop1 . html . Multivariate logistic regression analyses to identify factors with effect on the chance of occurrence of tungiasis in animals in general , pigs or dogs were conducted using the”glm” function in the R software . For identification of risk factors determining the occurrence of animal tungiasis irrespective of species , the variables used included sex of household head , ethnic group of household head , education level of household head , household size , homestead size , estimated annual income , human tungiasis , manure disposal distance from compound and method of manure disposal . Others included; number of animal species in households , presence of pigs , dogs , goats , cattle , cats , chicken and other poultry respectively as well as the period of rearing animals . For analysis of risks factors of pig tungiasis in households with pigs , the variables; “presence of tungiasis in humans” , “number of animal species” , “number of pigs” , “distance of pigs from human housing” , “presence of other ectoparasites in pigs” , “number of dogs” , “presence of tungiasis in dogs” , “number of cats” , “number of goats” , “number of cattle” , “number of chicken” , “presence of other poultry” and “sanitation of the pig dwellings ( clean vs . dirty ) ” were initially considered . The analysis of risk factors for presence of dogs with tungiasis in households used only households with dogs and started with the variables “presence of tungiasis in humans” , “number of animal species” , “number of pigs” , “presence of tungiasis in pigs” , “number of dogs” , “presence of other ectoparasites in dogs” , “number of cats” , “number of goats” , “number of cattle” , “number of chicken” and “presence of other poultry” . Some variable such as “presence of tungiasis in cats or goats” , “ectoparasite control in pigs” , pig management system , type of floor of pig residence or “presence of rats” were not included since the numbers of households with these states were either very low or close to 100% . Significance of individual factors was determined using the t test statistic implemented in “glm” . The Akaike information criterion ( AIC ) was used to compare models and the “drop1” function in R was used to progressively identify variables that could be excluded from models . Finally , pseudo-R2 according to McFadden was determined . In the 10 villages together , 236 households were selected using the criterion of having at least one pig , dog or cat . In addition , 26 and 31 households were selected in Masolya and Makoma 1 , respectively , solely on the criterion of having at least one goat . The other goat owning households had been selected due to the presence of pigs , dogs or cats . Out of 158 households with pigs in the 10 villages , three ( two in Busano and one in Busindha ) declined to participate . Hence , 155 pig owning households were sampled . Only one household out of 121 with at least one dog declined to participate . All the 19 households with cats in the 10 study villages were sampled . All households with at least one goat in Makoma 1 were sampled but in Masolya one household out of 48 goat owning households was excluded due to the absence of the household head during three successive visits . Overall , there were seven species of domestic mammals ( pigs , dogs , cats , goats , cattle , sheep and rabbits ) and five avian species ( chicken , ducks , pigeons , turkeys and guinea fowls ) being reared in the area . The total number of sampled households that had the various animal species and rat trapping sites in each of the 10 villages are shown in S1 Table . The total number of animals of the different species varied greatly in the target villages ( S2 Table ) . Pigs ( median = 40 . 5 , range = 10–156 ) and goats ( median = 29 . 5 , range = 25–222 ) were the predominant domestic mammalian species . While chicken ( median = 235 , range = 140–430 ) and ducks ( median = 22 , range = 7–69 ) were the most abundant avian species . The median number of cattle and dogs in villages among sampled households were 12 . 5 ( range = 3–31 ) and 29 . 5 ( range = 12–53 ) respectively . Cats ( median = 2 . 4 , range = 0–4 ) , sheep ( median = 0 , range = 0–7 ) , rabbits ( median = 0 , range = 0–4 ) , turkeys ( median = 0 , range = 0–10 ) , pigeons ( median = 4 , range = 0–45 ) and guinea fowl ( median = 0 , range = 0–6 ) were rare . There was also a considerable variation in the number of animals of each species reared per household . Pig rearing households had a median number of two pigs ( range = 1–20 ) and those with goats had a median of 4 goats ( range = 1–18 ) . Households with dogs had a median of two dogs ( range = 1–10 ) and those with cats had a median number of one cat ( range = 1–3 ) per household . The highest variation occurred among chicken rearing households which had a median of eight chicken ( range = 1–60 ) . Other species were found in very few households . Although an attempt was made to trap rats from all the villages at 34 sites , only 65 rats were trapped in cages from 22 sites across five villages ( S1 and S2 Tables ) . With the exception of one pig rearing household ( which was raising pigs intensively in a concrete floored house ) , the majority ( 154 out of 155; 99 . 4% ) confined pigs on earthen floors during the crop growing season and released them to scavenge after harvest . Dogs , cats and chicken roamed freely with no restriction on compounds . Dogs were not housed at all and cats lived inside the human houses . Chicken and other avian species were mainly housed in earthen kitchens or inside the human house in most households ( 79 . 8% , 162 out of 203 ) or in provisional structures or cages on compounds ( 20 . 2% , 41out of 203 ) . In all households goats were tethered during the day in bushes and kept at night in the kitchen , house or verandas ( 48 . 6% , n = 103 ) ; provisional structures ( 31 . 6% , n = 67 ) or in open spaces on pegs on the compound 19 . 8% ( n = 42 ) . Ectoparasite control was practiced ( but with no defined regular schedule ) in 12 . 9% ( 20 out of 155 ) , 10 . 4% ( 22 out of 212 ) and 5% ( 6 out of 120 ) of pig , goat and dog owning households , respectively . Owners used ectoparasiticides by either washing or spraying the animals . All gravid females extracted from infected animals and humans for identification exhibited a clover-like exoskeleton structure of the anterior extremity of the hypertrophic abdomen and hence were characterized as T . penetrans ( S1A Fig ) . Scanning electron microscopy also confirmed the presence of this structure ( S1B Fig ) Proportions of households with tungiasis in animals and humans in the study area are provided in Table 1 . Animal tungiasis was detected in nine of the ten villages with an overall prevalence of 26 . 3% ( n = 62 , 95% CI 21 . 1–32 . 2% ) out of the 236 households . Nagongera was the only village without any case of animal tungiasis . No animal cases were detected among the 57 additional households from Makoma 1 and Masolya which were selected on the criteria of having at least one goat to achieve a representative sample of goats in these villages . The overall prevalence as well as species-specific prevalence varied widely . The proportions of households with at least one infected animal were also highly variable among villages with a median proportion of 22 . 2% ( range = 0–71 . 4% ) . Busindha village had the highest prevalence of tungiasis among households ( 71 . 4% , 95% CI 45 . 4–88 . 3% ) . Pigs , dogs , goats and a single cat were the only infected domestic mammalian species out of the seven examined ( Table 2 ) . Only two cases of tungiasis were detected in goats ( one in Masolya and one in Busindha village ) . Goat tungiasis was detected in only one goat rearing household out of 97 ( 1% , 95% CI 0 . 2%-5 . 6% ) in Masolya and Makoma 1 combined , where unbiased sampling was undertaken . The only infected cat was found in Matyama village . Rats ( n = 65 ) and all poultry species examined were not infected even in households where other animal species and humans were heavily infected . However , many chickens were infested with the flea Echdinophaga gallinacea . Pig tungiasis occurred in nine of the 10 villages , while in dogs , tungiasis occurred in only five villages . In both species , the prevalence varied considerably ( median = 16 . 2% , range = 0–64 . 1%; median = 2% , range = 0–26 . 9% , respectively ) . Pigs were significantly more affected than other species ( pigs vs . dogs , p<0 . 0001; pigs vs . cats , p = 0 . 02; pigs vs . goats , p<0 . 0001 . There was no significant difference in prevalence between the dogs and cats ( p = 0 . 54 ) , though dogs were significantly more affected than goats , p<0 . 0001 . There was no correlation between prevalence of pig tungiasis and the size of the pig population at both household and village levels ( rho = 0 . 09 , p = 0 . 28 and rho = 0 . 3 , p = 0 . 44 respectively ) . The same trend was evident for dogs ( household level rho = 0 . 08 , p = 0 . 4; village level rho = 0 . 05 , p = 0 . 9 ) . Among pig rearing households , there was no significant difference in the proportion of those with infected pigs between those that practiced ectoparasite control for pigs and those that did not ( 6 out of 20 vs . 48 out of 135 , p = 0 . 42 ) . This was also true for dog owning households ( 2 out of 6 vs . 12 out of 114 , p = 0 . 145 ) . The two cases of goat tungiasis occurred in households with infected pigs and humans . The only infected cat had a single lesion and was detected in a household with neither human nor other animal species tungiasis . The infected goats were three week old kids while the cat was two years old . Families had a median size of eight ( range 1–24 ) members with a median of two households ( range 1–8 ) on the same compound . Most households ( 89% , n = 210 ) had earthen floored houses which occupants occasionally smeared with cow dung to minimize dust accumulation in the houses . Of the 1766 examined humans from the 236 households , 856 ( 48 . 5% ) were females while 910 ( 51 . 5% ) were males . Human tungiasis was detected in all the ten villages ( Tables 1 and 3 ) . In 80 ( 33 . 9% , 95% CI 28 . 2–40 . 2% ) of the 236 households ( which had at least one dog , cat or a pig ) , at least one human was affected ( Table 3 ) . The prevalence of households with human tungiasis also varied greatly ( median 27 . 8% , range 5–71 . 4% ) . In the additional 57 households ( selected on the criterion of at least one goat after covering those selected on the criterion of possessing a dog , cat or pig ) in Masolya and Makoma , 21 ( 36 . 8% ) had at least one human case . Among humans examined for tungiasis in the 236 animal rearing households sampled , 254 ( 14 . 4% , 95% CI 12 . 8–16 . 1% ) were infected but in the 57 additional households , 48 out of 382 humans ( 12 . 6% , 95% CI 9 . 6–16 . 3% ) were infected ( p = 0 . 20 ) . Prevalences of human infections in the villages ( Table 3 ) were significantly variable ( median 7% , range 1 . 3–37 . 3%; p<0 . 0001 ) . The prevalence of tungiasis was significantly higher in males ( n = 154 , 16 . 9% , 95% CI 14 . 6–19 . 5% ) than females ( n = 100 , 11 . 7% , 95% CI 9 . 7–14 . 0%; p = 0 . 001 ) . Children ( 0–15 years ) had a significantly higher prevalence of tungiasis than other humans above 15 years ( 20 . 3% vs . 5 . 5%; p<0 . 0001 ) . The prevalence of human tungiasis was highest in children of 6–15 years ( Fig 2 ) . Overall , the variations in prevalence of tungiasis among age groups were statistically significant ( p<0 . 0001 ) . There was also a significantly higher prevalence in the two youngest age groups compared with the middle age groups and a clear peak in the age group of 6–15 years ( Fig 2 ) . In 40 ( 17% , 95% CI 12 . 7–22 . 3 ) of the sampled households , animal and human tungiasis coexisted . These constituted 50% and 64 . 5% of the households with human and animal tungiasis respectively . Animal tungiasis increased the odds of the occurrence of human tungiasis in households by six times ( OR = 6 . 1 , 95% CI 3 . 3–11 . 4%; p<0 . 001 ) and vice versa . In Busindha , all animal rearing households that had infected animals also had infected humans . In Isakabisolo , the proportions of households with infected animals were similar to that of humans but infections were detected in different households , i . e . there were households where only human or only animal tungiasis was detected . In other villages the proportions differed ( Table 1 ) . Overall the proportions of households with human tungiasis did not differ significantly from those with animal tungiasis in the 10 villages ( p = 0 . 07 ) . A strong correlation existed between the prevalence of households with human tungiasis and those with animal cases within the 10 villages as illustrated in Fig 3A . ( rho = 0 . 85 , p = 0 . 002 ) . At household level , the prevalence of animal tungiasis correlated with human tungiasis prevalence ( rho = 0 . 4 , p<0 . 001 ) as shown in Fig 3B . Also , at household level , the prevalence of tungiasis in the mostly affected animal species strongly correlated with human prevalence ( dogs rho = 0 . 34 , p = 0 . 0002; pigs rho = 0 . 5 , p<0 . 001 ) . Pigs had the highest parasite load followed by goats and dogs: median = 8 lesions ( inter-quartile range ( IQR ) = 3–30; range of 1–246 lesions per pig ) ; goats median = 20 ( 6 and 34 lesions in 2 goats ) ; dogs median = 2 ( inter quartile range = 2–3; range = 1–8 ) . The only affected cat had a single non-viable lesion . Of the 3357 lesions in pigs , 2243 ( 66 . 8% ) were viable ( Fortaleza stage IIa-IIIb ) and 1114 ( 33 . 3% ) were non-viable ( Fortaleza stage IV ) . The number of lesions per pig was highly variable ( Fig 4 ) . Among the infected pigs , those which had the highest infection intensity ( >30 lesions , n = 30 , 24 . 8% ) presented 79% of the total number of embedded sand fleas . The 20 infected dogs had a total of 53 lesions of which 32 ( 60 . 4% ) were viable while 21 ( 39 . 6% ) were non-viable . Occasionally , it was observed that dogs bite at flea lesions and exteriorized the fleas with their teeth . Out of the 20 dogs only 2 ( 10% ) had ≥5 lesions while the other 18 had light infections ( 1–4 lesions per dog ) . Of the total 40 lesions found on the two goat kids , 27 ( 67 . 5% ) were viable while the other 13 ( 32 . 5% ) were non-viable . In pigs , no correlation was observed between age and the total number of lesions ( rho = 0 . 014 , p = 0 . 88 ) but in dogs the number of lesions per dog significantly decreased with age as shown in Fig 5 . ( rho = -0 . 47 , p = 0 . 039 ) . The number of lesions did not differ between sexes: female median 10 ( IQR 3–39 ) vs . male median 6 ( IQR 3–30 ) in pigs ( p = 0 . 37 ) ; female median 2 ( IQR 2–3 ) vs . male median 2 ( IQR 2–3 ) in dogs ( p = 0 . 88 ) . In the 236 households , sand flea lesions were counted in 111 infected children aged three to eight years , the age group known to have the highest intensity of infection . These included 62 boys and 49 girls . A total of 340 lesions were documented from one randomly selected foot of these children . The median number of lesions per infected child was 2 ( range 1–18 ) . The number of lesions per foot never differed significantly between boys ( median 2 , range 1–18 ) and girls ( median 2 , range 1–8; p = 0 . 42 ) . Pigs had a significantly higher number of lesions than other species combined ( median 8 , range 1–246 vs . median 2 , range 1–34; p = 0 . 0002 ) . Accordingly , the number of lesions was also significantly higher for pigs than dogs ( p < 0 . 0001 ) . The median number of lesions in infected animal species strongly correlated with the median number of lesions in children three to eight years of age at household level as illustrated in Fig 6 ( rho = 0 . 47 , p<0 . 0001 ) . The prevalence of human tungiasis at household and village levels correlated strongly with the number of lesions in pigs at the respective levels ( rho = 0 . 5 , p<0 . 0001; rho = 0 . 8 , p = 0 . 002 ) . At household level , an increase in human tungiasis intensities corresponded with an increase in the odds of occurrence of animal infections ( OR = 1 . 8 CI 1 . 4–2 . 2 , p<0 . 0001 ) and vice versa ( OR = 1 . 3 CI 1 . 1–1 . 4 , p < 0 . 0001 ) . Of the infected 121 pigs , only 18 ( 15% ) had ever received ectoparasite treatment and none of these had a well-defined interval of treatment . The period between the last time of pig treatment and the examination date ranged from one week to 10 weeks . Nine pigs had received ectoparasitic treatment between one and two weeks before the examination date while the rest ( 9 pigs ) had received treatment between five and 10 weeks prior to the examination date . Ectoparasiticides which had been used on infected pigs included pyrethroids ( 6 ) , amitraz ( 6 ) and a traditional concoction of molasses and a local gin ( waragi ) which was used on one pig . Three pig owners could not recall the type of ectoparasiticide they had used to treat five of the infected pigs . Although , the total number of sand flea lesions per infected pig was lower in pigs treated with ectoparasiticides than the untreated ( treated median 6 . 5 , IQR = 3–13 vs . untreated median 8 , IQR = 3–39 ) , the difference was not significant ( p = 0 . 34 ) . For treated pigs , there was no correlation between the number of embedded sand fleas and the time span since when the pigs received the last ectoparasiticide treatment ( rho = -0 . 16 , p = 0 . 53 ) . Pig dwellings were located at a median distance of 11 meters ( range 0–50 m ) from the edge of human compounds . The distance of pig dwellings ( places of pig confinement ) from human compounds had a weak positive correlation with the total number of lesions per pig ( rho = 0 . 18 , p = 0 . 043 ) . Ectoparasite control had been attempted for only two of the infected dogs ( 10% ) with no definite control interval . While one dog had received the ectoparasiticidal treatment one week before the examination date , the other had received the same treatment four weeks ago and in all cases α-cypermethrin 10% was used . Incidentally , the more recently treated dog had more lesions than the dog treated three weeks before ( three lesions vs . one lesion ) . Neither the two infected goat kids nor the infected cat had ever received any ectoparasiticidal treatment . A bivariate analysis of risk factors was undertaken ( S3 , S4 and S5 Tables ) . Factors strongly associated with occurrence of tungiasis in all animals irrespective of species; pigs and dogs within households are summarized in Table 4 . Occurrence of infected animals in households was strongly associated with human infections ( OR = 6 . 0 , 95% CI 2 . 4–9 . 1; p < 0 . 0001 ) and presence of pigs in a household ( OR = 5 . 8 , 95% CI 2 . 5–13 . 5; p < 0 . 0001 ) among other factors . For households with infected humans , the risk of animal tungiasis increased with the number of infected humans . One to four infected humans in households compared to none increased the risk by five times ( OR = 5 . 0 , 95% CI 2 . 6–9 . 5; p < 0 . 0001 ) but presence of 5–12 infected individuals raised the odds to 12 times ( OR = 12 . 2 , 95% CI 4 . 1–35 . 8; p < 0 . 0001 ) . Pig tungiasis occurred in strong association with dog tungiasis ( OR = 7 . 4 , 95% CI 1 . 5–36 . 9; p = 0 . 02 ) and human tungiasis ( OR = 7 . 0 , 95% CI 3 . 4–14 . 7; p<0 . 0001 ) while presence of infections in dogs was also strongly influenced by human tungiasis ( OR = 12 . 2 , 95% CI 2 . 6–57 . 4; p = 0 . 002 ) and pig infections ( OR = 5 . 6 , 95% CI 1 . 7–18 . 2; p = 0 . 004 ) . In multivariate analysis , presence of animal tungiasis in households was strongly influenced by presence of human tungiasis ( OR = 6 . 5 , p < 0 . 0001 ) and presence of pigs ( OR = 5 . 9 , p = 0 . 0002 ) as illustrated in Fig 7A . In addition , the number of animal species reared in the household ( OR = 1 . 6 , p = 0 . 02 ) and the size of the homestead ( OR = 1 . 4 , p = 0 . 02 ) significantly increased the odds detecting animal tungiasis among households . Slightly but non-significant protective effect was observed in association with the presence of chicken and goats in the households . However , the overall model had a poor to moderate fit ( McFadden pseudo R2 = 0 . 25 ) . Due to the overall low fit of the animal tungiasis model , separate models were estimated for pig and dog tungiasis . The odds of households to have pigs infected with T . penetrans were significantly increased if there was also human tungiasis as illustrated in Fig 7B ( OR = 2 . 1 , p = 0 . 001 ) . The final model showed an excellent fit ( McFadden pseudo R2 = 0 . 82 ) . It also included the variables; “presence of other poultry” , “dog tungiasis” and “pig herd size” which all increased the odds of pig tungiasis although their effects were all not significant . In addition , housing of pigs had a very low OR of 1 . 6×10−9 suggesting that it has strong protective effect against pig tungiasis . However , this effect was not significant due to the very low number of households with housing for pigs hence a very wide 95% CI . The same analysis for the presence of dog tungiasis in households ( Fig 7C ) suffered from the low number of households with dog tungiasis identified in the study ( n = 14 ) . Nevertheless , the overall fit of the model was very good ( McFadden pseudo R2 = 0 . 71 ) . The variable with the strongest influence on the odds of households to have dog tungiasis ( human tungiasis , OR = 4 . 0 × 109 had a very wide 95% CI . The number of goats significantly increased the odds ( OR = 2 . 0 , p = 0 . 04 ) while pig tungiasis had a non-significant influence . Presence of poultry other than chicken appeared to be slightly protective but this effect was also not significant . This study demonstrated a strong correlation between animal and human tungiasis in animal rearing households , which both occurred with high prevalence in rural endemic villages of Uganda . Pigs were identified as the major hosts of T . penetrans . An effective tungiasis control strategy; therefore , calls for an integrated One Health approach . In addition to treatment of humans and environmental sanitation , ectoparasite control should be encouraged among animal owners to eliminate animal infections . However , there is still need to evaluate the therapeutic and prophylactic effects of commercial pesticides against T . penetrans
Tungiasis is a neglected skin disease , frequent in resource-poor communities in the tropics . It is caused by sand fleas ( also called jigger fleas ) which burrow in the skin of humans and animals . Tungiasis can cause physical disabilities and the associated wounds facilitate entry of pathogens including those causing tetanus . In Brazil , presence of tungiasis in animals increased the risk and severity of the human disease . Until now , no systematic studies on animal tungiasis in Africa have been conducted . Therefore , an epidemiological study was performed in Busoga sub-region , where tungiasis in humans is very common . Tungiasis was detected in pigs , dogs , goats and a cat , respectively , in their order of significance . Animal tungiasis was strongly associated with human tungiasis and the presence of the disease in animals increased the risk of human infection by a factor of six . Our findings confirmed , for the first time , a strong correlation between the presence of tungiasis in animal reservoirs and the human population in Africa . Therefore , control of tungiasis in animals should be integrated in all interventions geared at controlling tungiasis in endemic communities .
[ "Abstract", "Introduction", "Materials", "and", "Methods", "Results", "Discussion" ]
[]
2015
Animal Reservoirs of Zoonotic Tungiasis in Endemic Rural Villages of Uganda
BK virus ( BKV ) associated nephropathy affects 1–10% of kidney transplant recipients , leading to graft failure in about 50% of cases . Immune responses against different BKV antigens have been shown to have a prognostic value for disease development . Data currently suggest that the structural antigens and regulatory antigens of BKV might each trigger a different mode of action of the immune response . To study the influence of different modes of action of the cellular immune response on BKV clearance dynamics , we have analysed the kinetics of BKV plasma load and anti-BKV T cell response ( Elispot ) in six patients with BKV associated nephropathy using ODE modelling . The results show that only a small number of hypotheses on the mode of action are compatible with the empirical data . The hypothesis with the highest empirical support is that structural antigens trigger blocking of virus production from infected cells , whereas regulatory antigens trigger an acceleration of death of infected cells . These differential modes of action could be important for our understanding of BKV resolution , as according to the hypothesis , only regulatory antigens would trigger a fast and continuous clearance of the viral load . Other hypotheses showed a lower degree of empirical support , but could potentially explain the clearing mechanisms of individual patients . Our results highlight the heterogeneity of the dynamics , including the delay between immune response against structural versus regulatory antigens , and its relevance for BKV clearance . Our modelling approach is the first that studies the process of BKV clearance by bringing together viral and immune kinetics and can provide a framework for personalised hypotheses generation on the interrelations between cellular immunity and viral dynamics . In the last years , BK virus-associated nephropathy ( BKVN ) has become the most challenging infectious cause of renal graft dysfunction in kidney transplant , leading to graft failure in over 50% of cases [1 , 2] . The rise in BKVN incidence has been attributed , at least to some degree , to the increased potency of immunosuppressive drugs [3 , 4] . Given the absence of specific antiviral treatments , BKVN is handled by changing the immunosuppressive regimes of the patients , enabling the development of a specific antiviral immune response [3–5] . Diagnosis of BKVN is performed through renal biopsy [3 , 6–8] as progression of the illness occurs without clinical signs , except for an increase in serum creatinine concentrations [1] . In the absence of medical intervention , BKVN can cause extensive fibrosis and tubular atrophy in the allograft , leading to transplant loss [1 , 3 , 7] . This progression is accompanied by a high BK virus ( BKV ) plasma load . Therefore , screening of plasma BKV viral load is currently recommended for the monitoring of BKVN [8 , 9] . BKV is a non-enveloped virus with an icosahedral capsid and a small circular double-stranded DNA genome ( ~5kb ) , which encodes for the early regulatory proteins: small tumor antigen ( st ) and large tumor antigen ( LT ) ( here collectively referred to as sLT antigens ) , the late structural viral proteins 1–3 ( VP1 , VP2 and VP3 ) ( here referred to as VP antigens ) and the agnoprotein [3 , 10] . Latent BKV infection is very common among the healthy population , with a prevalence above 80% [3 , 11–13] . In spite of a high frequency of self-limited BKV reactivation in kidney transplant recipients [12 , 14 , 15] , only 1–10% [2] of transplant recipients do actually develop BKVN . To determine the factors leading to BKVN , much emphasis has been placed on the immune reaction against BKV antigens . sLT and VP antigens ( but not the agnoprotein ) have been demonstrated to elicit a T cell response , as we previously showed in our studies [16–18] . Our data suggest that cellular immune reaction has a prognostic value for BKVN evolution [16] . However , T cell response can act through a number of mechanisms—killing of infected cells , blocking virus production or infection , among others—which should have different impacts on viremia control . Although our data [16] suggest that VP and sLT antigens trigger substantially different immune responses , the experimental data alone do not allow to determine the relation between antigens , immune mechanisms and clearance . Sophisticated instruments , such as mathematical models tailored for data analysis of this particular question , are required to formalise and analyse whether different antigens trigger different immune mechanisms and what these modes of action are . The most widely used method for modelling viral dynamics is ordinary differential equations ( ODE ) . It has , for instance , helped elucidate the dynamics of HIV-1 , hepatitis and opportunistic viruses in transplant recipients [19] . It has also been used for the study of BKV , simulating the dynamics of viral production , predicting cytopathic effects of the virus and explaining the interactions between viral reactivation in tubular epithelial cells , urothelial cells , viremia and viruria [20 , 21] . However , to our knowledge , no model exists that incorporates the activation of the immune response with viral clearance dynamics . Therefore , in this study we have retrospectively analysed the data of BKV plasma load kinetics and T cell responses against BKV antigens in six patients with biopsy-proven BKVN [16] . The objective of the analysis was to determine the dominant modes of action of the observed immune responses . For this , a tailor-made ODE model was generated , allowing for the formalisation of different hypotheses on the dominant modes of action of the immune response against BKVN . To accomplish our goal , we pursued the following strategy: Firstly , we obtained a continuous curve that fits the time course of the T cell response data ( Elispot ) for each patient and antigen . Secondly , we designed an ODE model for the viral load clearance dynamics dependent on the T cell response curves . This model uses the former curves as input and simulates the dynamics of three variables: number of healthy cells , number of infected cells and BKV viral load . It incorporates three mechanisms of the immune system in viral clearance , allowing for the simulation of nine different hypotheses about dominant modes of action . Lastly , we evaluated all hypotheses for their capacity to reproduce the viral clearance data . Our results allowed for the discarding of most hypotheses and suggested that the anti-VP response induces the blocking of virus production while anti-sLT responses induces killing of infected cells . This difference in modes of action could be central for disease outcome , since only the sLT responses would trigger a fast and continuous BKV clearance under this hypothesis . These results could therefore have implications in the development of new immunotherapies against BKVN . The study involved six renal transplant patients analysed in our previous study [16] . These six patients ( called Patient A to F in the following ) received renal transplants between 12/2004 and 05/2009 and developed severe BKV reactivation in follow-up . The patients were monitored for BKV viral load by quantitative polymerase chain reaction ( qPCR ) . Cellular adaptive immune response against the BKV antigens ( VP1 , VP2 , VP3 , st and LT ) was monitored by Interferon gamma ( IFN-γ ) Enzyme-Linked ImmunoSpot ( Elispot ) , measured in spot forming units ( SFU ) per 106 peripheral blood mononuclear cells ( PBMC ) . Elispot read-outs are known to accurately quantify antigen-specific T cell responses for BKV [22] . All patients had biopsy-proven BKVN and were initially treated with a tacrolimus-based immunosuppressive regimen . Tacrolimus is a calcineurin inhibitor . It inhibits T cell activation but does not have cell-depleting effects [23] . It is associated with significantly higher incidence of BKVN compared to cyclosporine A , a less potent calcineurin inhibitor [24] . Upon BKV reactivation and diagnosis of BKVN , tacrolimus was replaced by cyclosporine A . This immunosuppressant switch is a commonly used protocol against BKVN , as cyclosporine A is known to allow the onset of a T cell response against BKV [16 , 25] . Patients were monitored for BKV viral load during the complete evolution of the illness . The immune response was measured at the latest from the point of immunosuppressant switch until BKV clearance ( Fig 1 ) . We observed a considerable diversity in the times needed to reach viremia clearance for each patient , ranging from 117 days after viremia onset for Patient F to 1744 days ( ~4 years ) for Patient A . However , some common patterns could be observed . The immune response came generally in two waves , the first with an anti-VP immune response ( red , pink and yellow lines in Fig 1 ) and the second , targeted against sLT antigens ( light and dark green ) . Importantly , the immune response against VP was triggered for all but patient C within a relatively short span of time ( < 70 days ) after immunosuppressant switch . On the other hand , immune response against the sLT antigens was observed in only five patients . Again patient C did not show any immune response against either sLT antigen . Based on the delay between the VP and the sLT immune responses , patients could be grouped in two categories: Patients D , E and F showed a short delay of approximately 30 days , while patients A and B showed a much longer delay of over 180 days . The triggering of cellular immune responses against the BKV antigens occurred after the immunosuppressant switch . This immune response led to a progressive decrease of viral load until viral clearance was achieved . This decreasing phase took place for hundreds of days on most cases . In the five patients showing an anti-sLT immune response , the emergence of this response was tied to a substantially faster viral load decrease . This strongly suggests that the kind of immune response triggered by the sLT antigens is inherently different from the one triggered by VP antigens . With the goal of using the immune response data as an input for the viral load clearance dynamics model , we developed a simple curve based on one or more logistic functions to describe the experimentally observed T cell response . The use of logistic functions to describe T cell dynamics of antigen specific populations was chosen due to their simplicity and capacity to describe saturation-limited growth processes [26–28] . The model for one logistic function is ddtantia ( t ) ={ 0 , for0≤t≤tara·antia ( t ) · ( 1−antia ( t ) maxantia· ( 1−deca·t ) ) , fort>ta ( 1 ) antia ( t ) is the T cell response for an antigen , where a represents the antigen that elicits the response . For the definition of parameters see Table 1 . We chose the activation time ta as a free parameter because the T cell response may start at different points in time for every antigen . As it is possible that an immune response presents multiple boosting episodes , we considered the possibility that at a second time point ta2 the parameters of the curve are replaced by a second set of parameters . We fitted this function to the BKV specific immune response against each of the five antigens ( VP1 , VP2 , VP3 , st and LT ) . t = 0 was defined at a day for which there are both Elispot and viral load data and the viral load is maximum compared to all later measurements . This was defined as follows: Patient A , day 1363 after transplantation; B , day 412; C , day 538; D , day 175; E , day 235; and F , day 530 . Simulations were performed until the time point viral load becomes undetectable or there are no further Elispot measurements . This time point was chosen because we aim to model only the clearance process . The objective function used for the fitting takes the form of vertical least-squares such that f=∑t=1N∑a=1A ( log10 ( y- ( t , a ) ) -log10 ( y ( t , a , p ) ) ) 2N ( 2 ) where y- ( t , a ) is the experimental value of the Elispot read-out at time t for antigen a . y ( t , a , p ) is the calculated Elispot read-out for a given parameter set p . N is the total number of measurements and A is the number of screened antigens . The results of the parameter estimation are shown in S1 Table and Fig 2 . As depicted in Fig 2 , Eq 1 was sufficient to reproduce the immune response time courses of all six patients . For the immune response to the structural antigens of Patient A , a time point ta2 with a second parameter set was employed to achieve a minimum value for the objective function of ( 4 . 16·10−2 ) , instead of the minimum achieved for only one parameter set ( 2 . 24·10−1 ) ( see S1 Fig ) . In order to study the differences in the mechanisms of the immune responses against structural ( VP1 , VP2 , VP3 ) and regulatory ( st , LT ) antigens , the results of the fitting were summarised in a VP function and a sLT function . These functions are employed in the model of BKV viral load clearance as an input , to model the influence of each immune response against BKV . The maximum value is taken under the assumption that the effects of the antigens are not additive , but that there is some degree of saturation . The functions are subtracted by one unit because 1 is the baseline value of the logistic curve antia ( t ) . The evolution of BKV viral load clearance was described using a modified version of a basic model of viral dynamics [29] , such that ddtC ( t ) =g·C ( t ) · ( 1-C ( t ) +I ( t ) maxc ) -d·C ( t ) -β·C ( t ) ·V ( t ) · ( 1-ν ( t ) ) ddtI ( t ) =β·C ( t ) ·V ( t ) · ( 1-ν ( t ) ) -d·k·I ( t ) · ( 1+m·μ ( t ) ) ddtV ( t ) =p·I ( t ) · ( 1-ϵ ( t ) ) -c·V ( t ) ( 4 ) This model contains three variables: number of healthy cells ( C ) , number of infected cells ( I ) and BKV viral load in copies · mL-1 ( V ) . Healthy cells proliferate at a rate proportional to g; this rate is limited by maxc , which represents total number of cells ( including both healthy and infected ) . Healthy cells die at a rate d and are infected in presence of virus at a rate β . Infected cells die at a rate d · k , where k is virus-associated cytopathicity . Viruses are produced by the infected cells at a rate p and get cleared by the excretory system at a rate c . For a schematic representation of the model , see Fig 3 . For a further definition of the parameters , see Table 2 . The three model variables ( C , I and V ) depend on the T cell response curves as defined in previous section . To study the mode of action of T cell responses , we consider that T cells can act via three mechanisms: ( 1 ) virus production blockage ( described by function ε ( t ) ) , ( 2 ) killing of the infected cells ( described by function μ ( t ) ) and ( 3 ) infection blockage ( described by function υ ( t ) ) . ε ( t ) , μ ( t ) and υ ( t ) take the form of the sum of Hill functions , a standard form for describing a saturating function , with a maximum value of 1 , such that ϵ ( t ) =maxϵ·VP ( t ) hillϵθϵhillϵ+VP ( t ) hillϵ+maxΕ·sLT ( t ) hillΕθΕhillΕ+sLT ( t ) hillΕ μ ( t ) =maxμ·VP ( t ) hillμθμhillμ+VP ( t ) hillμ+maxΜ·sLT ( t ) hillΜθΜhillΜ+sLT ( t ) hillΜ ν ( t ) =maxν·VP ( t ) hillνθνhillν+VP ( t ) hillν+maxΝ·sLT ( t ) hillΝθΝhillΝ+sLT ( t ) hillΝ maxϵ+maxΕ≤1 maxμ+maxΜ≤1 maxν+maxΝ≤1 ( 5 ) where ε ( t ) , μ ( t ) and υ ( t ) depend on the VP ( t ) and the sLT ( t ) immune responses , as defined in Eq 3 . The objective of our work is to find the dominant modes of action responsible for viral load clearance . Therefore , we assume for the model that each one of the two immune responses ( VP ( t ) and sLT ( t ) ) acts through only one mode of action , either ε ( t ) , μ ( t ) or υ ( t ) ( Eq 5 ) . As these are three modes of action and two antigen-specific responses , nine different hypotheses on the relationship between dominant modes of action and immune response are possible . These nine hypotheses are referenced here following this convention: For example , the hypothesis that anti-VP triggers a μ ( t ) response ( accelerated killing ) and anti-sLT triggers a υ ( t ) response ( infection blockage ) is named VPμ-sLTυ hypothesis . For the definition and description of all nine hypotheses , see S2 Table . To evaluate the feasibility of the hypotheses for dominant modes of action of the immune system , the model was fitted against the BKV clearance data for all nine hypotheses . The parameters c , g , d , β and p were estimated based on previous publications . Parameter k was estimated for each hypothesis based on one particular patient , while the remainder of the parameters were estimated individually for each patient and hypothesis . The rate constant c for virus clearance was fixed to the value calculated by Funk et al . [30] . In the case of g , which is the maximum replication capacity for C ( t ) + I ( t ) << maxc , cell culture results show a maximum duplication rate of approximately one day for renal foetal kidney cells [31] . Therefore , for the sake of simplicity we assigned a value of 1 days-1 for g . For the cell death rate of healthy cells d , a value of 0 . 01 days-1 was used on a model of similar structure for Hepatitis C virus [32] and it was deemed to be reasonable estimation here . The value of the virus production rate p was calculated in the same model to be 100 copies · mL-1 · cells-1 · days-1 [32] . Given that BKV is a less aggressive infection , we deemed it reasonable to assume a value of 15 copies · mL-1· cells-1 · days-1 . This has the property that , for I ( t ) = V ( t ) and no immune reaction , the viral load is in a steady state . Likewise , as the cell infection rate β for the Hepatitis C virus was estimated to be 3·10−7 copies-1 · mL · days-1 [32] , a value of 3·10−8 copies-1 · mL · days-1 for BKV was assumed . Patient C had the slowest progression of viral clearance , which suggests that immune cytotoxic effects were relatively low . Therefore , we estimated the viral cythopathic factor ( k ) for all patients using data obtained from Patient C . The model as defined by Eqs 3–5 was fitted for all nine hypotheses ( S2 Table ) with the objective function f=∑t=1N ( log10 ( y- ( t ) ) -log10 ( y ( t , p ) ) ) 2N ( 6 ) which takes the form of vertical least-squares . N is the total number of measurements , y- ( t ) is the viral load at the time t , y ( t , p ) is the simulated viral load for a parameter set p and time t . The initial conditions for all cases were For t = 0: C ( 0 ) =maxc-cp·V ( 0 ) I ( 0 ) =cp·V ( 0 ) V ( 0 ) =V ( 0 ) ( 7 ) so that , at time t = 0 and no immune response , viral load is in steady state . V ( 0 ) is defined as the observed viral load at t = 0 . t = 0 was defined as above . The results obtained for the fittings , as well as the model selection criterion ( see Materials and methods ) for each hypothesis and patient , are shown in Table 3 . The results in Table 3 were interpreted to discard hypotheses based on the ΔBIC score and the value of the objective function . Accordingly , there is good empirical support to generally discard hypotheses VPν-sLTν and VPν-sLTε as probable mechanisms for viral clearance . Hypotheses VPμ-sLTν , VPε-sLTν , VPε-sLTε , VPμ-sLTμ and VPν-sLTμ can only be considered as possible mechanisms for individual patients but not for the entire patient cohort . Hypothesis VPμ-sLTε cannot be discarded but does not show the highest degree of empirical support . The hypothesis VPε-sLTμ has the lowest median ΔBIC and thus the highest empirical support . For five out of six patients , this hypothesis was within the range of substantial empirical support ( ΔBIC <2 ) [33] , while no other hypothesis had comparable support for more than two patients . This hypothesis associates an anti-VP response with virus production blockage and an anti-sLT response with accelerated killing of infected cells . The hypothesis VPε-sLTμ is shown compared to the other alternative hypotheses in S2 Fig . Results of the parameter estimation , confidence intervals and the objective function for the VPε-sLTμ hypothesis are shown in Table 4 . The fitted model for each patient is shown on Fig 4 . In spite of the good results of the fitting , the estimated values of the parameters should be taken with caution . The results show heterogeneity between patients , especially maxc , hillε and θε , with a range of around 3 orders of magnitude . This could be partly caused by parameter uncertainty , as supported by the 95% confidence intervals , which for some parameters range over 2 orders of magnitude . However , the variation of parameters between patients is larger than the confidence intervals for each patient , confirming that the high variation is not solely a product of parameter uncertainty . This is not surprising , as there is a very high degree of variation in the clearing time courses of the patients . Note that the fitted parameters summarise complex biological processes , as opposed to reflecting fundamental mechanisms , rendering it difficult to interpret parameter variations . Nevertheless , fundamental biological variation between patients is conceivable . A clear case is patient F . This patient had a simultaneous activation of the anti-VP and anti-sLT immune response , and the extremely low estimate for hillε and very broad confidence intervals hillε and θε , suggest that the anti-sLT immune response through the μ mode of action could have a saturating effect over the anti-VP immune response . In fact , assuming only an anti-sLT response for patient F led to an increase of f of less than 5% in comparison to the original VPε-sLTμ , with substantially lower BIC values ( see S3 Table ) . This result supports the possibility of a saturating anti-sLT response for this patient . To analyse the impact of the chosen values for the fixed parameters g , d , p , β and k on the behaviour of the model , a sensitivity analysis was performed . The goal was to analyse whether the same quality of fitting and qualitative behaviour of the model can be achieved for different values of these parameters . The analysis was performed following the principle of one-factor-at-a-time . The value of a single parameter was modified over a span ranging from a factor 0 . 1 of the original value up to 10; for each new value of the parameter a fitting was performed to minimise the value of the objective function ( Eq 6 ) . The detailed results of the sensitivity analysis are shown in S4 Table , the results for the extreme values ( factors 0 . 1 . and 10 ) are plotted in S3 Fig . Briefly , the results show that the model VPε-sLTμ can robustly simulate the viral clearance dynamics of the six patients and is not sensitive to variations of the fixed parameters: For the extreme values ( factors 0 . 1 and 10 ) , fittings with fSUM < 0 . 4 were achieved in all cases . This is especially relevant when comparing the results with those for the mode of action hypotheses ( Table 3 ) , where the best alternative hypothesis had a fSUM = 0 . 40800 . Taken together , the results of the analysis reinforce the relevance of the hypothesis VPε-sLTμ , demonstrating that it is able to fit the viral dynamics better than the other hypotheses , even when modifying the fixed parameters across two orders of magnitude . In this work we have created the first model that provides evidence of the dominant modes of action involved in the clearance of BKV . It is the first model that covers the process of BKV clearance harmonising the viral and immune dynamics and formalising different modes of action of the immune system and their influence on the viral dynamics . It incorporates the influence of the adaptive immune system on the clearance of BKV reactivation in a patient-to-patient basis by considering multiple antigens and immune reactions against the same viral infection and highlighting certain patterns of the process of immunological re-arming against BKV after immunosuppressant switch . Our results show that immune modes of action can be captured by acquisition of time series of blood markers not directly related to mechanistic observations . Taken together , our work can be used as a tool for personalised hypothesis generation and evaluation of the modes of action through which the immune system successfully fights against BKVN . Our model suggests that for VP-specific cellular immune response , the dominant mode of action is reducing the rate of virus production , while the mode of action triggered by sLT-antigen specific T cells is an increased death rate of infected cells . This remarkable feature would be central for BKV clearance: the VP-triggered immune response would cause an initial drop in the viral load , leading to a plateau , where reduction of the viral load is slower than 0 . 5 log10 ( virus·mL-1 ) every 100 days . Only the acceleration of death of infected cells , triggered by the sLT antigens , would lead to a fast and continuous clearance of the viral load . It further suggests that in cases of simultaneous anti-VP and anti-sLT response , the latter response would play the central role in viral clearing . This hypothesis , VPε-sLTμ , achieved substantial empirical support for five out of six patients , while none of the alternative hypotheses on dominant modes of action had substantial empirical support for more than two patients . Even though one alternative hypothesis could be used to fit the viral dynamics of the patients satisfactorily , the VPε-sLTμ hypothesis achieved the lowest total value for the objective function . The suggested VP-triggered blockage of virus production can be linked mechanistically to the action of some cytokines , such as type I-interferons; while sLT-triggered accelerated killing can be associated with cytotoxic cells . This qualitatively different role of both antigen groups is in agreement with biological evidence provided by a previous flow cytometry-based study on VP1- and LT-specific CD4+ and CD8+ T-cells in patients with BKV reactivation [34] . In this work , VP1 elicited a significantly higher response in CD4+ T-cells than in CD8+ T-cells . In the case of the LT antigen , even though there was no significant difference between the magnitude of the CD4+ and the CD8+ T-cell responses , CD8+ cells were significantly more likely to respond against LT than VP1 . The agreement between the hypothesis with the highest empirical support and the cited study highlights , in our opinion , the capabilities of using our model as an instrument for hypothesis generation on the physiological background of BKV clearance . Interestingly , our model highlights a feature of heterogeneity among patients , the delay between anti-VP and anti-sLT immune response , as central for BKV dynamics , linking it to the previously presented division of patients into two groups—with a first group ( upper row in Fig 4 ) clearing the infection after over 300 days and a second group ( lower row ) clearing the infection in around 100 days after immunosuppressant switch—in terms of an increased clearance speed associated with anti-sLT immune response . Our model highlights the close relationship between viral clearance and this delay , underscoring that anti-sLT specific T cells are needed for clearance . A delay between VP and sLT responses has been observed in two previous studies [16 , 34] . However , in spite of having been observed repeatedly , there is to our knowledge at present no discussion in the literature on this striking factor . Possible causes could be related to the different ways of VP and sLT antigen presentation or to the effects of immunosuppression . Based on the results of our model , we would welcome more profound experimental and theoretical research on the reasons underlying the delay . Moreover , our results suggest that heterogeneity is not confined to the delay between immune responses but is a central feature of the BKV clearing dynamics: For certain individual patients , hypotheses other than VPε-sLTμ might be specifically suitable to explain their viral clearance dynamics . There is also a high degree of variation in the estimated values of the parameters between individuals for each hypothesis . A part of this variation may stem from physiological differences . For example , in the case of patient F , for whom particularly extreme values for some parameters were found , this can be linked to this patient being the only one with simultaneous activation of anti-VP and anti-sLT immune responses: Analyses suggested that the latter response could have a saturating effect , rendering the former irrelevant for the viral dynamics . A relevant aspect of the model is that the dynamics of the immune response and their dependence on viral load were not explicitly modelled . The influence of the immune response on viral load is taken into account but the hypothetical contribution of BKV viral load to the building of an immune reaction is not addressed . This approach was chosen due to the high complexity and heterogeneity of the dynamics of immune reaction after immunosuppressant switch—especially the VP-sLT delay . Given that the mechanisms underlying this delay are currently unknown , we consider it to be highly unlikely that using currently available knowledge the immune response can be predicted from viral load . The findings of our work on immune modes of action are especially relevant for future immunotherapeutic approaches against BKVN , since they suggest that the immune response against regulatory sLT antigens is central for BKV clearance . The use of T cells specific for BKV regulatory antigens is an interesting clinical approach , which has recently been shown to be technically possible [35] . In this study , the authors established a protocol for the ex-vivo generation of T cells specific for the antigens VP1 and LT , offering evidence of the specificity and safety of these cells [35] . Our BKV clearance modelling approach provides a framework for the hypothesis generation on the interrelations between cellular immunity and viral load at a personalised basis . Further research with the model could help us to improve therapeutic approaches in patients with BKVN , with the final aim of preventing kidney graft failure . The results of our model strongly suggest a general association between different target antigens and distinct mechanisms of the cellular immune system , linking structural VP antigens with the blockage of viral production and regulatory sLT antigens with cytotoxic effects . It further highlights the essential role of anti-sLT antigen response in clearance . These results should serve as a stimulus for further research on the differences between anti-VP and anti-sLT responses , particularly on their mechanisms , exploring possible physiological differences between patients in this respect . A suggested method could involve complementing the Elispot analysis with flow cytometry analysis of different cell populations reacting to each antigen ( e . g . CD4+ , CD8+ , T helper 17 , T regulatory ) at all time points of the clearance process , with a special emphasis on the differences between the early- and late-stage responses . The knowledge gained through these experiments , as well as further implementations of our model , could open the door to the use of immunotherapy in the treatment , and perhaps prevention , of BKVN . Modelling approaches built upon our work could then be used in a personalised basis to tailor the therapy according to the characteristics of their viral and immune dynamics . This study was approved by our local ethical review committee in compliance with the declaration of Helsinki . Informed consent was obtained from all patients ( Ethic Committee Charité University Medicine , Berlin , Germany , 126/2001 , 07/30/2001 ) . Patients were monitored for serum BKV viral load from 4/2006 to 9/2012 and for BKV specific immune response against VP and sLT from 01/2008 to 07/2010 as described in our previous study [16] . Screening for viral load was performed monthly over the first six months after kidney transplantation , then every three months , and again monthly during active BKV reactivation , while screening for specific immune response with Elispot was performed monthly since approximately the change of immunosuppressive therapy , until BKV clearance ( <3000 copies·mL-1 ) . A total of 167 viral load samples and 98 Elispot samples were collected . BKVN was confirmed by histological examination of the graft biopsy . BKV viral load was measured by qPCR as described previously [15] . Briefly , BKV viral load was measured with TaqMan Real Time PCR . DNA was isolated from serum using a QIAamp DNA Mini Kit ( Qiagen Corp . , Hilden , Germany ) according to the instructions of the manufacturer . PCR was performed with the TaqMan platform ( ABI ) . PCR amplifications were set up in a reaction volume of 25 u/μL using primer and probe at final concentrations of 900 nM and 5 μM , respectively , amplifying the VP1 region of BKV . A plasmid standard containing the VP1 coding region of respective virus was used to determine the copy number per millilitre . Thermal cycling was begun with an initial denaturation step at 95°C for 10 min that was followed by 40 cycles at 95°C for 15 s and 60°C for 1 min . BKV-specific T cell immune response was determined by IFN-γ Elispot upon stimulation of PBMC with 5 different BKV proteins ( VP1 , VP2 , VP3 , st and LT ) as described in our previous study [16] . Briefly , PBMC were isolated from 10–20 mL of heparinised blood using the standard Ficoll Hypaque density gradient centrifugation technique . For the Elispot assay , 96-well multiscreen filter plates ( MAIPS 4510 , Millipore , Billerica , MA , USA ) were coated with 100 μL of primary IFN-γ monoclonal antibody ( mAb ) at a concentration of 3 μg/mL ( IFNG M700A , Endogen , Woburn , MA , USA ) and incubated overnight at 4°C . A standardised responder T-cell number of 2 . 5 × 105 PBMC per well was added in quadruple or at least triplicate wells with one of the five stimulating peptides ( 1 μg/mL ) . Staphylococcus enterotoxin B ( SEB; Sigma , Munich , Germany , 1 μg/mL ) was used as positive control and negative controls were run in parallel using responder cells plus medium alone . Probes were incubated for 24 hours at 37°C . The detection of IFN-γ took place after an overnight incubation at 4°C with 100 μL ( 1 μL/mL ) biotinylated detection IFN-γ antibody ( IFNG-M701-B Biotin , Endogen ) . After adding streptavidine ( 1 μg/mL ) for 2 hours at room temperature , spots were developed by adding 200μL visualization solution , AEC ( 3-amino-9-ethylcarbazole , Sigma ) in acetate buffer supplemented with H2O2 30% for 3–5 min . Resulting spots were counted using a computer-assisted Elispot reader ( Immunospot , Cellular Technologies , Ltd . , Cleveland , OH , USA ) . The number of SFU·10−6 PBMC was calculated by adding spot counts from each well . The models were fitted using the function fminsearch of the mathematical open-access software Scilab , which employs the Nelder-Mead algorithm [36] . To ensure that the minimum of the objective function is reached , several replications ( > 100 ) of the estimation were performed , using vastly different ( > 2 orders of magnitude in some cases ) starting parameter sets . The objective functions for the immune dynamics and the viral dynamics , which take the form of vertical least-squares , are defined in the Results section ( Eqs 2 and 7 ) . To avoid overestimating the degrees of freedom of each hypothesis , parameters appearing only as the product of two free parameters are considered as only one free parameter . This is the case for model VPμ-sLTμ , where m·maxμ and m·maxM are estimated as two parameters , instead of three parameters . Bayesian Information Criterion ( BIC ) differences were employed as the model selection criterion . Additionally , the Akaike’s Information Criterion ( AIC ) was also calculated . The corrected Akaike’s Information Criterion ( AICc ) was not used , as its value was not calculable for certain patient/hypotheses combinations . BIC and AIC were estimated for each patient i and hypothesis h under the assumption of independent , normally distributed errors BICih=Nilnfih+KihlnNi AICih=Nilnfih+2Kih ( 8 ) where Ni is the total number of measurements per patient i , Kih is the number of parameters for patient i and hypothesis h , and fih is the objective function for patient i and hypothesis h as defined in Eq 6 . [33] AIC and BIC differences were calculated as ΔBICih=BICih-min ( BICi ) ΔAICih=AICih-min ( AICi ) ( 9 ) where the function min denotes the lowest AIC or BIC achieved for a patient . A difference in the range [0 , 2] for ΔBICih is considered to give substantial empirical support for the hypothesis h in patient i [33] . 95% confidence intervals were estimated using bootstrapping , as described in Banks et al . [37] . Briefly , for each of the six patients the dynamics were simulated with the best-performing hypothesis ( VPε-sLTμ ) and the best-fitting parameter set ( Table 4 ) . Residuals for the viral load were calculated as the difference between predicted and observed viral load for each time point . The residuals of each patient ( excluding the first residual , which is zero by definition ) were randomly resampled with replacement 1000 times , constructing 1000 artificial data sets for each patient , each with the same number of measurements as the patient . These artificial data sets were subject to fitting using as initial parameter values those in Table 4 . The obtained distribution of estimated parameters for each patient was employed to calculate the 95% confidence intervals: for a normal distribution of parameter values for a patient , the confidence intervals were calculated as the mean ± 1 . 96 · standard deviation; for skewed distributions ( absolute value of skewness or kurtosis higher than 2 ) , the 95% confidence intervals were calculated directly from the 25th and 975-th entries in the set of ordered parameter estimates .
BK virus ( BKV ) is the cause of a kidney disease affecting 1–10% of kidney transplant recipients , which leads to transplantation failure in about 50% of the cases . This disease is not well understood , but there are indications that markers of the immune response against BKV can be used to predict the outcome . Since the immune response can act through different modes of action , we have studied the dynamics between immune response and virus to determine which modes of action play an important role in the fight against BKV . We have analysed immune and viral kinetics in six kidney transplantation patients and developed a mathematical model to integrate the data and better understand the interactions between virus and immune response to different BKV antigens . Our results allow for discarding the majority of action modes hypotheses . The most supported hypothesis is: structural proteins trigger the blocking of virus production by infected cells , whereas non-structural proteins trigger the acceleration of infected cells death . This difference could be central for disease outcome , as under this hypothesis only the latter would trigger a fast and continuous BKV clearance .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "blood", "cells", "cell", "death", "urinary", "system", "procedures", "medicine", "and", "health", "sciences", "organ", "transplantation", "immune", "cells", "immune", "physiology", "enzyme-linked", "immunoassays", "viral", "transmission", "and", "infection", "immunology", "cell", "processes", "microbiology", "surgical", "and", "invasive", "medical", "procedures", "renal", "transplantation", "immunologic", "techniques", "viral", "load", "research", "and", "analysis", "methods", "transplantation", "immune", "system", "proteins", "white", "blood", "cells", "viral", "clearance", "animal", "cells", "proteins", "antigens", "t", "cells", "immunoassays", "immune", "response", "biochemistry", "cell", "biology", "virology", "physiology", "biology", "and", "life", "sciences", "cellular", "types" ]
2018
Differential T cell response against BK virus regulatory and structural antigens: A viral dynamics modelling approach
Otitis media ( OM ) , inflammation of the middle ear ( ME ) , is a common cause of conductive hearing impairment . Despite the importance of the disease , the aetiology of chronic and recurrent forms of middle ear inflammatory disease remains poorly understood . Studies of the human population suggest that there is a significant genetic component predisposing to the development of chronic OM , although the underlying genes are largely unknown . Using N-ethyl-N-nitrosourea mutagenesis we identified a recessive mouse mutant , edison , that spontaneously develops a conductive hearing loss due to chronic OM . The causal mutation was identified as a missense change , L972P , in the Nischarin ( NISCH ) gene . edison mice develop a serous or granulocytic effusion , increasingly macrophage and neutrophil rich with age , along with a thickened , inflamed mucoperiosteum . We also identified a second hypomorphic allele , V33A , with only modest increases in auditory thresholds and reduced incidence of OM . NISCH interacts with several proteins , including ITGA5 that is thought to have a role in modulating VEGF-induced angiogenesis and vascularization . We identified a significant genetic interaction between Nisch and Itga5; mice heterozygous for Itga5-null and homozygous for edison mutations display a significantly increased penetrance and severity of chronic OM . In order to understand the pathological mechanisms underlying the OM phenotype , we studied interacting partners to NISCH along with downstream signalling molecules in the middle ear epithelia of edison mouse . Our analysis implicates PAK1 and RAC1 , and downstream signalling in LIMK1 and NF-κB pathways in the development of chronic OM . Otitis media ( OM ) is characterised by inflammation of the middle ear ( ME ) , often associated with a conductive hearing impairment , and is the commonest cause of hearing loss in children . It is perceived by many to be a transient affliction that in reality places a substantial social , medical and economic burden on healthcare systems globally [1] . Evidence from studies of the human population suggests that there is a significant genetic component predisposing to the development of recurrent and chronic forms of OM [2 , 3] . Despite the importance of the disease , many of the genes involved in OM susceptibility have still yet to be identified . At present , the use of mouse models is the most promising method to identify candidate loci underlying susceptibility to OM . Mouse models have highlighted the role of Toll-like receptors ( TLRs ) in acute OM , in particular the protection against commensal and pathogenic bacteria , and that persistent NF-κB or TGF-β signalling could be two mechanisms leading to the overactive pro-inflammatory response seen in chronic OM [4 , 5] . The large-scale phenotype-driven mouse ENU ( N-ethyl-N-nitrosourea ) mutagenesis program at MRC Harwell [6 , 7] has previously identified two novel mouse mutants , Jeff and Junbo , that develop a conductive hearing loss characterised by ME fluid and mucosal inflammation [8 , 9] . The Jeff mouse has a mutation in the Fbxo11 gene [10] and the Junbo mouse has a mutation in Evi1 [9] . Studies have revealed that these genes , are involved in signalling of the TGF-β superfamily , via SMAD proteins [11 , 12]; negatively regulate NF-κB–dependent inflammation [13]; and highlight the role of HIF–VEGF pathways in the underlying genetic and pathophysiological mechanisms that predispose to chronic OM [14] . OM mouse models with single gene mutations have identified a number of genes as candidate susceptibility genes for human OM , including Tlr2 , Tlr4 , p73 , E2f4 , Plg , Tgif1 , Evi1 and Fbxo11 [4] . These genes identified from mouse models of OM are beginning to be studied in the human population; with significant associations between OM and polymorphisms in FBXO11 [15 , 16] , TLR2 [17] and TLR4 [17–19] . We have identified and characterised a novel OM mouse mutant , edison , from the ENU mutagenesis program at MRC Harwell . Homozygous edison mice spontaneously develop a conductive hearing loss associated with chronic inflammation of the ME , sharing many features with chronic OM in humans . The underlying mutation of this phenotype has been identified as a mutation in the Nisch gene . We have explored the role of Nisch in chronic OM , relating the edison phenotype to the underlying mechanisms of Nisch function . We have utilised double mutants to assess genetic interactions and pathways involved , implicating PAK1 and RAC1 , and downstream signalling events in LIMK1 and NF-κB signalling pathways in the development of chronic OM . Overall , the edison mouse highlights a new candidate gene for susceptibility to chronic OM and has provided further insight into the genetic pathways and pathogenic processes involved . A phenotype-driven ENU mutagenesis screen [20] identified a new recessive mutant , edison ( edsn ) , with hearing loss . Preliminary phenotyping using a click-box test ( 20 kHz , 90 dB sound pressure level ( SPL ) tone burst ) of an age-matched cohort derived from the founder mouse indicated that 6-week-old ( wk ) mice demonstrated a reduced startle response . SNP-based linkage analysis and mapping identified an approximately 9 Mb interval on chromosome 14 delineated by marker rs30778552 and rs46823676 containing 119 genes ( Fig 1A ) . Whole-genome sequencing identified 60 ENU-induced , de novo variants within the critical 9Mb interval and importantly only one missense variant was identified . This missense variant was a c . 3079T>C substitution in Nischarin ( Nisch ) ( open reading frame of NCBI RefSeq transcript NM_022656 . 2 ) that results in a Leu972Pro substitution ( Fig 1B ) . The change occurs in a highly conserved region that has been maintained through evolution ( Fig 1C ) . PROVEAN analysis predicts that this change is ‘‘deleterious” and SIFT predicts that it is ‘‘not tolerated” . No other non-synonymous sequence changes were identified within the minimal interval . The Nisch locus encodes a protein of 1 , 593 amino acids , coded for by 22 exons . The protein consists of an N-terminal phox homology ( PX ) domain , six putative leucine-rich repeats ( LRRs ) , a predicted coiled-coil ( CC ) domain , an alanine/proline-rich region and a long C-terminal region ( Fig 1D ) . DNA and sperm archives derived from ENU mutagenesis programmes [21] were utilised to identify an additional allele at the Nisch locus . We screened ten exons of Nisch employing high resolution melting analysis of ~10 , 000 mutant mice and identified a c . 98T>C substitution resulting in a Val33Ala substitution within a conserved region of the NISCH PX domain . We rederived this second allele , NischV33A , and examined the phenotypes . NISCH binds to the cytoplasmic domain of ITGA5 [23] , and is thought to regulate its expression [24] . Cross-talk between VEGF and integrins has been shown to be a critical factor in the regulation of angiogenesis and vascularization [25] . Given these findings we examined the genetic interaction between Nisch and Itga5 . Nischedsn/+ mice and Itga5tm1Hyn/+; Nischedsn/+ double heterozygotes were intercrossed to produce Itga5tm1Hyn/+; Nischedsn/edsn littermates for the study , with Itga5tm1Hyn/+; Nisch+/+ and Itga5+/+; Nischedsn/edsn progeny as littermate controls ( Fig 5 ) . Itga5+/+; Nisch+/+ , Itga5+/+; Nischedsn/+ and Itga5tm1Hyn/+; Nisch+/+ mice showed normal click ABR thresholds across the study ( Fig 5A ) . Both Itga5+/+; Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice displayed a progressive hearing loss with onset at 4 wk . Interestingly , Itga5tm1Hyn/+; Nischedsn/edsn mice exhibited significantly elevated auditory thresholds compared to Itga5+/+; Nischedsn/edsn mice , throughout the time course ( Kruskall-Wallis: p < 0 . 01 ) . At 20 wk , Itga5tm1Hyn/+; Nischedsn/edsn animals were recorded with a mean click ABR threshold of 61 ± 3 dB SPL , compared to 40 ± 4 dB SPL for Itga5+/+; Nischedsn/edsn mice . There was a consistently high prevalence of OM in Itga5tm1Hyn/+; Nischedsn/edsn mice compared to Itga5+/+; Nischedsn/edsn animals ( Fig 5C and 5D ) . Itga5tm1Hyn/+; Nischedsn/edsn mice exhibited significantly increased OM prevalence at 4 wk compared to Itga5+/+; Nischedsn/edsn mice ( Fisher Exact: p = 0 . 026 ) . At 4 wk , 67% of Itga5tm1Hyn/+; Nischedsn/edsn mutants had bilateral OM and 33% had unilateral OM ( n = 12 ) , whereas in Itga5+/+; Nischedsn/edsn mice at 4 wk , 13% had bilateral OM , 63% unilateral OM and 25% showed no OM phenotype ( n = 8 ) . By 20 wk , the difference in OM prevalence observed between Itga5tm1Hyn/+; Nischedsn/edsn and Itga5+/+; Nischedsn/edsn mice was still increased ( Fisher Exact: p = 0 . 051 ) . In Itga5tm1Hyn/+; Nischedsn/edsn mutants at 20 wk , 83% had bilateral OM and 17% had unilateral OM ( n = 12 ) . While , in Itga5+/+; Nischedsn/edsn mice at 20 wk , 38% had bilateral OM , 25% unilateral OM and 37% showed no OM phenotype ( n = 8 ) . One Itga5tm1Hyn/+; Nisch+/+ mouse ( n = 15 ) displayed unilateral OM at 4 wk , with no other recordings at later time points ( S4A Fig ) . Histological examination confirmed that Itga5+/+; Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice develop chronic OM ( Fig 5E–5J ) . Itga5tm1Hyn/+; Nischedsn/edsn mice displayed a more severe mucosal inflammation , with increased polypoid exophytic growths and a thick cellular effusion . Blinded assessment of the mucoperiosteum thickness ( Fig 5K ) indicated that both Itga5+/+; Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice had significant mucosal thickening compared to wild-type littermates ( Kruskall-Wallis: p = 0 . 003 and p < 0 . 001 respectively ) . Additionally , when only OM ears from Itga5+/+; Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice were compared ( Fig 5L ) , there was a significant increase in mucosal thickness observed in Itga5tm1Hyn/+; Nischedsn/edsn mice ( Itga5+/+; Nischedsn/edsn , 97 . 8 ± 12 . 12 μm , n = 8; Itga5tm1Hyn/+; Nischedsn/edsn , 137 . 9 ± 10 . 85 μm , n = 9; Kruskall-Wallis: p = 0 . 026 ) . Additionally , double heterozygotes ( Itga5tm1Hyn/+; Nischedsn/+ ) exhibited a mild late-onset hearing loss , with onset at 12 wk ( Fig 5A ) . Visualisation of the tympanic membrane showed this mild hearing loss was associated with a late-onset in the prevalence of OM from 12 wk in Itga5tm1Hyn/+; Nischedsn/+ mice ( S4B Fig ) . By 20 wk , Itga5tm1Hyn/+; Nischedsn/+ mice exhibited significantly increased prevalence of OM compared to wild-type littermates ( Fisher Exact: p = 0 . 041 ) . In Itga5tm1Hyn/+; Nischedsn/+ mutants at 20 wk , 31% had unilateral OM and 69% had no OM phenotype ( n = 13 ) . Histological examination confirmed that Itga5tm1Hyn/+; Nischedsn/+ mice develop chronic OM ( S4D and S4F Fig ) . The mucosal inflammation was diffuse and of mild severity , with the presence of a cellular effusion . Blinded assessment of the mucoperiosteum thickness indicated that Itga5tm1Hyn/+; Nischedsn/+ mice had significant mucosal thickening compared to wild-type littermates ( Fig 5K ) . We proceeded to investigate the expression of interacting partners to NISCH , including ITGA5 , as well as key downstream effectors in order to relate the underlying mutation to the edison phenotype . In addition to binding ITGA5 , NISCH has also been shown to interact directly with PAK1 [23 , 26] , and RAC1 [27] . As well as being a downstream effector of PAK1 , LIMK1 [28] also interacts directly with NISCH . In addition PAK controls NF-κB activation [29] and RAC1 leads to activation of NF-κB [30 , 31] . We thus performed IHC expression analysis of NISCH , ITGA5 , phosphorylated-PAK1 ( p-PAK1 ) , phosphorylated-LIMK1/2 ( p-LIMK1/2 ) , RAC1 and NF-κB p65 on ME epithelia from wild-type , Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice . In addition , we assessed protein expression in ME epithelia by western blot analysis for each of these proteins . IHC labelling for NISCH , ITGA5 and p-PAK1 was observed in ME epithelial cells with similar patterns of expression in Nisch+/+ , Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice . No obvious differences in localisation were observed for these three proteins , although staining was stronger in Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice ( Fig 6A–6C ) . Western analysis of ME epithelial cell lysates showed raised levels of ITGA5 in Nischedsn/edsn mice but not significantly different compared to wild-type ( t-test: p = 0 . 071 ) and not surprisingly a significant decline in levels between Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice ( t-test: p = 0 . 020 ) ( Fig 7A ) . PAK1 protein levels were significantly raised in both Nischedsn/edsn ( t-test: p = 0 . 002 ) , and Itga5tm1Hyn/+; Nischedsn/edsn mice ( t-test: p = 0 . 006 ) when compared to wild-type , but not between Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice ( t-test: p = 0 . 282 ) ( Fig 7B ) . Available antibodies for p-LIMK1 were ineffective . However , we carried out expression analyses using a p-LIMK1/2 and LIMK1 antibody . IHC analysis of p-LIMK1/2 expression in ME epithelial cells revealed nuclear localisation and increased expression from both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice ( one-way ANOVA: p < 0 . 001 ) compared to wild-type . However , no significant difference was observed between ME epithelial cells in Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice ( one-way ANOVA: p = 0 . 704 ) ( Fig 6D ) . Similarly , protein levels of p-LIMK1/2 in ME epithelial cells were significantly raised in Nischedsn/edsn ( t-test: p = 0 . 039 ) and Itga5tm1Hyn/+; Nischedsn/edsn ( t-test: p = 0 . 038 ) compared to wild-type . No difference was detected between Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn samples ( t-test: p = 0 . 598 ) , consistent with the observations from immunohistochemistry ( Fig 7C ) . In addition , levels of LIMK1 in ME epithelial cells were also significantly raised in Itga5tm1Hyn/+; Nischedsn/edsn compared to wild-type ( t-test: p = 0 . 030 ) and Nischedsn/edsn ( t-test: p = 0 . 041 ) mice ( Fig 7D ) . IHC analysis of RAC1 demonstrated nuclear localisation and increased expression from Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type ( one-way ANOVA: p < 0 . 001 ) ( Fig 6E ) . Moreover , in agreement with these observations , protein levels of RAC1 were significantly raised in Itga5tm1Hyn/+; Nischedsn/edsn mice ( t-test: p = 0 . 033 ) , compared to wild-type ( Fig 7E ) . IHC analysis of NF-κB p65 expression showed nuclear localisation and raised levels of protein in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type ( one-way ANOVA: p = 0 . 017 and p <0 . 001 respectively ) . Moreover , there was a significant enhancement of NF-κB labelling in the double mutant compared to Nischedsn/edsn ( one-way ANOVA: p = 0 . 026 ) ( Fig 6F ) . In agreement with IHC , we found significantly higher levels of NF-κB p65 by western blot in both mutants compared to wild-type ( t-test: p = 0 . 039 and p = 0 . 041 ) ( Fig 7F ) . We also examined levels of activated NF-κB p65 by western blot employing an antibody that recognises phosphorylated-NF-κB [Ser 276] p65 ( p-NF-κB p65 ) and detected significantly higher levels of the activated protein in both mutants compared to wild-type ( t-test: p = 0 . 030 and p = 0 . 035 ) ( Fig 7G ) . In addition , we investigated the expression of two pathways that are implicated in the development of chronic OM ( see Introduction ) , or are regulated by NISCH interacting partners . First , we evaluated levels of focal adhesion kinase ( FAK ) and SRC . Cross-talk between integrins and VEGF is a critical factor in the regulation of angiogenesis , vascularisation and vascular permeability [25] . Integrins regulate VE-cadherin via the activation of SRC , and FAK catalytic activity is required when α5β1 integrin stimulates SRC activation through FAK phosphorylation . FAK inhibition prevents VEGF-stimulated vascular permeability underlining the importance of FAK activity in the regulation of adherens junctions [32] . Tyr 397 in human FAK becomes phosphorylated upon integrin engagement and creates a binding site for SRC . This results in release of the inactive conformation of SRC ( Tyr 527 ) and leads to autophosphorylation of SRC on Tyr 416 . Activated SRC further phosphorylates FAK on additional residues , one of which is Tyr 576 . The activated FAK-SRC complex then initiates multiple downstream signalling pathways [33 , 34] . IHC of ME epithelial cells showed there was increased expression of total FAK in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn compared to wild-type mice ( one-way ANOVA: p = 0 . 015 and p < 0 . 001 respectively ) . A significant difference was also observed between Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn ears ( one-way ANOVA: p = 0 . 005 ) ( Fig 6G ) . To study protein levels of FAK we used an antibody raised against the last 50 amino acids at the C-terminal of the human protein . There are nine known mouse isoforms of FAK ( http://www . uniprot . org/uniprot/P34152 ) produced by alternative promoter usage and alternative splicing and the antibody is potentially able to detect six of them . We detected three main bands in ME epithelial cell lysates at 124 , 115 and 100kDa . The full-length canonical isoform is 124kDa . We detected significantly increased levels of the full length 124kDa FAK1 protein in Nischedsn/edsn mutants compared to wild-type ( t-test: p = 0 . 014 ) . The level of the 115kDa form was significantly raised in Nischedsn/edsn ( t-test: p = 0 . 014 ) and Itga5tm1Hyn/+; Nischedsn/edsn ( t-test: p = 0 . 001 ) mice compared to wild-type , while the 100kDa form was the main isoform detected in wild-type samples . A significant difference was detected in the levels of the 100kDa between wild-type and Itga5tm1Hyn/+; Nischedsn/edsn ( t-test: p = 0 . 0005 ) ( Fig 7H ) . Furthermore we used phosphorylated-FAK ( p-FAK ) [Y576] and phosphorylated-SRC ( p-SRC ) [Y527] antibodies to test the activity of the FAK-SRC complex in middle ear epithelia . Using a p-FAK [Y576] antibody , which recognises activated FAK , we detected an increase in the activated FAK in the Nischedsn/edsn tissue compared to the wild-type ME epithelial cell lysate ( t-test: p = 0 . 007 ) ( Fig 7I ) . Not surprisingly , in the double mutant Itga5tm1Hyn/+; Nischedsn/edsn , levels of activated FAK were not significantly different to wild-type . Using a p-SRC [Y527] antibody , which recognises inactive SRC , we detected complementary results to that seen with activated FAK . We found reduced levels of protein in Nischedsn/edsn ME lysates compared to the wild types ( t-test: p = 0 . 002 ) but no differences between wild-type and Itga5tm1Hyn/+; Nischedsn/edsn ( Fig 7J ) . Finally , we proceeded to evaluate activation of the TGF-β pathway during chronic ME disease by assessment of phosphorylated-SMAD2 ( p-SMAD2 ) . IHC analysis of p-SMAD2 revealed significantly raised levels in Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type ( one-way ANOVA: p < 0 . 001 ) . However , there was no significant difference between Nischedsn/edsn and wild-type mice ( one-way ANOVA: p = 0 . 680 ) ( Fig 6H ) . In addition , protein levels of p-SMAD2 in ME epithelial cells were significantly higher in Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type ( t-test: p = 0 . 029 ) or Nischedsn/edsn ( t-test: p = 0 . 024 ) mice . Again no difference was detected between wild-type and Nischedsn/edsn mice ( t-test: p = 0 . 864 ) ( Fig 7K ) . IHC analysis of this suite of proteins in airway epithelia revealed many similarities to that seen in ME epithelia ( S5 Fig ) . Levels of NISCH appeared to be raised in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type . Furthermore , increased epithelia expression of p-LIMK1/2 in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice mirrored the findings in ME epithelia . Similarly , RAC1 epithelial levels were significantly raised in Itga5tm1Hyn/+; Nischedsn/edsn mice , while NF-κB and FAK expression was raised in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice . However , we observed no significant changes in p-SMAD2 levels in mutant airways . In contrast , in lung tissue we observed very few significant changes in protein levels by western blot analysis ( S5 Fig ) . These results may reflect the complexity of tissues and cell types isolated from dissected material and the visible mesenchymal expression for many of these proteins in airway tissue . In a large-scale ENU mutagenesis screen we recovered a new recessive mouse model of chronic OM , edison . The edison mutant carries a Leu972Pro change in the Nischarin gene . Nischedsn/edsn homozygotes display a progressive middle ear disease with 56% of mice displaying bilateral OM by 20 weeks and elevated ABR thresholds of 20–30 dB SPL indicative of a conductive hearing loss . We derived an additional ENU allele ( NischV33A ) in the Nischarin gene which also presents with progressive chronic OM , but where ABR thresholds were only very moderately increased and at 12 weeks only 10% of the mice had bilateral OM . It appears that the NischV33A allele is severely hypomorphic . Compound heterozygotes of the edison and NischV33A alleles showed an intermediate non-complementing OM phenotype . We did not identify any sensorineural element to the hearing loss in the Nischedsn/edsn mutant . The chronic OM in Nischedsn/edsn mice is exemplified by exudate within the ME cavity and a thickened mucoperiosteum and polypoid exophytic growths , sometimes associated with an inflamed tympanic membrane . Serous or granulocyte-rich effusions were observed , but as the mice aged a thick effusion was predominately observed rich in macrophages and PMNs . Examination of ME exudates for upregulation of both inflammatory genes and hypoxia genes found that both Il-1b and Tnfa were both upregulated , as were Hif1a and the HIF responsive gene Vegfa . This is similar to the findings reported for other mouse models of chronic OM , such as the Jeff [8] , Junbo [9] and Tgif1 [35] mutants . Both the middle ear and the lungs have substantial similarities in structure and function [36] and , intriguingly , we identified a lung defect in Nischedsn/edsn mice . During embryonic development , we found a significant reduction in airspace width , while in the adults , we observed an emphysema-like phenotype with enlarged airspace width and a reduced number of airspaces . In utero , the network of airways is generated first followed by formation of the gas-exchanging units ( alveoli ) that develop from the distal ends of the small airways . As a consequence disruption to lung development often results in narrower airspaces in embryonic lungs but enlarged airspaces post-natally because of insufficient generation of alveoli . These lung abnormalities likely account for the deficit of Nischedsn/edsn mice recovered from the various crosses that we report . The discovery of the involvement of Nischarin in the development of inflammatory middle ear disease identifies a novel gene and associated pathways that are involved in OM . This led us to explore the intersection with known pathways of OM [11 , 13 , 14] and the downstream signalling mechanisms that lead to the OM phenotype . Nischarin is a highly conserved protein across mammalian species , consisting of an N-terminal phox homology ( PX ) domain , 6 putative leucine-rich repeats , a coiled-coil domain , an alanine/proline-rich region and a long C-terminal region . NISCH has a multitude of interacting partners , including ITGA5 [37] , PAK1 [26] , Rac1 [27 , 38] , LIMK1 [28] , Rab14 , PI3P [38] , and LKB1 [39] . Association of NISCH with these interacting partners underlines its broad impact on the regulation of cell motility , cell invasion , vesicle maturation , as well as its role as a tumour suppressor [28 , 37 , 38 , 40] . Most notably , the binding of NISCH to ITGA5 [37] is thought to mediate the translocation of ITGA5 from the cell membrane to endosomes [24] thus regulating ITGA5 levels . As we discuss above , integrins have been shown to play a critical role in modulating VEGF-induced angiogenesis and vascularization [25] . These pathways thus intersect with the hypoxia-response pathways mediated by HIF-1a which have been demonstrated to be involved with the development of chronic OM in the Junbo and Jeff models [14] . Hypoxia leads to upregulation of VEGFA and downstream pathway genes resulting in VEGF-induced angiogenesis and vascular leak . VEGFR inhibitors moderated angiogenesis and lymphangiogenesis in the Junbo mouse . For these reasons we sought to explore the role of ITGA5 in the edison mutant , and also to characterise the responses of downstream pathways which may illuminate the mechanisms of OM development in edison . We found a strong genetic interaction between edison and Itga5 mutants . Itga5tm1Hyn/+; Nischedsn/edsn double mutants compared to Nischedsn/edsn mice showed significantly elevated ABR thresholds as well as a very significant raised frequency of bilateral OM in mice from 4 weeks onwards . In summary , the OM was more highly penetrant from an earlier age , and commensurately less progressive . Given the interactions of ITGA5 and NISCH , along with the interactions of NISCH with diverse molecules involved in LIMK1 and NF-κB signalling , we sought to interpret this genetic interaction in the context of known signalling pathways and interactions downstream of NISCH . Moreover , in developing a mechanistic model , we took into account the reports that interaction of ITGA5 with NISCH affects some of the downstream interactions of the NISCH molecule itself . RAC1 signalling regulates disparate cellular functions mediated through a variety of effector proteins [30 , 31] . PAK1 is a key downstream effector of RAC1 [41 , 42] , with binding of RAC1 leading to activation of PAK1 [43] . NISCH represses this pathway , and NISCH has been shown to block RAC1 induced cell migration through binding to PAK1; interaction with NISCH strongly inhibits the kinase activity of PAK1 [23] . RAC1 activation of PAK1 enhances the interaction between NISCH and PAK1 , while notably expression of ITGA5 also increases the association between NISCH and PAK1 [23] . LIMK1 is a downstream effector of PAK1 [44] and has been shown to be involved in vascular permeability [45] . NISCH is also an interacting partner with LIMK1 , regulating cell invasion through repression of the LIMK1-cofilin pathway [28] . NISCH also regulates PAK1-independent RAC1 signalling through direct interaction with RAC1 [27] . RAC1 stimulates the phosphorylation and degradation of IkB and up-regulates NF-κB [46 , 47] . Overexpression of NISCH has been shown to suppress the ability of RAC1 to stimulate NF-κB activation [27] . The Junbo OM mutant carries a mutation in the Evi1 gene , and it is noteworthy that EVI1 is a negative-feedback regulator of NF-κB [13] . The mutation in Junbo leads to activation of NF-κB and inappropriate regulation of the inflammatory response [13] . We have assessed the expression of the critical genes within these pathways in the ME epithelia of wild-type , Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice . First , we observed that levels of ITGA5 were raised in Nischedsn/edsn mice though not significantly , reflecting the role of NISCH in regulating ITGA5 levels . Not surprisingly , ITGA5 was significantly reduced compared to edison mice in the double mutant , Itga5tm1Hyn/+; Nischedsn/edsn . We found significantly raised levels of activated p-PAK1 in both mutant lines compared to wild-type , which was mirrored by downstream raised levels of p-LIMK1/2 in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice . Raised levels of p-LIMK1/2 were also reflected in the IHC assessment . LIMK1 levels were also raised in Nischedsn/edsn Itga5tm1Hyn/+ mice . We were unable to assess directly levels of p-LIMK1 due to the ineffectiveness of available antibodies . While RAC1 protein levels were not affected in Nischedsn/edsn mice , they were significantly raised in the double mutant , Itga5tm1Hyn/+; Nischedsn/edsn mice which was mirrored in the IHC assessment . We also found by both IHC and western analysis that NF-κB levels were raised in both Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice compared to wild-type . Moreover , there is evidence from IHC that the effect of the two mutations are additive and that the double mutant shows a significantly higher level of NF-κB expression compared to Nischedsn/edsn mice . While the protein analysis shows a similar trend the differences between Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice are not significant . Overall , our analysis indicates that the edison mutation leads to activation of PAK1 and PAK1-independent RAC1 pathways with increased levels of NF-κB and p-LIMK1/2 each of which may lead to inflammatory and vascular permeability effects . In addition , a combination of mutations in NISCH and ITGA5 can lead to an exacerbation of raised protein levels which may underlie the more severe phenotype seen in the double mutant , Itga5tm1Hyn/+; Nischedsn/edsn . This may reflect the role of ITGA5 in enhancing binding of NISCH to PAK1 , and provides us with a model of the mechanism underlying the Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn phenotypes ( Fig 8 ) . We surmise that impairing function of NISCH leads to derepression of RAC1 pathways , while reducing levels of ITGA5 in combination with impaired NISCH leads to further derepression and activation of downstream pathways manifested in the more severe phenotype . However , we did not observe significantly raised levels of RAC1 in the single mutant . Nevertheless , we found raised levels of NF-κB that may reflect activation of PAK1 independent pathways . ITGA5 is known to be involved with the activation of SRC protein tyrosine kinase , as well as FAK , both of which are involved with mediating VEGF induced vascular leak [32] . ITGA5 can mediate its effects by phosphorylation of FAK and binding of activated FAK to SRC leading to conformational SRC activation [33] . Alternatively , for example in the context of neuroblastoma cell motility , FAK is required for integrin α5β1-mediated SRC phosphorylation [34] . We thus investigated FAK and SRC levels in the mutant mice , focusing on activated FAK and inactive SRC . We found total levels of the full length isoform of the FAK protein raised in Nischedsn/edsn mice . However , in Itga5tm1Hyn/+; Nischedsn/edsn mice , full length FAK protein was not significantly different to wild-type . Importantly , we detected raised levels of activated FAK along with reduced levels of inactive SRC in Nischedsn/edsn mice . These changes may contribute to angiogenesis and vascular permeability through upregulation of VEGF signalling pathways . The genes mutated in previously characterised OM models ( Junbo , Jeff and Tgif1 ) , have been reported to regulate the TGF-β signalling pathway [11 , 12 , 35] . There is considerable cross-talk between TGF-β signalling and hypoxia pathways and mutations that perturb the TGF-β pathway might be expected to perturb hypoxia responses with downstream consequences on VEGFA and VEGF signalling , as is observed in the mutants studied [14] . We discuss above the raised levels of HIF-1a and VEGFA found in the edison mutant . We thus assessed TGF-β signalling ( in edison ) , and found that p-SMAD2 levels are significantly raised in Itga5tm1Hyn/+; Nischedsn/edsn mice , but not in Nischedsn/edsn . The lack of raised p-SMAD2 levels in the Nischedsn/edsn mouse suggests that activation of TGF-β signalling is not a primary event underlying the development of chronic OM in the edison mouse . Rather , the upregulation of p-SMAD2 in the double mutant may reflect the very severe inflammatory state of the middle ear leading to activation of TGF-β pathways . In summary ( see Fig 8 ) , we conclude that mutations in Nischarin impact upon PAK-dependent and PAK-independent RAC pathways with downstream signalling effects on LIMK1 and NF-κB . Moreover , the interplay between Nischarin and ITGA5 likely underlies impacts on FAK and SRC signalling which may lead to VEGF mediated vascular leak . The combined effects on LIMK1 , NF-κB and FAK signalling can account for the observed inflammatory changes in the edison middle ear , which along with vascular leak and middle ear exudate , produce a chronic OM . Together , the pathways changes we describe provide a mechanism underlying the observed phenotypic changes in edison . Moreover , these studies further enhance our knowledge of the relevant genetic pathways that contribute to middle ear inflammatory disease , as well as a panel of new genes that are candidates for genetic susceptibility to chronic OM in the human population . Mice were bred and maintained by Mary Lyon Centre , MRC Harwell and were housed in specific-pathogen free conditions . All animal experimentation was approved by the Animal Welfare and Ethical Review Body at MRC Harwell ( License Numbers: 30/3015 and 30/3280 ) . The humane care and use of mice in this study was under the authority of the appropriate UK Home Office Project License . The founder mouse carrying the edison mutation was generated in a large-scale phenotype-driven ENU mutagenesis program at MRC Harwell [20] . Briefly , Male C57BL/6J mice were mutagenized and mated to C3H . Pde6b+ females ( a C3H stock that does not carry the retinal degeneration allele Pde6brd ) . G3 offspring were screened for a variety of abnormalities , including deafness and vestibular dysfunction . The edison founder was identified due to lack of a Preyer reflex when presented with a calibrated 20 kHz , 90 dB SPL tone burst via a click-box test . The founder edison mouse was maintained by repeated outcrossing to C3H/HeH and intercrossing to produce homozygous mutant progeny , identified by the lack of a Preyer reflex . For linkage analysis genomic DNA from 13 affected mice were screened with 63 strain specific SNP markers spaced equidistantly across the genome using the Pyrosequencing SNP genotyping system ( QIAGEN ) . Additional SNP markers were used within linked regions to further fine map the causal mutation . Markers and primer sequences are available on request from the authors . Genomic DNA from a single affected edison mouse was sent for next-generation sequencing ( High-Throughput Genomics , WTCHG ) . Identification , analysis and dissemination of sequence variant information identified through whole-genome sequencing were achieved with the tools provided by the MRC Harwell Biocomputing custom sequence analysis pipeline . Sequence reads were mapped to the NCBI37/mm9 assembly of the reference mouse genome . Within the critical interval , the mean read depth was 8 . 17 and the read coverage was 99 . 64% . Sequence variants were identified and were subsequently categorised into those which occurred within exons and splice donor/acceptor sites , and were not known or strain-specific variants . This led to the identification of a T to C base substitution within exon 14 of Nisch , which is predicted to cause a Leu972Pro missense change in NISCH protein . This sequence variant was validated using Sanger sequencing ( Source BioScience , UK ) . Affected and unaffected mice were genotyped using the LightScanner SNP genotyping system ( Idaho Technology Inc . , USA ) to confirm the association of genotype to phenotype . In all cases the genotype correlated with the phenotype . DNA from the MRC Harwell ENU-DNA sperm archive ( http://www . har . mrc . ac . uk/services/archiving-distribution/enu-dna-archive ) was screened with the LightScanner platform ( Idaho Technology Inc . , USA ) . Briefly , male C57BL/6J mice were treated with ENU and crossed to C3H/HeH females . F1 progeny ( C3H/HeH . C57BL/6J ) were rederived and male F1 animals had sperm and DNA samples taken for archiving . Ten exons of Nisch were screened in DNA from ~10 , 000 F1 ENU mutagenised animals and potential mutations confirmed with Sanger sequencing ( Source BioScience , UK ) . All edison mice used for phenotyping were congenic on a C3H/HeH background . They were backcrossed for at least ten generations . The NischV33A strain was rederived by in vitro fertilisation of C57BL/6J oocytes with F1 sperm from the MRC Harwell ENU-DNA sperm archive and maintained on a mixed C3H/HeH and C57BL/6J genetic background . NischV33A/+ mice were intercrossed for phenotypic analysis and crossed to congenic Nischedsn/+ mice for complementation testing . Cryopreserved Itga5tm1Hyn mutant sperm was imported from the Jackson Laboratory ( Stock No . 002274 ) [48] and the colony was rederived using in vitro fertilisation of C57BL/6J oocytes . Itga5tm1Hyn mice had been backcrossed 4–5 generations onto a C3H/HeH background , before crossing to congenic Nischedsn mice for phenotypic analysis . Genotyping for edison mice was performed using an allelic discrimination assay with primers 5’-GGC AGC ACA AAG ATG GCG GTA AC-3’ and 5’-AAC TGC CGC AAC CGC AAC A-3’ and labelled probes 5’-[6-FAM]_AGC AGC TCG AGC ACA T-3’ ( edsn ) and 5’-[TET]_CAG CTC GGG CAC ATG-3’ ( Wild-type ) . The Applied Biosystems 7900HT Fast System ( Applied Biosystems , USA ) was used for amplification and analysis . To genotype NischV33A mice , PCR amplification was performed with primers 5’-GAC TGA GTA CCT TGC AGC TA-3’ and 5’-CTG TAA CGG TGT TTG ATC GTC-3’ and an unlabelled probe 5’-CCC TTT AGG CTT ATG TCA TCC AGG TTA C_[SpC3]-3’ . The LightScanner System ( Idaho Technology Inc . , USA ) was used for subsequent unlabelled probe genotyping analysis . Itga5tm1Hyn mice were genotyped with mutant and control specific primers , as described on the Jackson Laboratory Mice Database ( http://jaxmice . jax . org/strain/002274 ) . Analysis of skulls from 20 wk mice was performed using a Faxitron Mx-20 DC-4 specimen X-ray System . ImageJ software was used to measure the skull length , nasal bone length , frontal bone length , parietal bone length and skull width . Allometric comparisons were performed against skull length with at least 12 mice of each genotype . Mice were anesthetized and hearing thresholds determined using ABR , as previously described [7] . The ABR threshold was measured for each ear . Click-evoked hearing assessments for edison mice were conducted at 3 , 4 , 6 , 8 , 12 , 16 and 20 wk with cohorts containing at least 14 mice of each genotype at each time point . Frequency-specific ( 8 , 16 , and 32 kHz ) analysis of auditory function for edison mice was conducted over a longitudinal time course at 4 , 6 , 8 , 12 and 20 wk with 5 mice of each genotype . At least 10 NischV33A mice were used for click-evoked ABR analysis across a longitudinal time course at 4 , 6 , 8 and 12 wk . Finally , click-evoked analysis of Itga5tm1Hyn Nischedsn hearing thresholds were measured across a longitudinal time course at 4 , 6 , 8 , 12 , 16 and 20 wk with at least 8 mice of each genotype . Mouse 3 , 4 , 6 , 8 , 12 , 16 and 20 wk heads from Nisch+/+ , Nischedsn/+ and Nischedsn/edsn mice were fixed for 48 hours in 10% neutral buffered formaldehyde , decalcified in D . F . B decalcifying agent ( Kristensen; Pioneer Research Chemicals ) for 72 hours and embedded in paraffin following routine procedures . Perinatal heads were processed in the same manner without the decalcification steps . Four-micrometre-thick sections were obtained , de-paraffinized in xylene substitute and rehydrated via a graded ethanol . For morphological observations , sections were stained with haemotoxylin and eosin ( H&E ) . The histological sections were used to investigate the middle ear inflammation of the mice . Evaluation of mean mucosal thickness was by blinded assessment of a standard 1000 μm length of ME mucosa ( avoiding the cochlea and the region close to the Eustachian tube ) , the mucosal thickness was averaged from five measurements . To study the lung morphology of edison mice , H&E stained sections from adult and perinatal lungs were viewed using a Zeiss Axiostar Plus bright-field microscope and analysed using cellB imaging software ( Olympus ) . The data was analysed as previously described [49] . To study the ultra-structure of the organ of Corti we dissected the inner ears from five 20 wk Nisch+/+ and Nischedsn/edsn mice and prepared the samples as previously described [50] . Inner ears were imaged using a JEOL 6010 LV scanning electron microscope under high vacuum conditions . Blood and bulla fluids were collected , as previously described [14] , for analysis using Real-time quantitative PCR . Real-time quantitative PCR was performed as previously described [14] . For ear fluid analysis , each sample pool comprised the fluid from both ears of four individual samples . For blood analysis each sample pool comprised four individual samples . Murine TaqMan gene expression assays used for analysis were Hif1a ( Mm01283756_m1 ) , Il1b ( Mm01336189_m1 ) , Tnfa ( Mm00443258_m1 ) , Vegfa ( Mm00437304_m1 ) , Src ( Mm00436785_m1 ) , Evi1 ( Mm00491303_m1 ) and Fbxo11 ( Mm01227499_m1 ) . Ppia ( Mm02342429_g1 ) was used as the endogenous control . For immunohistochemical analysis , the avidin–biotin complex ( ABC ) method was used to look for the localization of NISCH , ITGA5 , p-PAK , p-LIMK1/2 , RAC1 , NF-κB p65 , FAK and p-SMAD2 in wild-type and mutant mouse ME and lungs . The sections through the ears of mice were de-parafinized , and endogenous peroxidase activity was quenched with 3% hydrogen peroxide in isopropanol for 30 min . Vectastain Elite ABC kit ( Vector Laboratories , PK 6101 ) was used to perform the immunohistochemistry . The antibodies were as follows: rabbit polyclonal anti-NISCH ( sc-98980 , Santa Cruz Biotechnology ) , rabbit polyclonal anti-ITGA5 ( sc-10729 , Santa Cruz Biotechnology ) , rabbit polyclonal anti-p-αPAK ( Thr212 ) ( sc-101772 , Santa Cruz Biotechnology ) , rabbit polyclonal anti-p-LIMK1/2 ( Thr508/505 ) ( sc-28409-R , Santa Cruz Biotechnology ) , rabbit polyclonal anti-RAC1 ( sc-95 , Santa Cruz Biotechnology ) , rabbit polyclonal anti-p-SMAD2 ( Ser465/467 ) ( AB3849 , Chemicon International ) , rabbit polyclonal anti-FAK ( sc-558 , Santa Cruz Biotechnology ) rabbit polyclonal anti-NF-κB p65 ( ab131485 , Abcam ) . The sections were incubated with the antibodies overnight at the following dilutions: p-PAK , 1:50; NISCH , ITGA5 , p-LIMK1/2 , NF-κB p65 , FAK and p-SMAD2 , 1:200; Rac1 , 1:400 . For F4/80 visualisation , sections were treated with 0 . 05% trypsin in calcium chloride for 20 min at 37°C , blocked with 10% rabbit serum ( X0902 , DAKO ) , incubated with rat anti mouse F4/80 ( MCA497GA , Serotec ) antibody overnight at 1:100 dilution and the next day after the washes were incubated with biotinylated rabbit anti-rat secondary antibody at 1:400 dilution ( E0468 , DAKO ) . The serum and the secondary antibody for all the other antibodies were from the Vectastain Elite ABC kit and they were used according to the manufacturer's instructions . DAB+ chromogen system ( DAKO K3468 ) was used to develop the specific signals . The slides were counterstained with haematoxylin . Total protein extracted from the ME epithelial cells and lungs of two-months-old wild-type , Nischedsn/edsn and Itga5tm1Hyn/+; Nischedsn/edsn mice were used for the western blot analysis . Each middle ear sample consisted of combined epithelial cells scooped out of both ears of one mouse . Each lung sample consisted of whole lung tissue from one mouse . Either three or four biological replicates were performed for each antibody . The tissues were homogenised in CelLytic MT Cell Lysis Reagent ( Sigma C3228 ) , protease inhibitors , phosphatase inhibitors and vanadate and centrifuged at 4°C . Protein concentration was determined using the DC Protein Assay kit ( Bio-Rad ) . Samples ( 30 μg from the lung samples and 10 μg from the middle ear samples ) were loaded into 12% NuPAGE Bis-Tris gel , 7% NuPAGE Tris Acetate gel or 3–8% NuPAGE Tris acetate gels ( Invitrogen ) , blotted onto nitrocellulose membrane ( Invitrogen ) and immunostained . 5% non-fat milk in TBST was used as blocking solution and antibody diluent . The antibodies and the dilutions they were used at for the western blot analysis were as follows: rabbit polyclonal anti-ITGA5 ( sc-10729 , Santa Cruz Biotechnology ) 1:500 , rabbit polyclonal anti-PAK1 ( 2602 , Cell Signaling ) 1:1000 , rabbit polyclonal anti-p-LIMK1/2 ( Thr508/505 ) ( sc-28409-R , Santa Cruz Biotechnology ) 1:500 , goat polyclonal anti LIMK1 ( sc-8387 , Santa Cruz Biotechnology ) 1:500 , rabbit polyclonal anti-RAC1 ( sc-95 , Santa Cruz Biotechnology ) 1:500 , rabbit polyclonal anti-FAK ( sc-558 , Santa Cruz Biotechnology ) 1:500 , rabbit polyclonal anti-NF-κB p65 ( ab131485 , Abcam ) 1:1000 , rabbit polyclonal p-NFκB p65 ( Ser 276 ) ( sc-101749 , Santa Cruz Biotechnology ) 1:500 , rabbit polyclonal anti-phospho-FAK ( Tyr576 ) ( 44-652G , Invitrogen ) , rabbit polyclonal anti-phospho-SRC ( Tyr527 ) ( 2105 , Cell Signaling ) , rabbit polyclonal anti-phospho-SMAD2 ( Ser465 /467 ) ( 3101 , Cell Signaling ) 1:500 and actin ( A 2066 , Sigma ) . Goat anti-rabbit IgG ( H+L ) -HRP conjugate ( 1706515 , Bio-Rad ) , 1:3000 , was used as a secondary antibody for all the primary antibodies except for LIMK1 for which Rabbit anti-goat IgG ( H+L ) secondary antibody , HRP , 1:5000 ( 81–1620 , Invitrogen ) was used . ECL or ECL 2 ( GE Healthcare ) were used as detection system . All data are given as unadjusted mean +/- SEM ( standard error of the mean ) unless stated otherwise . Data were analysed to establish normal distribution . Where data was normally distributed an ANOVA or Student’s t-test were conducted . If data was not normally distributed the non-parametric equivalents of these tests were used ( Kruskal-Wallis One Way Analysis of Variance on Ranks or Mann-Whitney Rank Sum Test ) to establish if data were significant . The Holm-Sidak method ( ANOVA ) or Dunn’s method ( Ranks ) was used for multiple comparisons versus a control group . Results with values of P < 0 . 05 were considered statistically significant . SigmaPlot 11 . 0 software was used to perform all statistical analysis .
Otitis media ( OM ) is the most common cause of deafness in children and is primarily characterised by inflammation of the middle ear . It is the most common cause of surgery in children in the developed world , with many children developing recurrent and chronic forms of OM undergoing tympanostomy tube insertion . There is evidence that a significant genetic component contributes towards the development of recurrent and chronic forms of OM . The mouse has been a powerful tool for identifying the genes involved in chronic OM . In this study we identified and characterised edison , a novel mouse model of chronic OM that shares important features with the chronic disease in humans . A mutation in the Nisch gene causes edison mice to spontaneously develop OM following birth and subsequently develop chronic OM , with an associated hearing loss . Our molecular analysis of the mutation reveals the underlying pathological mechanisms and pathways involved in OM in the edison mouse , involving PAK1 , RAC1 and downstream signalling in LIMK1 and NF-κB pathways . Identification of the edison mutant provides an important genetic disease model of chronic OM and implicates a new gene and genetic pathways involved in predisposition to OM .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "medicine", "and", "health", "sciences", "pathology", "and", "laboratory", "medicine", "ears", "immunology", "animal", "models", "middle", "ear", "developmental", "biology", "otology", "model", "organisms", "organism", "development", "signs", "and", "symptoms", "experimental", "organism", "systems", "skeleton", "lung", "development", "hearing", "disorders", "immunologic", "techniques", "research", "and", "analysis", "methods", "skull", "musculoskeletal", "system", "inflammation", "organogenesis", "mouse", "models", "head", "otorhinolaryngology", "immune", "response", "immunohistochemistry", "techniques", "diagnostic", "medicine", "deafness", "anatomy", "biology", "and", "life", "sciences", "histochemistry", "and", "cytochemistry", "techniques" ]
2017
A mutation in Nischarin causes otitis media via LIMK1 and NF-κB pathways
Invasive lobular breast cancer ( ILC ) accounts for 10–15% of all invasive breast carcinomas . It is generally ER positive ( ER+ ) and often associated with lobular carcinoma in situ ( LCIS ) . Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer , but these studies included predominantly ductal ( IDC ) carcinomas . To identify novel common polymorphisms that predispose to ILC and LCIS , we pooled data from 6 , 023 cases ( 5 , 622 ILC , 401 pure LCIS ) and 34 , 271 controls from 36 studies genotyped using the iCOGS chip . Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases ( 482 ILC , 36 LCIS ) and 1 , 467 controls . These analyses identified a lobular-specific SNP at 7q34 ( rs11977670 , OR ( 95%CI ) for ILC = 1 . 13 ( 1 . 09–1 . 18 ) , P = 6 . 0×10−10; P-het for ILC vs IDC ER+ tumors = 1 . 8×10−4 ) . Of the 75 known breast cancer polymorphisms that were genotyped , 56 were associated with ILC and 15 with LCIS at P<0 . 05 . Two SNPs showed significantly stronger associations for ILC than LCIS ( rs2981579/10q26/FGFR2 , P-het = 0 . 04 and rs889312/5q11/MAP3K1 , P-het = 0 . 03 ) ; and two showed stronger associations for LCIS than ILC ( rs6678914/1q32/LGR6 , P-het = 0 . 001 and rs1752911/6q14 , P-het = 0 . 04 ) . In addition , seven of the 75 known loci showed significant differences between ER+ tumors with IDC and ILC histology , three of these showing stronger associations for ILC ( rs11249433/1p11 , rs2981579/10q26/FGFR2 and rs10995190/10q21/ZNF365 ) and four associated only with IDC ( 5p12/rs10941679; rs2588809/14q24/RAD51L1 , rs6472903/8q21 and rs1550623/2q31/CDCA7 ) . In conclusion , we have identified one novel lobular breast cancer specific predisposition polymorphism at 7q34 , and shown for the first time that common breast cancer polymorphisms predispose to LCIS . We have shown that many of the ER+ breast cancer predisposition loci also predispose to ILC , although there is some heterogeneity between ER+ lobular and ER+ IDC tumors . These data provide evidence for overlapping , but distinct etiological pathways within ER+ breast cancer between morphological subtypes . Invasive lobular breast cancer ( ILC ) accounts for 10–15% of all invasive breast carcinomas and it has distinct etiological , clinical and biological characteristics compared with the more common invasive ductal/no special type carcinoma ( IDC ) [1] . Lobular cancers show stronger associations with the use of hormone replacement therapy ( HRT ) than IDC , [2] and its incidence follows a similar temporal pattern as the use of combined HRT [3] . ILC is characterized by E-cadherin loss and the malignant cells therefore infiltrate the breast stroma in single files with little associated stromal reaction . This makes it difficult to detect these tumors by palpation or mammography , and they are often larger at presentation than IDCs [4] . ILCs are generally of histological grade 2 and estrogen receptor positive ( ER+ ) , with the exception of the pleomorphic subgroup . They typically have a different pattern of metastatic spread to IDCs , tending to infiltrate the peritoneum , ovary and gastrointestinal system . There is some evidence that they are less chemo-sensitive than IDC and that the 10-year survival rate of women with ILC is lower than that of ER+ IDCs [5] , [6] . ILC is often associated with lobular carcinoma in situ ( LCIS ) , a form of non-invasive breast cancer that is difficult to detect clinically and typically found incidentally on biopsy . The increased breast biopsy rate associated with screening mammography has led to an increase in the diagnosis of LCIS . LCIS shares many of the same genetic aberrations as ILC , suggesting that it is a precursor lesion in an analogous manner to ductal carcinoma in situ ( DCIS ) and IDC [7] . Women who have had LCIS are 2 . 4 times more likely to develop invasive breast cancer compared to the general population , with an excess of ILC ( 23–80% of cases ) [8] , [9] . However only 50–70% of invasive cancers associated with LCIS have lobular morphology [10 , unpublished data from GLACIER study] . The remaining cancers have a IDC or mixed ductal-lobular appearance , but again are generally ER+ ( 95% of IDC and mixed ductal-lobular cancers associated with LCIS in the GLACIER study were ER+ ) . Unlike DCIS , LCIS is also a risk factor for developing invasive cancer in the contralateral breast [8] . Genome-wide association studies ( GWAS ) in breast cancer have identified loci that predispose to invasive breast cancer in general , or specifically to ER+ or ER-negative disease [11]–[25] . However , no previous study has focused specifically on lobular carcinomas . Only one common single nucleotide polymorphism ( SNP; rs11249433 at 1p11 . 2 ) has been shown to be more strongly associated with lobular than ductal histology [26] . For the remaining SNPs predisposing to ER+ tumors , it is unclear whether the studies have lacked statistical power to identify differential associations by histology , or whether associations tend to be non-differential by morphology after accounting for ER status . The aim of this study was to identify new breast cancer susceptibility loci specific to lobular carcinoma , and to evaluate the heterogeneity of associations of known loci by morphology . This involved pooling genotyping data from over 6 , 000 cases of lobular carcinoma ( ILC and/or LCIS ) and over 34 , 000 controls genotyped using the iCOGS chip , a custom SNP array that comprises 211 , 155 SNPs enriched at predisposition loci for breast and other cancers [24] . All SNPs reaching genome-wide significance ( P<5×10−8 ) in the meta-analysis were correlated with one of the known breast cancer predisposition loci . In order to identify new loci that predispose to lobular carcinoma , we selected six uncorrelated SNPs ( rs11977670 , rs2121783 , rs2747652 , rs3909680 , rs9948182 , rs7034265 ) that were only weakly correlated ( r2<0 . 25 ) with known loci and that showed the best evidence of association ( P between 5×10−8 and 5×10−5 ) in the overall lobular case-control analysis ( ILC and LCIS ) . These SNPs were genotyped in a Phase II including 516 cases ( 481 ILC , 35 LCIS ) and 1 , 467 controls , all from white European donors ( Figure 1 ) . One of the six SNPs , rs11977670 at 7q34 , reached genome-wide significance in a pooled analysis of phase I and II ILC cases and controls ( OR = 1 . 13 , 95%CI = 1 . 09–1 . 18 , P = 6 . 0×10−10 , Table 1 , Figure 2 ) . rs11977670 showed a similar association with LCIS ( P-het for ILC vs LCIS = 0 . 198 ) , and a very weak or no association with IDC ( OR = 1 . 02 , 95%CI = 1 . 00–1 . 05 , P = 0 . 070; P-het for ILC vs IDC = 1 . 3×10−5 ) , indicating that this is a lobular specific predisposition locus ( Table 2 ) . The risk allele appeared to act in a dominant rather than additive manner: ORAG = 1 . 21 , 95%CI = 1 . 14–1 . 30; ORAA = 1 . 27 , 95%CI = 1 . 17–1 . 38; P for departure from log-additivity = 0 . 009; Table S3 . rs11977670 was not significantly associated with age at onset of ILC ( Ptrend = 0 . 16 ) and risk alleles were not significantly over-represented in cases with a positive family history ( FH ) ( P = 0 . 90 , FH+ vs FH− ) . None of the other 5 SNPs genotyped were associated with lobular breast cancer at a genome-wide significance level , with the strongest association being for rs2121783 at 3p13 ( OR = 1 . 11 , 95%CI = 1 . 07–1 . 15 , P = 4 . 5×10−7; Table S4 ) . rs11977670 at 7q34 ( position:139942304 , GRCh Build 37 ) is intergenic , 65 kb from the nearest gene , JHDM1D , a histone demethylase and 500 kb from BRAF , a gene frequently mutated in melanoma . It is also in close proximity to a predicted novel U1 spliceosomal RNA that contains two U1 specific promoter motifs ( Figure S2 ) . ENCODE data on normal human mammary epithelial cells ( HMEC ) , and breast carcinoma ( MCF-7 ) , were used to establish chromatin states in the region and showed that rs11977670 lies in region marked by H3K27 acetylation , Figure S3 . Using expression data from the Cancer Genome Atlas Network ( TCGA database ) [27] , we assessed expression of the nine genes within 0 . 5 Mb of rs11977670 by breast cancer subtype ( ER+ ILC , 40 cases; ER+ IDC , 341 cases; and ER-negative IDC , 108 cases; Figure S4 ) . Three genes showed differential expression in ER+ ILC compared to ER+ IDC ( BRAF , P = 0 . 006; NDUFB2 , P = 0 . 02 , SLC37A3 , P = 0 . 05 ) , however none reached statistical significance when correcting for multiple testing . Another two genes , JHDM1D and ADCK2 , showed a difference in expression between ER-negative and ER+ cancers , but this was not lobular-specific . To further investigate which genes may be influenced by SNPs tagged by rs11977670 , germline genotype data for rs13225058 ( A/G ) , a surrogate for rs11977670 ( G/A ) ( r2 = 0 . 79 ) was taken from the TCGA database ( SNP6 . 0 Affymetrix array ) and compared to expression of these genes , correcting for copy number variation , in 335 ER+ primary breast cancers where both genotype and expression data was available . A significant difference , after correcting for multiple testing , was found in expression between the AA and GG genotype for two genes JHDM1D ( P = 0 . 0005 ) and SLC37A3 ( P = 0 . 004 ) , Figure S5a . Confining the analysis to the 36 ILC cases with data in TCGA showed no significant genotype specific expression due small numbers although there was the suggestion of a trend towards overexpression with the GG genotype ( 2 cases ) , Figure S5b . 48 of the cases also had expression data on adjacent normal breast tissue , but due to the small numbers no significant genotype specific expression changes were detected , Figure S6 . There was no evidence of copy number variation around rs11977670 and no evidence of an excess of somatic mutations in JHDM1D , SLC37A3 or BRAF in ILC . Most ( 56 of 75 ) known common breast cancer susceptibility loci were associated with ILC at P<0 . 05 with the effect in the same direction as previously reported ( Table S5 ) , and 13 of these reached genome-wide significance ( P<5×10−8 , Table 3 ) . The strongest associations were with SNPs close to FGFR2 ( rs2981579 , OR = 1 . 38 , P = 5 . 1×10−52 ) , TOX3 ( rs3803662 , OR = 1 . 33 , P = 1 . 1×10−35 ) , at 1p11 . 2 ( rs11249433 , OR = 1 . 25 , P = 2 . 7×10−25 ) and 11q13 . 3 ( rs554219 , OR = 1 . 33 , P = 1 . 6×10−22 ) . All 13 loci had previously been shown to be associated with ER+ breast cancer and one locus , rs11249433 ( 1p11 . 2 ) , with lobular histology in subgroup analysis . Of the remaining 19 SNPs with P≥0 . 05 , 18 had ORs in the same direction as previously reported for overall breast cancer ( Sign test P = 0 . 0001 ) , suggesting that these SNPs are also likely to predispose to LCIS . Only one of the seven ER-negative specific loci on the iCOGS array showed a significant association with ILC ( rs12710696 , P = 0 . 037 ) . In case-only analyses , no SNP showed an association with family history of breast cancer or young age at onset of ILC . For the 75 known breast cancer susceptibility loci , case-control analysis for the 401 cases of pure LCIS ( without invasion ) and 24 , 045 controls , revealed 15 out of 75 SNPs associated with LCIS at P<0 . 05 ( Table 3 ) . The strongest associations were for rs865686 ( 9q31 . 2 , P = 2 . 2×10−5 ) ; rs3803662 ( TOX3 , P = 1 . 2×10−4 ) , c11_pos69088342/rs75915166 ( 11q13 . 3 , P = 7 . 8×10−4 ) and rs1243482 ( MLLT10 , 10p12 . 31 , P = 7 . 8×10−4 ) that is partially correlated ( r2 = 0 . 69 ) with rs7072776 , a recently identified ER+ breast cancer predisposition locus that showed a weaker association with LCIS ( OR = 1 . 17 , 95%CI = 1 . 00–1 . 36 , P = 0 . 05; Table S5 ) . Forty-seven of the remaining 60 SNPs at P>0 . 05 had ORs in the same direction as for ILC . This is greater than one would expect by chance ( Sign Test P = 1 . 2×10−5 ) suggesting many of these SNPs predispose to LCIS , but the study did not have enough power to detect these associations with the small sample size . A global test in case-only analysis ( ILC vs LCIS ) indicated no significant differences in associations of the 75 SNPs between LCIS and ILC ( likelihood ratio test ( 75 df ) = 0 . 438 ) . However , individual SNP analyses suggested some differences . Two loci showed stronger associations with ILC than pure LCIS: rs2981579 , FGFR2 ( P-het = 0 . 02 ) ; and rs889312 , 5q11 . 2 ( P-het = 0 . 03 ) . Case-only analysis also suggested that two ER-negative specific SNPs [23] , [25] were more strongly associated with LCIS than ILC: rs6678914 , 1q32 . 1 ( P-het = 0 . 0007 ) and rs17529111 , 6q14 . 1 ( P-het = 0 . 04 ) Table 3 . The remaining SNPs showed no significant heterogeneity between ILC and LCIS . In order to identify lobular specific SNPs , we performed a case-only analysis of 3 , 201 ER+ ILC cases and 15 , 024 ER+ IDC cases from BCAC . Analysis was confined to ER+ cases since 94% of ILC cases were ER+ ( compared to 78% of IDC in BCAC ) . A global test indicated significant differences in SNP associations between ILC and IDC ( likelihood ratio test ( 75 df ) P = 5 . 9×10−6 ) . The SNP showing the largest difference between ILC and IDC was rs11249433 at chr 1p11 . 2 ( P-het = 2 . 7×10−8; Table 4 ) , a SNP previously associated with lobular histology . At P<0 . 05 , a further two loci were associated more strongly with ILC than IDC: rs2981579 , FGFR2 ( P-het = 5 . 3×10−3 ) and rs10995190 , 10q21 . 2 ( P-het = 0 . 002 ) . This analysis also identified four IDC-specific SNPs at P<0 . 05: rs10941679 , 5p12 ( P-het = 1 . 5×10−4 ) ; rs2588809 , RAD51L1 ( P-het = 0 . 001 ) ; rs6472903 , 8q21 . 11 ( P-het = 0 . 004 ) ; rs1550623 , CDCA7 ( P-het = 0 . 031 ) Table S6 . Case-control analysis of 690 mixed ductal–lobular carcinomas revealed 25 loci that showed an association with these mixed cancers at P<0 . 05 . The top hits were at FGFR2 ( rs2981579 , OR = 1 . 37 , P = 1 . 6×10−7 ) , rs941764 ( CCDC88C , OR = 1 . 25 , P = 3 . 6×10−4 ) and rs10995190 ( ZNF365 , OR = 0 . 74 , P = 3 . 9×10−4 ) . The case-only analysis above showed that two of these SNPs are more strongly associated with ILC than IDC ( rs2981579 , rs10995190 ) . rs941764 showed no association with ILC and only weak association with ER+ IDC , Table S6 . Our analyses of a total of 6 , 539 lobular cancers ( including 436 cases of pure LCIS ) and 35 , 710 controls has identified for the first time a lobular-specific SNP , rs11977670 ( JHDM1D; OR = 1 . 13 P = 4 . 2×10−10 , that showed little evidence of association with IDC ( P = 0 . 07 ) or DCIS ( P = 0 . 23 ) . Identification of the target of this association will require fine mapping of the region , followed by functional assays to determine which gene ( s ) the key SNPs regulate . The preliminary in silico functional analysis suggests that SNPs in this region may be influencing expression of JHDM1D ( a histone demethylase ) and SLC37A3 ( a sugar-phosphate exchanger ) . For JHDM1D this appears to be a recessive effect , in contrast to the susceptibility data , which suggests a dominant effect . There are little data on the role of these genes in cancer . There is some evidence that increased expression of JHDM1D can suppress tumor growth by regulating angiogenesis [28] and decreased expression promotes invasiveness , which is contrary to what one would expect from the risk data [29] . This inconsistency does shed some doubt on these results and further analysis of the region is required before any firm conclusion can be made . Studies of syndecan-1-deficient breast cancer cells , which show increased cell motility and invasiveness , demonstrate decreased expression of both JHDM1D and E-cadherin [29] , suggesting the two genes may interact . Somatic mutations in CDH1 ( E-Cadherin ) are frequent in ILC and rare germline frameshift mutations in CDH1 have been described in ILC , particularly in families with hereditary diffuse gastric cancer ( HDGC ) , but also in cases of familial ILC with no HDGC [30] , [31] . However , none of the 56 SNPs in CDH1 that were typed on the iCOGS chip showed any association with lobular cancer at P<0 . 05 . It should also be noted that this study is not a true genome wide association study for lobular breast cancer as the SNPs on the iCOGS chips were chosen on the basis of some prior evidence of association with breast cancer as a whole . Although ILC would have been a small proportion of the samples in the discovery sets for these SNPs it is possible that other lobular specific loci exist that have not been included on the iCOGS chip . This is particularly true for LCIS , which would only have been included in the discovery set as a parallel phenotype when associated with invasive disease . 75 of the known common breast cancer susceptibility loci were assessed for association with ILC and LCIS . As cases of ILC were included in the discovery sets that generated these susceptibility loci and lobular breast cancer is generally ER+ ( 94% of the ILC cases in this study were ER+ ) with the majority of ILCs classified as luminal tumors [32] , it is not surprising that the majority of SNPs that we found to be associated with ILC were known to also predispose to ER+ breast cancer . However , some loci were only associated with ER+ IDC and not with ILC , particularly rs10941679 at 5p12 , previously shown to predispose more strongly to ER-positive , lower-grade cancers [33] , P-het = 2 . 7×10−8 . Others showed a much stronger association with ILC than IDC , particularly rs11249433 at 1p11 . 2 , as previously described [26] . These data suggest specific etiological pathways for the development of different histological subtypes of breast cancer , in addition to common pathways that predispose to multiple tumor subtypes . Despite the small number of pure LCIS cases without invasive disease , our analyses have shown for the first time that many of the SNPs that predispose to ILC also predispose to LCIS . Although only 15 of the known breast cancer SNPs were associated with LCIS risk at P<0 . 05 , 47 of the remaining 60 SNPs at P>0 . 05 had ORs in the same direction as for ILC ( Sign Test P = 1 . 2×10−5 ) suggesting that many more SNPs are likely to be associated with pure LCIS but did not reach statistical significance individually because of the relatively few LCIS cases without associated ILC in our sample set . This is not unexpected if LCIS is an intermediate phenotype for ILC . However , a small number of SNPs had differential effects on LCIS or ILC risk . Specifically , rs6678914 at 1q32 . 1 ( LGR6 ) , known to be an ER-negative specific SNP [25] , that appeared to be associated with LCIS but not ILC ( P-het = 0 . 0007 ) , and rs17529111 at 6q14 preferentially associated with ER-negative tumors [23] that had a stronger association with LCIS than ILC ( P-het = 0 . 04 ) . We also identified SNPs in FGFR2 and at 5q11 . 2 ( MAP3K1 ) that appear only to predispose to ILC , but have little effect on LCIS suggesting that SNPs affect different parts of the lobular carcinoma pathway . These findings are surprising and as based on small numbers need confirmation in future studies . Some of the SNPs associated with both ILC and LCIS showed a stronger effect size in LCIS compared to ILC ( for example SNPs at TOX3 , 9q31 . 2 , 11q13 . 3 , ZNF365 and MLLT10 ) . It is possible that the SNPs that showed an association with both LCIS and ILC predispose to the development of LCIS rather than ILC , and that the effect size is smaller in ILC as not all cases of LCIS will become invasive cancer . SNPs that predispose strongly to LCIS were also associated with ER+ IDCs but again with stronger effect sizes in LCIS , consistent with the fact that 30–40% of invasive tumors associated with LCIS will not be ILC but will be IDC , mixed ductal-lobular or other morphology . One SNP , rs1243182 ( MLLT10 ) , that showed a strong association with LCIS ( LCIS: P = 7 . 8×10−4 , OR = 1 . 29; ILC: P = 6 . 1×10−9 , OR = 1 . 14; ILC+LCIS: P = 3×10−10 , OR = 1 . 15 , IDC: P = 1 . 4×10−5 , OR = 1 . 07 , is partially correlated ( r2 = 0 . 69 ) with rs7072776 , a recently identified ER+ breast cancer predisposition locus , which showed no association with LCIS in this study . It is also strongly correlated with rs1243180 ( r2 = 0 . 80 ) , an ovarian cancer predisposition variant [34] and rs11012732 ( r2 = 0 . 57 ) , which predisposes to meningioma [35] . The ovarian SNP , rs1243180 , also showed a strong association with lobular cancer ( ILC+LCIS: P = 5 . 54×10−10; OR = 1 . 13 ) . Conditional analysis confirmed that this was not independent of rs1243182 . rs11012732 was not genotyped on the iCOGS chip . The increased risk of ovarian carcinoma after breast cancer is well documented in epidemiological studies [36] . Of note , there are also reports suggesting an association between breast cancer and meningioma [37] . In conclusion , we have identified a novel lobular-specific predisposition SNP at 7q34 close to JHDM1D that does not appear to be associated with IDC . Most known breast cancer predisposition SNPs also predispose to ILC , with some differential effects between ILC and IDC . In addition , many SNPs predisposing to invasive cancer are also likely to increase the risk for LCIS . Overall , our analyses show that genetic predisposition to IDC and lobular lesions ( both ILC and LCIS ) overlap to a large extent , but there are important differences that are likely to provide insights into the biology of lobular breast tumors . All studies were performed with ethical committee approval , Table S7 , and subjects participated in the studies after providing informed consent . In order to establish the SNP's functional role , a window of 10 kb both up and downstream was formed around the marker and pairwise r2 values calculated using 1000 genome CEU population data . Three SNPs were identified as being in LD ( r2>0 . 5 ) with rs11977670 and were compared to next generation sequence technologies to elucidate the overlap between chromatin states ( ENCODE Project ) . Two cell lines , normal human mammary epithelial ( HMEC ) , and breast carcinoma ( MCF-7 ) , were used to establish these chromatin states , i . e . active or engaged enhancers ( H3K27ac ) , nucleosome-depleted regions ( DNase I and FAIRE ) , and RNA polymerase linked regions ( Pol II ) . Expression data from the Cancer Genome Atlas Network for each gene within a 1 Mb window of rs11977670 was analyzed looking for differential expression in each breast cancer subtype ( ER+ ILC , 40 cases; ER+ IDC , 341 cases; and ER-negative IDC , 108 cases ) . Allele data for surrogate SNP rs13225058 was obtained for all ER+ cases from TCGA . These 335 cases were used to produce genotype specific gene expression data in R . Differences in gene expression between the three genotypes were tested for using one-way-anova , verified by t-test and visually by boxplot . Linear regression was performed across all three genotypes using copy number variation as a co-variate . Level 3 copy number variation data ( hg19 build ) was obtained from the TCGA data portal .
Invasive lobular breast cancer ( ILC ) accounts for 10–15% of invasive breast cancer and is generally ER positive ( ER+ ) . To date , none of the genome-wide association studies that have identified loci that predispose to breast cancer in general or to ER+ or ER-negative breast cancer have focused on lobular breast cancer . In this lobular breast cancer study we identified a new variant that appears to be specific to this morphological subtype . We also ascertained which of the known variants predisposes specifically to lobular breast cancer and show for the first time that some of these loci are also associated with lobular carcinoma in situ , a non-obligate precursor of breast cancer and also a risk factor for contralateral breast cancer . Our study shows that the genetic pathways of invasive lobular cancer and ER+ ductal carcinoma mostly overlap , but there are important differences that are likely to provide insights into the biology of lobular breast tumors .
[ "Abstract", "Introduction", "Results", "Discussion", "Methods" ]
[ "genetics", "biology", "and", "life", "sciences", "human", "genetics" ]
2014
Genetic Predisposition to In Situ and Invasive Lobular Carcinoma of the Breast
Eukaryotic cells must coordinate contraction of the actomyosin ring at the division site together with ingression of the plasma membrane and remodelling of the extracellular matrix ( ECM ) to support cytokinesis , but the underlying mechanisms are still poorly understood . In eukaryotes , glycosyltransferases that synthesise ECM polysaccharides are emerging as key factors during cytokinesis . The budding yeast chitin synthase Chs2 makes the primary septum , a special layer of the ECM , which is an essential process during cell division . Here we isolated a group of actomyosin ring components that form complexes together with Chs2 at the cleavage site at the end of the cell cycle , which we named ‘ingression progression complexes’ ( IPCs ) . In addition to type II myosin , the IQGAP protein Iqg1 and Chs2 , IPCs contain the F-BAR protein Hof1 , and the cytokinesis regulators Inn1 and Cyk3 . We describe the molecular mechanism by which chitin synthase is activated by direct association of the C2 domain of Inn1 , and the transglutaminase-like domain of Cyk3 , with the catalytic domain of Chs2 . We used an experimental system to find a previously unanticipated role for the C-terminus of Inn1 in preventing the untimely activation of Chs2 at the cleavage site until Cyk3 releases the block on Chs2 activity during late mitosis . These findings support a model for the co-ordinated regulation of cell division in budding yeast , in which IPCs play a central role . Eukaryotic cells divide their cytoplasm at the end of mitosis in a highly regulated process called cytokinesis , which safeguards inheritance of the genome and organelles by the two daughter cells . The failure of cell division results in the formation of genetically unstable tetraploid cells , which may give rise to cancer [1] [2] . The successful completion of cytokinesis requires the precise coordination between an actomyosin-based contractile ring , which drives the ingression of the plasma membrane , and the remodelling of the extracellular matrix ( ECM ) [3] [4] [5] [6] . Yeast cells are surrounded by rigid ECM known as the cell wall , which provides the structural support and protection necessary to survive as unicellular organisms . The ECM is composed of a collection of biochemically distinct components , among which polysaccharides are emerging as key factors during cytokinesis , as shown by the failure in cytokinesis caused by defects associated with their synthesis in evolutionary distant organisms such as the budding yeast Saccharomyces cerevisiae [7] [8] , the fission yeast Schizosaccharomyces pombe [9] [10] [11] , the nematode Caenorhabditis elegans [12] and the mouse [13] . In these four examples , the impairment of a glycosyltransferase determines clear cell division defects . In budding yeast , it is the glycosyltransferase chitin synthase II , a transmembrane protein encoded by CHS2 , which centripetally produces a distinct layer of chitin between mother and daughter cells during cytokinesis , called the primary septum , which is essential for life [6] . Chitin is a polymer of N-acetylglucosamine ( Glc-NAc ) , which is synthesised from an activated nucleotide substrate UDP-N-acetylglucosamine ( UDP-GlcNAc ) , and chitin chains are subsequently secreted outside the cells , assembled into microfibrils and organised in the extracellular matrix [14] [15] . In yeast cells , primary septum formation is tightly coupled to actomyosin ring contraction and ingression of the plasma membrane at the cleavage site [6] . In fact , defects associated with one of those processes perturb the others , although the underlying mechanisms linking them together remain unclear [16] [17] [18] [8] [19] [20] . The primary septum , which is later flanked by secondary septa , is finally digested to allow separation of the two daughter cells [21] . The core components and mechanisms of cytokinesis are largely conserved from yeast to humans , which makes the budding yeast cells an attractive model for studying the process of eukaryotic cytokinesis and for identifying how cells coordinate such processes [22] [5] [6] . Successful cytokinesis requires mechanisms that timely and effectively orchestrate the completion of the different steps along the cell cycle . First , cells need to assemble a contractile ring containing type II myosin and many other factors at the cleavage site , in a sequential and highly regulated process . At the early stages of the cell cycle , the type II myosin Myo1 forms a ring at the place that will later become the division site [16] [23] . Myo1 plays a scaffolding role in the assembly of the cytokinetic machinery [24] and associates with other factors during mitosis . These include actin-nucleating and bundling factors such as formins and the IQGAP protein Iqg1 , leading to the assembly of a functional contractile actomyosin ring at the end of anaphase [25] [26] [22] [5] . Iqg1 contains an amino terminal calponin homology domain , which is thought to crosslink actin filaments , followed by IQ repeats that interact with Hof1 [27] . Interestingly , Hof1 interacts directly with type II myosin Myo1 and localises at the cleavage site in a complex manner , which depends upon Myo1 [28] [29] . In addition , it has recently been described that Hof1 shares a role with Rvs167 in actin ring assembly and Iqg1 recruitment to the bud-neck [30] . Hof1 contains an F-BAR domain in its N-terminal region and an SH3 domain in its C-terminus , both of which have been shown to be important for dynamics and function of the Hof1 protein [28] [29] . The SH3 domain of Hof1 is known to interact with proline-rich motifs ( PXXP ) located at the C-terminus of Inn1 [19] [31] [30] . Cells depleted for Inn1 still allow contraction of the actomyosin ring , but membrane ingression fails and the primary septum is not formed , despite the presence of Chs2 [19] [31] . In addition to Hof1 , Inn1 interacts with Iqg1 [19] and with Cyk3 , through the SH3 domain of Cyk3 located at its N-terminus [32] [31] [33] [30] . Furthermore , Hof1 SH3 binds to a proline-rich stretch of Cyk3 [34] . Taken together , it seems that multiple actomyosin components share binary interactions , but until now there has been no evidence that they all interact together to form large complexes in cells , in order to perform coordinated functions during cytokinesis . Following full assembly of the contractile ring , primary septum formation occurs when cells have segregated their chromosomes and actomyosin ring contraction initiates . The expression , localisation and enzymatic activity of chitin synthase Chs2 are temporally and spatially regulated [35] [36] [8] [37] [38] [39] . Recent findings suggest that Hof1 , Inn1 and Cyk3 regulate chitin synthase during cytokinesis in budding yeast , although the molecular mechanism is poorly understood [19] [31] [32] [40] [20] . Hof1 interacts directly with Chs2 and stabilises the chitin synthase at the cleavage site [29] . It also appears that Cyk3 could regulate Chs2 activity , since an increased dosage of Cyk3 stimulates Chs2-dependent chitin synthesis and the formation of primary-septum-like structures at the bud neck [41] [42] . Moreover , we found genetic evidence that enhanced chitin synthase activity associated with a hypermorphic allele of CHS2 , CHS2-V377I , suppresses the defects associated with an inactive form of the C2 domain of Inn1 ( first 134 amino acids of Inn1 ) and deficiencies associated with the lack of Cyk3 in budding yeast cells [20] . Here , we have isolated complexes containing the actomyosin ring components Myo1 , Iqg1 , Hof1 , Inn1 and Cyk3 all together with chitin synthase Chs2 from cells undergoing cytokinesis , which we named ‘ingression progression complexes’ or IPCs . We show that IPCs are assembled at the end of the cell cycle and we propose that IPCs coordinate contraction of the actomyosin ring , plasma membrane ingression and primary septum deposition in budding yeast . We find that IPC components co-operate to recruit Chs2 to the division site . Moreover , we provide evidence that Inn1 and Cyk3 interact directly with the catalytic domain of Chs2 . Our data indicate that the C2 domain of Inn1 and the transglutaminase-like domain of Cyk3 increase the chitin synthase activity associated with Chs2 . We used an experimental system to find a previously unanticipated role for the C-terminus of Inn1 in preventing the untimely activation of Chs2 at the cleavage site until Cyk3 releases the block on Chs2 activity , when cells reach the end of the cell cycle We previously found that Inn1 co-purified with Chs2 when studying cells that had been released into mitosis from a G2-M block to allow them to undergo cytokinesis synchronously [20] . To study further the interaction between Inn1 and Chs2 , we used several approaches . First , we used the yeast two-hybrid assay to show that a fragment of Chs2 that contains its catalytic domain ( Chs2-215-629 ) was able to interact with full-length Inn1 ( Fig 1A ) . We then determined whether these factors were able to interact directly in an extract of E . coli cells . We generated an E . coli strain that expressed 6His-tagged Inn1 and , in parallel , another strain that expressed a truncated version of Chs2 fused to Streptag ( Streptag-Chs2-215-629 ) , as indicated in S1A Fig . We then mixed the cultures and generated a single cell extract containing Inn1 , Chs2 and all the native E . coli proteins ( S1A Fig ) . We initially purified the truncated version of Chs2 from the cell extracts , and subsequently isolated 6His-Inn1 from the purified material . In this way , we found that Chs2 co-purified specifically with Inn1 ( Fig 1B ) . Note that both Inn1 and Chs2-215-629 migrate similarly in SDS-PAGE gels , and so their presence was confirmed by mass spectrometry and immunoblotting analysis ( Fig 1Bii and 1Biii ) . Following the same purification procedure described above , we found that a fragment of Chs2 that contains its CDK-regulated N-terminal domain together with its catalytic domain ( Chs2-1-629 , which only lacks the transmembrane domain ) co-purified specifically with Inn1 ( Fig 1C ) . Furthermore , we determined that formation of Chs2-Inn1 complex was not abolished by the Inn1-K31A mutation , which disrupts the function of the Inn1 C2 domain , or by a hypermorphic mutation in the catalytic domain of Chs2 ( Chs2-V377I ) , which enhances its activity in vitro ( Fig 1D ) . Since it has been shown that inactivation of the C2 domain of Inn1 can be rescued by specific mutations in the catalytic domain of Chs2 that increase its activity [20] , we tested whether the C2 domain of Inn1 directly associates with and regulates chitin synthase Chs2 in vivo . A yeast strain was generated in which either wild-type Inn1 or the Inn1 C2 domain were fused to the tandem affinity purification ( TAP ) tag and expressed under the control of the INN1 promoter . INN1-TAP , C2-TAP and control strains were grown at 24°C , synchronised in G1 phase of the cell cycle by the addition of mating pheromone and cells were then released from G1 arrest . The resultant fusion proteins were isolated from cells going through cytokinesis synchronously 105 minutes after the release from G1 block , when localisation of Inn1 and Chs2 at the site of division peaks . We found that Chs2 co-purified specifically with the C2 domain of Inn1 , equivalent to full-length Inn1 ( Fig 2Ai ) . To test whether the C2 domain of Inn1 could interact directly with Chs2 , we generated E . coli strains that produced 6His-tagged-Inn1-C2 and Strep-tag-Chs2-215-629 and proceeded as above . We found that 6His-C2 co-purified over two purification steps with Strep-tag-Chs2-215-629 ( Fig 2Aii ) , indicating that the Inn1 C2 domain interacts directly with a fragment of Chs2 that contains its catalytic domain . In addition , we determined that interaction between Chs2 and the Inn1 C2 domain was not disrupted by Inn1-K31A mutation ( Fig 2Aiii ) . To investigate whether the Inn1 C2 could induce chitin synthase activity in vivo , we monitored the chitin level at the division site by calcofluor staining [43] in cells that overexpressed the C2 domain and lacked Chs3 ( studies focused on Chs2 activity require the use of chs3Δ cells , because Chs3 is responsible for the synthesis of the vast majority of the chitin content in budding yeast cells [44] ) . Asynchronous cultures were grown at 24°C and cells were synchronised in G1 phase with mating pheromone . Subsequently , we released cells from G1 block into medium containing calcofluor to stain primary septa and galactose to allow overexpression of the C2 domain . Progression through cytokinesis and localisation of Chs2 at the site of division were similar in both control and GAL-C2 cells ( S1B Fig ) . To observe calcofluor-stained chitin in cells completing mitosis , cells were collected 135 minutes after release from G1 block ( Fig 2B ) when the percentage of cells containing primary septa peaks . We found that the signal intensity associated with calcofluor-stained chitin at the division site was higher in cells overexpressing C2 as compared to control cells ( Fig 2B ) , indicating that the C2 domain of Inn1 is able to induce septum formation . To test whether the C2 of Inn1 positively regulates the chitin synthase Chs2 , two different in vitro approaches were used . First , two chs3Δ yeast strains were generated to overexpress either CHS2 or CHS2 together with the C2 domain . We grew control , GAL-CHS2 and GAL-CHS2 GAL-C2 strains asynchronously in the presence of raffinose and then switched to medium containing galactose to induce the expression of Chs2 and the C2 domain ( Fig 2Ci ) . After two hours we isolated membranes to perform a chitin assay , as previously reported [45] [20] . We found that the Inn1 C2 domain had an effect on Chs2 activity , since overexpression of C2 at the same time as Chs2 caused a 30% increase in the percentage of active chitin synthase ( Fig 2Cii , compare CHS2 with CHS2 C2 ) . Consistently , we observed that cells overproducing the C2 domain and Chs2 induced thicker primary septum deposition ( Fig 2Ciii and 2Civ ) . Second , we fused the Inn1 C2 domain to Chs2 and measured the enzymatic activity associated with the C2-Chs2 fusion protein . We have previously shown that C2-CHS2 fusion fully supports cytokinesis in inn1Δ cells [20] . We grew cells asynchronously , isolated membranes and performed an in vitro chitin assay . Subsequently , we calculated the percentage of active chitin synthase associated with C2-Chs2 and found that it increased 3-fold in comparison with Chs2 activity in control cells ( Fig 2D , compare 1–2 ) . This increase was significantly reduced when an inactive version of the C2 ( C2-K31A ) was fused to Chs2 ( Fig 2D , compare 1–3 ) . Taken together , these findings show that the Inn1 C2 domain directly binds to and regulates the catalytic domain of Chs2 , which is required to form the primary septum during cytokinesis . Interestingly , the percentage of active chitin synthase associated with Chs2-V377I , increased 4 . 3 fold when compared with control Chs2 under the same conditions described above ( Fig 2D ( i ) , compare 1–4 ) while fusion proteins expression levels were similar ( Fig 2D ( ii ) ) . This suggests that there might be other factors , in addition to the Inn1 C2 , that contribute to Chs2 activation ( Fig 2D , compare the difference between 1–2 , 1–4 and 2–4 ) . To understand how cells control the activity of Chs2 at the division site during cytokinesis , we aimed to isolate Inn1-Chs2 complexes specifically and subsequently identify their protein composition by mass spectrometry . We grew a five-litres culture of INN1-TAP CHS2-9MYC cells , together with INN1 CHS2-9MYC control cells that expressed the TAP tag under the control of the TET promoter . Both cultures were grown at 24°C , synchronised in G1 phase of the cell cycle by the addition of mating pheromone and cells were then released from G1 arrest for 105 minutes to focus on the time when the localisation of Inn1 and Chs2 at the cleavage site peaks . Initially , after making cell extracts , Inn1-TAP ( or TAP tag in the control ) were pulled down and subsequently Chs2-9MYC was immunoprecipitated from the material generated in the first step . This method facilitated the specific enrichment of Inn1-Chs2 complexes , as well as any proteins interacting with them at this point during cell division [46] . First , we confirmed by immunoblotting the presence of both Inn1 and Chs2 in our final purified material ( Fig 3Ai ) . To identify in an unbiased fashion other factors that might regulate Chs2 activity , both purified samples were run in polyacrylamide gels and the lanes were cut into 10 bands and analysed by mass spectrometry ( Fig 3Aii ) . A specific set of proteins that interact with Inn1-Chs2 complexes and are known core components of the budding yeast actomyosin ring was found: the sole and essential IQGAP protein Iqg1; the F-BAR domain containing protein Hof1; the type II myosin , Myo1 and Cyk3 protein , which contains a transglutaminase-like domain and an SH3 domain ( Fig 3Aii ) . The interactions were subsequently confirmed by immunoblotting ( Fig 3Aiii ) , using antibodies we raised against Cyk3 ( S1C Fig ) and Inn1 [20] . In addition , to test whether this set of proteins could be isolated immunoprecipitating another component of that newly identified complex , we pulled down protein Iqg1 fused to HA from cells going through cytokinesis synchronously , as explained above . Then , we used antibodies against Chs2 that we raised ( S1D Fig ) , together with antibodies against Inn1 and Cyk3 , to confirm that Iqg1 indeed interacted with proteins isolated in our systematic analysis ( Fig 3B ) , in agreement with past observations of binary interactions amongst these factors [25] [19] [31] [32] [33] [34] [29] [30] [27] . These findings suggest that Inn1 , Chs2 , Iqg1 , Hof1 , Myo1 and Cyk3 interact during cytokinesis , to form complexes that coordinate actomyosin ring contraction , plasma membrane ingression and primary septum formation . We propose to name these complexes ‘ingression progression complexes’ or IPCs . To determine when during the cell cycle IPC components interact , the type II myosin Myo1 was immunoprecipitated from extracts of cells that had been arrested in G1 phase , S phase or were going through cytokinesis synchronously ( Fig 3C ) . We found that Myo1 only interacted with IPC components at the end of the cell cycle , which is consistent with a key role of IPCs during cytokinesis ( Fig 3C ) . Amongst the components of the IPCs , the Cyk3 protein is poorly characterised and might play a direct role in the regulation of Chs2 chitin synthase activity associated with Chs2 , although the molecular details are unclear . Genetic studies have shown that increased doses of Cyk3 complemented defects associated with cytokinesis mutants myo1 , iqg1 , inn1 and hof1 [47] [31] [32] [42] but failed to rescue chs2Δ cells ( S2 Fig ) [42] . In addition , the overexpression of Cyk3 stimulated chitin synthesis at the division site ( Fig 4B ) [41] [42] and a hypermorphic allele of CHS2 rescued defects produced by the lack of the Cyk3 protein [20] . Thus , we aimed to explore further the role of the Cyk3 subunit of IPCs in the regulation of the Chs2 chitin synthase . Cyk3 contains two domains , an N-terminal SH3 domain and a transglutaminase-like domain located in the second half of the protein . We initially used the yeast two-hybrid assay to determine whether the Cyk3 SH3 interacted with a truncated version of Chs2 lacking the transmembrane domain ( Chs2-1-629; S3 Fig ) . We found that the Cyk3 SH3 domain did not interact with chitin synthase Chs2 , although it did interact with the C-terminus of Inn1 ( S3 Fig ) [31] [32] [33] [30] . The catalytic core of the active transglutaminase domains has three conserved active residues that form the catalytic triad: cysteine , histidine , and aspartic acid . The catalytic triad of the fungal Cyk3 proteins is unusual since it contains the conserved histidine and aspartic acid , but it lacks the conserved catalytic cysteine ( S6A Fig ) [48] [49] . To examine the role of the transglutaminase-like domain of Cyk3 in more detail , the conserved histidine and aspartic acid , which are well conserved in orthologues of Cyk3 in other eukaryotic species , were mutated to alanines ( H563A and D578A; hereafter called cyk3-2A ) ( Figs 4 and S6A ) . To analyse the function of the Cyk3 transglutaminase-like domain in budding yeast we used cells in which the C2 domain of Inn1 was fused to the actomyosin ring component Hof1 , since we have previously reported that CYK3 becomes essential in these cells [20] . C2-HOF1 strain grew as rapidly as a wild-type strain and did not display any detectable defects in cell division [19] . The meiotic progeny of C2-HOF1 cyk3-2A diploid cells was then analysed by tetrad analysis . We found that cyk3-2A was synthetically lethal with C2-HOF1 , which suggested that the conserved residues H563 and D578 in the tranglutaminase-like domain are important for maintaining the function of Cyk3 ( Fig 4A ) . Overexpression of Cyk3 stimulated chitin synthesis at the division site ( Fig 4B ) [41] [42] and seemed to have no effects on cell cycle progression and Chs2 localisation ( S4 Fig ) . To investigate whether the transglutaminase-like domain mutant cyk3-2A conserved the ability to increase the primary septum formation , chs3Δ strains overexpressing CYK3 or cyk3-2A , together with control were grown at 24°C and the cells were synchronised in G1 phase . They were then released from G1 arrest into medium containing calcofluor to stain the primary septa and galactose to allow the overexpression of either Cyk3 or Cyk3-2A . Cells were collected 135 minutes after the release when the percentage of cells containing primary septa peaks . Subsequently , samples were used to examine the presence of primary septum at the division site by fluorescence microscopy . Cells overexpressing Cyk3-2A contained similar levels of primary septum as control cells ( Fig 4B ) unlike cells overproducing Cyk3 , whose primary septa were 3 fold more intense ( Fig 4B ) . Taken together , these observations suggest that the transglutaminase-like domain of Cyk3 is important to stimulate chitin synthesis during cell division in budding yeast . To explore the possibility that Cyk3 might interact with Chs2 and therefore could be important for its chitin synthase activity , we performed a yeast two-hybrid assay with two different fragments that contained the transglutaminase-like domain of Cyk3 ( Cyk3-1-594 and Cyk3-475-885 ) against the Chs2 truncation mentioned above that includes its catalytic domain ( Chs2-215-629 ) ( Fig 5Ai ) or the fragment of Chs2 that only lacks the transmembrane domain ( Chs2-1-629 ) ( S5 Fig ) . We determined that both Cyk3 truncations were clearly able to interact with Chs2 ( Fig 5Ai; S5 Fig ) . To study whether the transglutaminase-like domain mutant cyk3-2A conserved the ability to interact with Chs2 , we carried out a yeast two-hybrid assay as above ( Fig 5Aii; S5 Fig ) . We found that interaction was not abolished by mutations in the transglutaminase-like domain of Cyk3 ( Fig 5Aii; S5 Fig ) . Thus , we aimed to determine whether the transglutaminase-like domain of Cyk3 interacts with Chs2 , so we performed a yeast two-hybrid assay and found that a fragment of Cyk3 that contains precisely the transglutaminase-like domain ( Cyk3-475-594 ) was unable to interact with Chs2-215-629 ( Fig 5Aiii ) or Chs2-1-629 ( S5 Fig ) . Whereas a slightly bigger fragment of Cyk3 containing the transglutaminase-like domain ( Cyk3-475-764 ) , interacted with Chs2 , which would indicate that the transglutaminase-like domain is not enough to bind to Chs2 ( Fig 5Aiii ) . In addition , we observed that the two versions of Cyk3 that lack the transglutaminase-like domain ( Cyk3-1-475 and Cyk3-765-885 ) are able to interact with Chs2 , which showed that different domains within Cyk3 protein structure are responsible for the interaction between Cyk3 and Chs2 ( Fig 5Aiii; S5 Fig ) . Interestingly we found that interactions are the same whether we performed the yeast two-hybrid assay with either Chs2-215-629 ( Fig 5A ) or Chs2-1-629 ( S5 Fig ) , except for Cyk3-475-764 fragment . We showed that Cyk3-475-764 interacted with the fragment of Chs2 that lacks the N-terminal domain but not with Chs2-1-629 , which would suggest that the N-terminal tail of Chs2 could play a role in regulating the interaction between Chs2 and Cyk3 . Our findings would indicate that Cyk3 protein uses different domains to bind to chitin synthase Chs2 . We then examine whether artificial recruitment of the transglutaminase-like domain of Cyk3 to the actomyosin ring was sufficient to supply Cyk3 function . We have previously reported that CYK3 becomes essential in cells in which the C2 domain of Inn1 was fused to the chitin synthase Chs2 ( C2-CHS2 ) in the same way as when the C2 domain is fused to HOF1 [20] . A diploid strain was created in which a copy of CYK3 was inactivated ( cyk3-2A ) and one copy of HOF1 had been modified so that the encoded protein was fused to the transglutaminase-like domain of Cyk3 ( TG-HOF1 ) . The meiotic progeny of the resultant strain was then analysed by tetrad analysis . We found that expression of the TG-Hof1 fusion protein rescued the lethal effects associated to C2-CHS2 cyk3-2A cells ( S6B Fig ) , which shows that the fusion protein is able to bring the function of the transglutaminase-like domain to the site of division . Nevertheless , the transglutaminase-like domain is not the only essential function of Cyk3 in C2-CHS2 cells , since artificial recruitment of the transglutaminase-like domain of Cyk3 to the actomyosin ring was insufficient to provide Cyk3 function in cells lacking the CYK3 gene ( S6C Fig ) . To determine whether Cyk3 and Chs2 did indeed bind each other directly , we studied whether these factors were able to interact in E . coli extracts . We used E . coli cells to express 6His-Cyk3 , in parallel with another strain that expressed Strep-tag-Chs2-215-629 . After two consecutive purification steps , as described previously , we were able to observe that both proteins formed a stable complex ( Fig 5B ) . Overall , these data suggest that Cyk3 interacts directly with chitin synthase Chs2 and regulates its enzymatic activity during cytokinesis , in which the transglutaminase-like domain of Cyk3 plays an important role . The next step was to determine whether a protein fragment of Chs2 that contained the catalytic domain ( Chs2-215-629 ) together with Inn1 and Cyk3 could form a stable complex in the absence of other eukaryotic proteins by using an E . coli expression system . We made parallel cultures of cells that expressed 6His-Inn1 , Strep-tag-Chs2-215-629 and untagged Cyk3 . We then mixed them and prepared a common cell extract containing the three proteins . After consecutive purification of the Chs2 fragment and Inn1 , we were able to show that these factors formed a ternary complex with Cyk3 ( Fig 5C ) . Therefore , our findings so far show that Chs2 , Inn1 and Cyk3 proteins all bind directly to each other . These findings also indicate that both the transglutaminase-like domain of Cyk3 and the C2 domain of Inn1 regulate chitin synthase activity at the site of division . We have previously found that Cyk3 is essential in cells expressing the fusion C2-Hof1 [20] despite the presence of wild-type Inn1 in these cells . We proposed that understanding why Cyk3 becomes essential in C2-HOF1 cells could reveal the molecular details of how Inn1 and Cyk3 regulate primary septum deposition . To determine whether the problem associated with those cells was related to the function of chitin synthase Chs2 , we constructed a diploid strain that lacked one copy of CYK3 and harboured the fusion C2-HOF1 and the hypermorphic allele of CHS2 ( Fig 6A ) . We found that hypermorphic Chs2 ( CHS2-V377I ) suppressed the cytokinesis defect caused by the lack of the Cyk3 protein in C2-HOF1 cells ( Fig 6A , compare double and triple mutant ) , which confirms that C2-HOF1 cyk3Δ cells fail cell division because of the defects associated with primary septum formation , despite the presence of wild-type Inn1 ( Fig 6A ) . One possible explanation for why Cyk3 becomes essential in C2-HOF1 cells might be that wild-type Inn1 is unable to localise at the cleavage site , such that these cells would have C2 function ( via C2-Hof1 fusion ) but they would lack Inn1 C-terminus function . This hypothesis would argue that the Inn1 C-terminus and Cyk3 could share a function and cells would cope with the absence of one of them , but not with the lack of both at the same time . To determine whether wild-type Inn1 is able to localise in C2-HOF1 , we synchronised INN1-GFP and C2-HOF1 INN1-GFP cells at 24°C in the G1 phase and then released cells to study Inn1-GFP localisation at the cleavage site . We could observe no defect in Inn1 localisation ( S7A Fig ) . Since C2-HOF1 cells have two C2 domains ( C2-Hof1 and full-length Inn1 ) , second option could be that cells containing two active C2 domains might require the presence of Cyk3 , presumably to regulate Chs2 function . We generated yeast strains harbouring the C2-HOF1 fusion and the ‘auxin inducible degron’ ( ‘aid’ ) cassette on CYK3 to conditionally inactivate Cyk3 protein [50] . We reproduced previously described synthetic lethality using tetrad analysis ( Fig 6B ( i ) ; see 3 and 4 ) . In addition , to further check this second possibility , we made strains in which cells carried a degron version of Inn1 in order to be able to deplete Inn1 . In parallel these cells expressed an extra copy of INN1 , which had been mutated to inactivate C2 function ( C2-K31A ) , although the Inn1 C-terminus remained fully functional ( C2-HOF1 td-inn1-aid leu2::K31A ) ( Fig 6B ( ii ) ) . After Inn1 inactivation , these cells grew as the C2 function was carried by the fusion C2-HOF1 , despite the expression of mutated Inn1 ( Inn1-K31A ) ( Fig 6B ( ii ) ; see 5 and 6 ) . To determine whether Cyk3 was essential for cells expressing C2-Hof1 and Inn1-K31A , we inactivated Cyk3 and assayed cell growth after three days to show that cells died ( Fig 6B ( ii ) ; see 6 and 7 ) . Thus , we noted that the reason why C2-HOF1 cyk3Δ cells cannot grow is not due to the presence of extra C2 activity , but it is down to the lack of Cyk3 when cells express a functional Inn1 C-terminus ( Fig 6B; see 4 and 7 ) . Furthermore , tetrad analysis of diploid C2-K31A-HOF1 cyk3Δ CHS2-V377I ( containing wild-type levels of Inn1 ) revealed that C2-K31A-HOF1 cyk3Δ cells are unable to form a colony ( Fig 6C ) . Intriguingly , in those cells , despite the presence of non-functional C2 fused to HOF1 , C2 function can be performed by wild-type copy of Inn1 ( Fig 6C , see C2-K31A-HOF1 cells ) . It thus appears that it is the presence of Inn1 C-terminus and the lack of Cyk3 function that are responsible for the death of C2-K31A-HOF1 cyk3Δ cells . This defect can be rescued by the hypermorphic allele of CHS2 ( Fig 6C , see C2-K31A-HOF1 cyk3Δ CHS2-V377I cells ) . To determine whether the lack of Inn1 C-terminus and the absence of Cyk3 can be fully bypassed by hypermorphic CHS2 , we generated a diploid carrying the fusion C2-HOF1 , deletions of both CYK3 and INN1 , together with hypermorphic allele of CHS2 ( Fig 6D ) . We found that the lack of Inn1 C-terminus function in C2-HOF1 cyk3Δ inn1Δ cells ( Inn1 C2 function is carried by the fusion C2-HOF1 ) is completely rescued by increasing the chitin synthase activity associated to Chs2 ( Fig 6D; the result was confirmed using a growth assay in S7B Fig ) . Finally , we confirmed the same observations inactivating specifically the transglutaminase-like domain of Cyk3 ( cyk3-2A ) in C2-HOF1 inn1Δ CHS2-V377I cells ( Fig 6E ) . Our data would indicate that Inn1 C-terminus and Cyk3 are involved in the regulation of chitin synthase activity associated to Chs2 . Therefore , the third possibility is that , despite the presence of C2 function ( via C2-Hof1 ) , the Inn1 C-terminus could be regulating chitin synthase Chs2 activity , in such a way that Cyk3 would be required as well . Interestingly , the C-terminus of Inn1 localises at the site of division in a manner similar to full-length Inn1 [19] , which shows that the Inn1 C-terminus can still interact with components of the actomyosin ring . Using the yeast two-hybrid assay we found that the Inn1 C-terminus interacted with Chs2 ( Chs2-1-629 ) . Interestingly , the Inn1 C-terminus binds to the N-terminal tail of Chs2 ( Chs2-1-215 ) , which has been shown to be regulated by CDK activity , whereas a fragment of Chs2 that contains only its catalytic domain ( Chs2-215-629 ) was unable to interact with the Inn1 C-terminus ( Fig 7A ) . In order to test whether the Inn1 C-terminus could bind Chs2 in vivo , we generated a yeast strain in which the TAP epitope was fused to the Inn1 C-terminus . We then cultured Inn1 C-terminus-TAP and control cells ( as detailed in Fig 2A ) and found that Chs2 interacted with the Inn1 C-terminus ( Fig 7B ) . To study whether the Inn1 C-terminus could regulate chitin synthase activity associated with Chs2 , chs3Δ cells were transformed to generate strains that overexpressed Chs2 or Chs2 together with the Inn1 C-terminus in order to perform an in vitro chitin assay ( Fig 7Ci ) . We found that the Inn1 C-terminus had an inhibitory effect on Chs2 activity ( Fig 7Cii ) . We have shown that C2 overexpression had a direct positive impact on Chs2 chitin synthase activity ( Fig 2C ) , whereas the remainder of the protein , that is the C-terminus , displayed an adverse effect on Chs2 function ( Fig 7C ) . Subsequently , we aimed to find out how full-length Inn1 might regulate the chitin synthase activity of Chs2 . Cells overexpressing Chs2 , or Chs2 at the same time as full-length Inn1 ( Fig 7Di ) , were used to assay chitin synthase activity . We found that full-length Inn1 negatively regulated Chs2 enzymatic activity ( Fig 7Dii ) . Thus , our findings indicate that the Inn1 C-terminus blocks the ability of the C2 domain to induce chitin synthase activity associated with Chs2 . To determine the role of Inn1 and Cyk3 during cytokinesis , we aimed to study the defects associated with C2-HOF1 cells in which Cyk3 was depleted . First , to investigate whether these cells had a defect in actomyosin ring formation or contraction we followed the presence of Myo1 protein at the site of division . To tightly control Cyk3 inactivation , we included a ‘heat-inducible degron’ cassette at the N-terminus of Cyk3-aid and created a double degron td-cyk3-aid as previously reported ( S8A Fig ) ( ‘td’ indicates the temperature sensitive degron ) [51] [52] [53] [50] [20] . We grew asynchronous cultures of C2-HOF1 td-cyk3-aid MYO1-GFP and control cells at 24°C before synchronising cells in G1 phase with mating pheromone ( Fig 8A ) . After the induction of both Ubr1 E3 ligase and Tir1 F-box protein , together with the addition of auxins to rapidly deplete Td-Cyk3-aid protein , cells were released at 24°C from G1 block . We observed that both mutant and control cells progressed up to anaphase in a similar manner . Unlike control cells , C2-HOF1 td-cyk3-aid MYO1-GFP accumulated as binucleate cells , which would reflect a failure in cell division ( Fig 8Ai ) . Localisation of Myo1 at the site of division was observed with similar kinetics in both strains , which would indicate that mutant cells were able to assemble and contract the actomyosin ring ( Fig 8Aii ) . To confirm the kinetics of ring contraction , time-lapse video microscopy was used ( Fig 8B ) . C2-HOF1 td-cyk3-aid MYO1-GFP and control cells were grown in a similar way as for Fig 8A . After the cells had budded and completed S-phase , nocodazole was added to synchronise the cells , this time in G2-M-phase . Cells were washed into fresh medium and subsequently placed in the time-lapse slide to examine the localisation of Myo1 every two minutes as cells completed mitosis at 24°C . To ensure that both strains were treated in an identical fashion , the cultures were mixed before the cells were transferred to the time-lapse slide ( the control cells expressed Spc42-eQFP and thus could be distinguished from C2-HOF1 td-cyk3-aid cells ) ( see Materials and Methods for details ) . Twenty-two movies each were examined for control and C2-HOF1 td-cyk3-aid MYO1-GFP cells , and contraction of the actomyosin ring was observed with similar kinetics ( Fig 8B ) . The average period from the initiation of contraction to the final disappearance of the ring was similar in control and C2-HOF1 td-cyk3-aid MYO1-GFP cells ( a mean value of 5 . 54 min in control cells compared with 5 min in the mutant strain ) . C2-HOF1 td-cyk3-aid MYO1-GFP cells never showed a contracted ‘spot’ as control cells . In mutant cells , the actomyosin ring disassembled before reaching the final contraction stage ( ‘spot’ ) , which explains the slightly shorter contraction period in mutant cells ( Fig 8B ) . Taken together , these experiments demonstrate that C2-HOF1 cells in which Cyk3 has been inactivated are able to form an actomyosin ring and subsequently to contract and disassemble . To examine whether Inn1 localisation was altered by the lack of Cyk3 in C2-HOF1 strain , we cultured control and C2-HOF1 td-cyk3-aid cells , both of which expressed Inn1-GFP . Cells were treated in the same way as for Fig 8A . We found a higher percentage of cells with Inn1-GFP accumulation in C2-HOF1 td-cyk3-aid cells ( Fig 9A ) . To confirm that the lack of Cyk3 function in C2-HOF1 cells promoted Inn1 accumulation , we transformed C2-HOF1 td-cyk3-aid with either CYK3 or cyk3-2A alleles and cultured them in an identical way as above ( Fig 9A ) . We showed that inactivation of the transglutaminase-like domain of Cyk3 ( cyk3-2A ) induced Inn1-GFP accumulation ( Figs 9B and S8B ) . Since actomyosin ring contraction seemed to have no delay in C2-HOF1 td-cyk3-aid cells ( Fig 8 ) , which would explain the accumulation of Inn1-GFP , we aimed to determine whether Inn1-GFP localisation is slightly advanced in mutant cells . We grew control and C2-HOF1 td-cyk3-aid cells in the same fashion as described previously ( Fig 8B ) . After inactivation of Td-Cyk3-aid protein , cells were synchronised in G2-M-phase with high mitotic CDK by addition of nocodazole to the culture medium . Inn1 protein is unable to be localised at the site of division before cells down-regulate CDK activity at the end of mitosis [31] [41] [54] ( Fig 9C ) . However , we found that 33% of C2-HOF1 td-cyk3-aid cells were able to localise Inn1-GFP with high mitotic CDK , which indicates that inactivation of Cyk3 prompts earlier Inn1 localisation . So far our findings indicate that Inn1 and Cyk3 formed a ternary complex with chitin synthase Chs2 ( Fig 5C ) . In addition , our biochemical and genetic analysis show that Inn1 and Cyk3 control chitin synthase activity associated to Chs2 ( Figs 6 and 7 ) . Therefore , we aim to determine whether C2-HOF1 td-cyk3-aid cells have a defect in primary septum formation in vivo . We cultured C2-HOF1 td-cyk3-aid and control cells under the same conditions as indicated above for Fig 8A , but in the presence of calcofluor upon release from G1 block to stain the primary septa . We found that cells expressing C2-Hof1 together with wild-type Inn1 in the absence of Cyk3 were unable to lay down a primary septum , which would suggest that Chs2 function was impaired ( Fig 9D ) . We were unable to determine whether Chs2 localisation occurred in C2-HOF1 td-cyk3-aid cells , as triple mutant cells are dead or extremely sick ( C2-HOF1 CHS2-GFP td-cyk3-aid ) ( S8C Fig ) . However , we found that the delivery of Chs2 to the site of division seems to be similar in control and Cyk3-depleted cells , since both type of cells showed similar dynamics of the localisation of Chs2-GFP ( S8D Fig ) and the formation of primary septum ( S8E Fig ) . Therefore , our data indicate that the lack of Cyk3 does not prevent Chs2 localisation and primary septum deposition . Overall these data show that Inn1 regulates Chs2 activity at the site of division , where the C2 domain induces Chs2 function , whereas the C-terminus of Inn1 seems to have an inhibitory effect on Chs2 . Our results indicate that Cyk3 counteracts this inhibitory role since Cyk3 becomes essential under conditions in which the Inn1 C-terminus plays a more relevant role , such as in C2-HOF1 cells . In addition , Cyk3 seems not to have a role in the delivery of Chs2 vesicles to the cleavage site . Chs2 protein interacts with actomyosin ring components to build the IPCs at the end of mitosis . To understand the importance of these interactions for Chs2 localisation and maintenance at the site of division we studied the fluorescence signal associated with Chs2-GFP in controls cells and in cells in which a particular actomyosin ring component had been previously inactivated . Cultures of CHS2-GFP and iqg1-td CHS2-GFP cells were grown at 24°C and cells were synchronised in G1 phase of the cell cycle with mating pheromone , before rapidly inactivating Iqg1 at 37°C . Upon release from G1 arrest at 37°C , iqg1-td cells completed mitosis but were unable to divide unlike the control cells ( Fig 10Ai ) . Importantly , medial rings or contracted dots of Chs2 were not observed in the absence of Iqg1 ( Fig 10Aii and 10Aiii ) . This shows that Iqg1 is essential for the localisation of Chs2 . Additionally , it has been described that Iqg1 interacts with Hof1 and Inn1 , and we have previously reported that Inn1-Iqg1 interaction is required for the Inn1 protein to be localised at the division site [19] . Our next step was therefore to determine whether Iqg1 is important for Hof1 to interact with the actomyosin ring . We grew HOF1-GFP and iqg1-td HOF1-GFP cells as detailed in Fig 10A and we found that the absence of Iqg1 caused a defect in Hof1 localisation ( Fig 10B ) . Taken together , these experiments indicate that the Iqg1 protein is crucial for building functional IPCs at the end of mitosis in budding yeast . To determine whether Chs2 localisation requires the presence of Hof1 or Inn1 at the site of division , we grew CHS2-GFP and hof1-td CHS2-GFP cells asynchronously at 24°C and cultured them in the same manner as described for Fig 10A . After rapid depletion of Hof1 in cells we followed Chs2-GFP localisation and found that Chs2-associated signal at the cleavage site was compromised when Hof1 protein was inactivated ( S9A Fig ) . Subsequently , we investigated whether Chs2 localisation depends on Inn1 protein . We observed that Chs2 protein was still able to localise , although Chs2 dynamics at the site of division seemed to be affected , since we detected less Chs2 at the division site ( S9B Fig ) . Finally , we investigated whether the lack of Hof1 and Inn1 at the same time would affect Chs2 recruitment . CHS2-GFP and hof1-td inn1-td CHS2-GFP cells were grown and , after rapid inactivation of Hof1 and Inn1 , we found that Chs2 localisation at the cleavage site was entirely dependent on the presence of both Hof1 and Inn1 ( Fig 10C ) , which is the same result as showed above for iqg1-td cells . Our findings would suggest that the dynamics of the chitin synthase Chs2 at the site of division in budding yeast requires the interaction with either Iqg1 protein or Hof1 and Inn1 together . Our data indicate that budding yeast cells assemble at the end of mitosis protein complexes that we have named ingression progression complexes ( IPCs ) to coordinate actomyosin ring contraction , plasma membrane ingression and primary septum formation . The IPCs include Myo1 , Iqg1 , Hof1 , Inn1 , Cyk3 and Chs2 . We propose that the IPCs indeed form the central machinery with which cells are able to coordinate cytokinetic events , which provides a mechanistic explanation for the tight coordination between them [55] [17] [8] . Our data support a model whereby IPCs are assembled in a sequential and highly regulated fashion to control first the localisation and then the activation of the chitin synthase Chs2 at the end of mitosis , which plays a key role in the tight coordination of actomyosin ring contraction , plasma membrane ingression and primary septum formation ( Fig 11 ) [8] [37] [38] [39] [14] . Myo1 and Iqg1 serve as initial building blocks with which the other IPC components Hof1 , Cyk3 , Inn1 and Chs2 then interact [19] [31] [32] [33] [34] [30] [29] [27] . Specific inactivation of Myo1 or Iqg1 prevents the localisation of the other components of IPCs , which highlights their scaffolding role [19] . Moreover , IPC members commonly displayed Myo1-dependent immobility during cytokinesis , supporting further that Myo1 plays a scaffolding role in the assembly of IPCs [24] . Our findings indicate that Hof1 would facilitate Chs2 localisation at the site of division whereas Inn1 and Cyk3 are essential for the activation of chitin synthase activity . In addition to its role in promoting the formation of the primary septum , Hof1 plays an important role in the assembly of the actomyosin ring in S . cerevisiae , together with the protein Rvs167 [56] [55] [28] [29] [30] . It appears that the basic principles of action of budding yeast Hof1 and its fission yeast orthologue Cdc15 are likely to be similar , with both proteins contributing to assembly of the actomyosin ring as well as to the stability of the contracting ring and/or septum formation [57] [58] [59] [29] [30] [11] . In budding yeast it has been described that Hof1 interacts directly with Chs2 and stabilises the chitin synthase at the cleavage site [29] . Accordingly , we found that Chs2 localisation at the bud neck is clearly compromised in Hof1-depleted cells . In addition , we observed that increased expression of Chs2 rescues defects associated with the lack of Hof1 ( S9C Fig ) . However , a hypermorphic version of Chs2 was unable to supress the cell division defect produced by Hof1 inactivation ( S9D Fig ) , unlike what occurs with Inn1 or Cyk3-depleted cells [20] . Our findings indicate that Hof1 assists in the incorporation of Chs2 at the cleavage site and not in its activation . Our data is consistent with recent reports that showed how fission yeast cells lacking Cdc15 fail to accumulate at the cleavage site the protein that plays an analogous role to Chs2 [11] , namely the transmembrane glycosyltransferase Bgs1 ( beta ( 1 , 3 ) -glucan synthase ) , which lays down the primary septum during cytokinesis in fission yeast cells [9] [60] . Chs2 appears to be delivered to the plasma membrane in an inactive form and is then activated in situ by a mechanism that has not previously been understood [31] [19] [20] [32] [40] . Our data indicate that the Inn1 and Cyk3 proteins are indeed directly responsible for such activation ( Fig 11 ) . The interaction of Chs2 , Inn1 and Cyk3 would require the inactivation of mitotic forms of Cyclin Dependent Kinase ( CDK ) and the dephosphorylation of CDK targets such as Chs2 and Inn1 by the Cdc14 phosphatase [38] [39] [33] [54] [61] [62] . Our model proposes that Inn1 binds to Chs2 at the end of mitosis , but the C-terminus of Inn1 keeps Chs2 chitin synthase inactive . It has been reported that a version of Chs2 that lacks its N-terminal domain show high levels of chitin synthase activity ( Martinez-Rucobo et al 2009 ) , which suggests that the N-terminal tail of Chs2 ( Chs2-1-215 ) negatively regulates its own activity . Interestingly , our data indicate that the C-terminus of Inn1 binds precisely to the N-terminal tail of Chs2 ( Fig 7A ) and , consistently with these data , we described how the C-terminus of Inn1 blocks chitin activity associated to Chs2 . In addition , it seems that the N-terminal tail of Chs2 could be regulating as well the interaction between Chs2 and Cyk3 ( Fig 5A ) . Cyk3 becomes incorporated to the IPCs and precisely releases chitin synthase activity of Chs2 from such a block and consequently the C2 domain of Inn1 acts in conjunction with Cyk3 to activate the catalytic domain of Chs2 ( Fig 11 ) . In addition to its catalytic activity , Chs2 has attractive features to serve as an anchor between the actomyosin ring and the plasma membrane , since it is the only component of the IPCs that has a transmembrane domain embedded in the plasma membrane . It appears that , in budding yeast , having such a physical link with the plasma membrane is not sufficient for ingression , since cells need active glycosyltransferase for extracellular matrix remodelling and its coordination with actomyosin ring contraction during cytokinesis [19] [20] . Interestingly , each component of budding yeast IPCs has an orthologue in fission yeast cells with a role during cytokinesis , although the molecular mechanism by which they regulate cell division is not yet understood in all cases [60] [22] [63] [58] [49] . Fission yeast cells have orthologues of Inn1 and Cyk3 , namely Fic1 and Cyk3 , which share the same structure as their budding yeast counterparts and , in addition , they have been described to play a role during cytokinesis [58] [49] . The Fic1 protein interacts with Cdc15 and adds structural integrity to the actomyosin ring and prevents it from collapsing during cell division [58] , whereas fission yeast Cyk3 has been suggested to play a role in coupling actomyosin ring contraction and primary septum formation , although the molecular mechanism remains unclear [49] . The presence of chitin in S . pombe septum is uncertain , but instead it has been proposed that S . pombe Chs2 would play a structural role and would be required for proper actomyosin ring contraction and stability [64] . Intriguingly , in fission yeast the glycosyltransferase Bgs1 could play the same role as Chs2 in budding yeast , although the polysaccharide that Bgs1 produces is different ( Chs2 synthesises chitin , which is a polymer of N-acetylglucosamine; Bgs1 synthesises glucan , which is a polymer of D-Glucose ) . Bgs1 is an integral membrane protein with its catalytic domain located at the cytoplasmic side of the membrane like Chs2 [9] [60] . Interestingly , the lack of Bgs1 promotes actomyosin ring sliding along the plasma membrane , which supports the idea that Bgs1 could function as an anchor between the actomyosin ring and the plasma membrane [11] [65] . How human cells perform the coordination of actomysin ring contraction , plasma membrane ingression and ECM remodelling remains largely unknown . Taking into account the conservation of the basic cytokinetic mechanisms [22] [60] [3] , it will be interesting to determine whether glycosyltransferases also play a role during cytokinesis in higher eukaryotes . The strains used in this study are listed in S1 Table . Yeast cells were grown in rich medium ( 1% Yeast Extract , 2% peptone , 0 . 1 mg per ml adenine ) supplemented with 2% glucose ( YPD ) , 2% Raffinose ( YPRaff ) or 2% Galactose ( YPGal ) as the carbon source with the exception of cells for time-lapse video microscopy , for which we used Synthetic Complete medium at the end of the experiment . We arrested cells in the G1 phase of the cell cycle by the addition of alpha factor mating pheromone to the medium at a final concentration of 7 . 5 μg per ml . We arrested cells in the G2-M phase of the cell cycle by the addition of nocodazole to the medium at a final concentration of 5 μg per ml . To degrade proteins fused to the ‘heat-inducible degron’ and ‘auxin-inducible degron’ we followed procedure described previously [66] [50] . In experiments with temperature sensitive degron strains and for strains expressing fused proteins ( C2-HOF1 , C2-CHS2 and TG-HOF1 ) , 0 . 1mM CuSO4 was included in the growth medium , as all of them were expressed from the CUP1 promoter . To stain primary septa of living cells , calcofluor was added when specified 30 minutes after release from G1 block to a final concentration of 0 . 05 mg per ml and culture was incubated further for at least 60 minutes . Two-hybrid analysis was performed using the vectors pGADT7 and pGBKT7 ( Clontech ) . Cells were grown for two or three days at 30°C on Synthetic Complete medium lacking leucine and tryptophan ( non-selective ) or lacking leucine , tryptophan and histidine ( selective ) . The plasmids used in this study to express recombinant proteins in E . coli are based on the ‘pET’ series ( Novagen ) and are listed in S2 Table . To isolate recombinant protein complexes from extracts of E . coli cells , we followed the scheme illustrated in S1A Fig and as it was described previously [30] . The various protein fragments were expressed individually as ‘Streptag’ or ‘6His-tag’ fusions . Cells containing each of the fusions were grown at 37°C , after which the expression of the recombinant protein fragments was induced with 1 mM IPTG . Subsequently , the cultures were mixed , so that each cell extract would contain two recombinant proteins ( Figs 1B , 1C , 1D , 2A ( ii ) , 2A ( iii ) and 5B ) or three recombinant proteins ( Fig 5C ) . In the case of the controls , a culture with an empty vector was mixed with the corresponding cultures expressing recombinant proteins . The Streptag-fusions were then isolated from the cell extracts in 1 ml of Strep-Tactin Superflow ( 2-1206- 025 , IBA GmbH ) , before elution with 2 . 5 mM d-Desthiobiotin ( D1411 , Sigma ) . The eluted material was then diluted and incubated with 1 ml of Ni-NTA Agarose ( 30230 , Qiagen ) , and bound protein complexes were eluted with sequential 0 . 5 ml aliquots of buffer containing 250 mM imidazole . Following the addition of 3X Laemmli buffer to the eluted samples , 20 μl of each purified sample was resolved by SDS-PAGE . To monitor the association of proteins in yeast cell extracts we followed methods previously described [67] [46] with slight modification as cell extracts were spun down at 20 000 x g . We have isolated tagged proteins by immunoprecipitation with magnetic Dynabeads M-270 Epoxy ( Invitrogen ) coupled to rabbit anti-sheep IgG ( Sigma S-1265 ) , 9E10 anti-MYC monoclonal antibody ( Cancer Research Technology ) or 12CA5 anti-HA monoclonal antibody ( Cancer Research Technology ) . We detected the indicated proteins by immunoblotting with previously described polyclonal antibodies to Inn1 [20] or by using polyclonal anti-FLAG antibody ( Sigma F-7425 ) , or monoclonal 9E10 ( anti-MYC ) , or 12CA5 ( anti-HA ) . To detect Chs2 ( rabbit polyclonal ) and Cyk3 ( sheep polyclonal ) , we raised polyclonal antibodies to 25 kDa portions of each protein ( S1C and S1D Fig ) , expressed as His-tagged recombinant proteins in E . coli and purified in a denatured form . The TAP tag was detected using the rabbit peroxidase anti-peroxidase complex ( Sigma P-2026 ) . For mass spectrometry analysis of protein content , the digested peptides were analysed by nano LC/MS/MS with an ‘Orbitrap Velos’ ( ThermoFisher ) and the data were processed as described previously [68] [69] . Cell membrane isolation and chitin synthase activity assays were performed as described previously [20] , clearly detecting chitin synthase activity associated to Chs2 ( S10A Fig ) In isolated cell membranes Chs2 is nearly inactive , unless protease treatment is used to bypass inhibition [14] . To clearly identify whether full-length Inn1 , Inn1 C2 or Inn1 C-terminus had an effect on chitin synthase associated with Chs2 , we plotted the percentage of active chitin synthase calculated as percentage of chitin synthase activity ( without trypsin ) compared to the maximum chitin activity reached by the same sample ( with trypsin ) : ( chitin synthase activity without trypsin / chitin synthase activity with trypsin ) x100 . Error bars represent SEM values calculated for each of the experiments . Samples used to measure the DNA content were fixed with 70% ethanol . Subsequently samples were processed and stained with propidium iodide after RNA digestion , as described previously [53] . The proportion of binucleate cells was determined by observing the same samples under the microscope as those employed for flow cytometry [70] . We examined 100 cells for each sample . Pictures of cells and colonies on agar plates were taken after 24 hours ( YPD medium ) or 30 hours ( YPGal medium ) with a Nikon CoolPix 995 camera attached to a Nikon Eclipse E400 microscope . We used calcofluor ( Fluorescent Brightener 28; Sigma; F3543-1G ) to stain the primary septa of live cells . We tested that there was a direct correlation between calcofluor staining and chitin synthase activity associated to Chs2 in vivo ( S10B Fig ) . Calcofluor was added 30 minutes after release from G1 block to a final concentration of 0 . 05 mg per ml and the culture was further incubated for at least 60 minutes . Calcofluor-stained cells were observed live . To quantify primary septum deposition , we examined 100 cells with primary septum for each sample , and measure the relative signal intensity of the primary septum using Image J software [71] . To observe GFP-tagged proteins , the cells were fixed with 8% formaldehyde for 10 minutes and subsequently washed twice with PBS [19] . We examined 100 cells for each sample . Phase contrast and fluorescence microscopy images of cells grown in liquid culture were obtained with a Nikon A1R Microscope and an Orca R2 camera ( Hamamatsu ) with objective lens Plan Apo TIRF 100x oil DIC 1 . 49NA , and LightLine single-band filter set FITC Semrock . The illumination source was the Nikon Intensilight C-HGFIE ( ultrahigh Presure 130W Mercury lamp ) , and we used NIS elements software . We analysed eleven z-sections with a spacing of 0 . 375 μm to facilitate the examination of the whole cell for all experiments . In all cases , the exposure time , sensor gain , and digital adjustments were the same for the control and experimental samples . Time-lapse video microscopy was performed using DeltaVision system with Olympus IX-71 microscope and CoolSNAP HQ2 Monochrome camera . The objective lens was Plapon 60X0 1 . 42 NA . The illumination source was the 300W xenon system with liquid light guide , and we used Softworx Resolve 3D acquisition software . Cells were grew in an IBIDI cells in focus 15 micro-slide ( 8 well 80827 glass bottom ) . The base of the time-lapse chamber is formed by a glass coverslip that we coated with a 5 mg per ml solution of the lectin Concanavalin A ( Sigma L7647 ) , and then washed with water and dried for 30 minutes . We analysed 10 z-sections with a spacing of 0 . 4 μm . The microscopy data were deconvolved , except for cells stained with calcofluor , using Huygens ( SVI ) according to the “Quick Maximum Likelihood Estimation” method and a measured point spread function . The deconvolved data set was viewed with Image J software [71] .
Cytokinesis is the process by which a cell divides in two and occurs once cells have replicated and segregated their chromosomes . Eukaryotic cells assemble a molecular machine called the actomyosin ring that drives cytokinesis . Contraction of the actomyosin ring is coupled to ingression of the plasma membrane and extracellular matrix remodelling . In eukaryotes , glycosyltransferases that synthesise polysaccharides of the extracellular matrix are emerging as essential factors during cytokinesis . Defects associated with the function of those glycosyltransferases induce the failure of cell division , which promotes the formation of genetically unstable tetraploid cells . Budding yeast cells contain a glycosyltransferase called Chs2 that makes a special layer of extracellular matrix and is essential during cell division . Our findings provide new insights into the molecular mechanism by which the cytokinesis regulators Inn1 and Cyk3 finely regulate the activity of glycosyltransferase Chs2 at the end of mitosis . In addition we isolated a group of actomyosin ring components that form complexes together with Chs2 and Inn1 at the cleavage site , which we have named ‘ingression progression complexes’ . These complexes coordinate the contraction of the actomyosin ring , ingression of the plasma membrane and extracellular matrix remodelling in a precise manner . Chs2 is indeed a key factor for coordinating these events . It appears that similar principles could apply to other eukaryotic species , such as fission yeast even if the identity of the relevant glycosyltransferase has changed over the evolution . Taking into account the conservation of the basic cytokinetic mechanisms future studies should try to determine whether a glycosyltransferase similar to Chs2 plays a key role during cytokinesis in human cells .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "chitin", "cell", "physiology", "g1", "phase", "cell", "cycle", "and", "cell", "division", "cell", "processes", "mitosis", "fungi", "model", "organisms", "materials", "science", "cytokinesis", "macromolecules", "cellular", "structures", "and", "organelles", "materials", "by", "structure", "saccharomyces", "research", "and", "analysis", "methods", "polymers", "polymer", "chemistry", "chromosome", "biology", "chemistry", "cell", "membranes", "yeast", "cell", "biology", "biology", "and", "life", "sciences", "yeast", "and", "fungal", "models", "physical", "sciences", "saccharomyces", "cerevisiae", "organisms", "cell", "fusion" ]
2016
Ingression Progression Complexes Control Extracellular Matrix Remodelling during Cytokinesis in Budding Yeast
Decision formation recruits many brain regions , but the procedure they jointly execute is unknown . Here we characterize its essential composition , using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex ( MT ) . Using it to simulate the random-dot-motion task , we demonstrate it quantitatively replicates the choice behaviour of monkeys , whilst predicting losses of otherwise usable information from MT . Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops , whose components are all implicated in decision-making . We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions , and forecast those of basal ganglia output and thalamus . This also predicts which aspects of neural dynamics are and are not part of inference . Our single-equation algorithm is probabilistic , distributed , recursive , and parallel . Its success at capturing anatomy , behaviour , and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics . Decisions rely on evidence that is collected for , accumulated about , and contrasted between available options . Neural activity consistent with evidence accumulation over time has been reported in parietal and frontal sensorimotor cortex [1–5] , and in the subcortical striatum [6 , 7] . What overall computation underlies these local snapshots , and how it is distributed across cortical and subcortical circuits , is unknown . Multiple models of decision making match aspects of recorded choice behaviour , associated neural activity or both [8–16] . While successful , they lack insight into the underlying decision mechanism . In contrast , other studies have shown how exact inference algorithms may be plausibly implemented by a range of neural circuits [17–21]; however , none of these has reproduced experimental decision data . Here we test the hypothesis that the brain implements an approximation to an exact inference algorithm for decision making . We show that the algorithm reproduces behaviour quantitatively while the dynamics of its inner variables match those of corresponding neural signals on the random dot motion task—a highly developed paradigm to probe decision formation . By doing so , we predict how experimentally-acquired snapshots of neural activity map onto inference operations . We show this mapping accounts for the involvement of full recurrent cortico-subcortical loops in decision making . Evidence accumulation is thus predicted to occur over the entire loops , not just within cortex . Introducing this algorithm enables us to predict which aspects of neural activity are necessary for inference—hence decision-making—and which are not . For instance , recent data questioned whether non-increasing cortical firing rates encode evidence accumulation during decisions [22 , 23] . We demonstrate that , counter-intuitively , non-increasing as well as increasing cortical rates can encode likelihood functions , and hence evidence accumulation . Our algorithm explains the decision-correlated experimental data more comprehensively than any prior model , thus introducing a new , cohesive formal framework to interpret it . Collectively , our analyses and simulations indicate that mammalian decision-making is implemented as a probabilistic , recursive , parallel procedure distributed across the cortico-basal-ganglia-thalamo-cortical loops . Normative algorithms are useful benchmarks to test how well the brain approximates an optimal probabilistic computation . The family of the multi-hypothesis sequential probability ratio test ( MSPRT ) [25] is an attractive normative framework for understanding decision-making . However , the MSPRT is a feedforward algorithm . It cannot account for the ubiquitous presence of feedback in neural circuits and , as we show ahead , for slow dynamics in neural activity that result from this recurrence during decisions . To solve this , we introduce a novel recursive generalization , the rMSPRT , which uses a generalized , feedback form of the Bayes’ rule we deduced here from first principles ( Eq 5 ) . We now conceptually review the MSPRT and introduce the rMSPRT ( Fig 2 ) , giving full mathematical definitions and deductions in the Materials and methods . The ( r ) MSPRT decides which of N parallel , competing alternatives ( or hypotheses ) is the best choice , based on C sequentially sampled streams of evidence ( or data ) . For modelling the dot-motion task , we have N = 2 or N = 4 hypotheses—the possible saccades to available targets ( Fig 1b and 1c ) —and the C uncertain evidence streams are assumed to be simultaneous spike-trains produced by visual-motion-sensitive MT neurons [1 , 9] ( see Methods ) . Every time new evidence arrives , the ( r ) MSPRT refreshes ‘on-line’ the likelihood of each hypothesis: the plausibility of the combined evidence streams assuming that hypothesis is true . The likelihood is then multiplied by the probability of that hypothesis based on past experience ( the prior ) . This product for every hypothesis is then normalized by the sum of the products from all N hypotheses; normalisation is crucial for decision , as it provides the competition between hypotheses . The result is the probability of each hypothesis given current evidence ( the posterior ) —a decision variable per hypothesis . Finally , posteriors are compared to a threshold , whose position controls the speed-accuracy trade-off . A decision is then made to either choose the most probable hypothesis , if its posterior surpassed the threshold , or to continue sampling the evidence streams otherwise . Crucially , the ( r ) MSPRT allows us to use the same algorithm irrespective of the number of alternatives , and thus aim at a unified explanation of the N = 2 and N = 4 dot-motion task variants . The MSPRT is a special case of the rMSPRT ( in its general form in Eqs 5 and 10 ) when priors do not change or , equivalently , for an infinite recursion delay; that is , Δ → ∞ . Also , the previous recurrent extension of MSPRT [18 , 26] is a special case of the rMSPRT when Δ = 1 . Hence , our rMSPRT generalizes both in allowing the re-use of posteriors from any given time in the past as priors for present inference . This uniquely allows us to map the rMSPRT onto neural circuits containing arbitrary feedback delays , in particular solving the problem of decomposing the decision-making algorithm into distributed components across multiple brain regions . We show below how this allows us to map the rMSPRT onto the cortico-basal-ganglia-thalamo-cortical loops . Inference using recursive and non-recursive forms of Bayes’ rule gives the same results ( e . g . see [27] ) , and so MSPRT and rMSPRT perform identically . Thus , like MSPRT [17 , 25] , for N = 2 rMSPRT also collapses to the sequential probability ratio test of [28]; the rMSPRT is thereby optimal , not only in the oft-used sense of using all available information to do statistical inference ( e . g . using the Bayes’ rule ) , but also in the strict sense that it requires the smallest expected number of observations , thus the shortest time to decide , at any given error rate ( which follows from [29] ) . This is to say that the ( r ) MSPRT is quasi-Bayesian in general: the physical limit of performance or ideal Bayesian observer for two-alternative decisions ( N = 2 ) , and an asymptotic approximation to it for decisions between more than two ( N > 2 ) ( which follows from [17 , 25] ) . The hypothesis that the brain approximates an exact inference algorithm during decision formation is so far untested . This requires showing how uncertain sensory spike-trains can be transformed into the experimentally recorded choices . We do so here for the first time by comparing the predicted choice reaction times of the ( r ) MSPRT to those of monkeys performing the random dot motion task . We sought to account for the reaction time dependence on three factors: the coherence of the dot motion , the number of decision alternatives , and the trial’s outcome ( error , correct ) . We use a particular instance of rMSPRT ( Eqs 9 and 10 ) to determine predicted normative bounds on the decision time in the dot motion task . We can then ask how well monkeys approximate such bounds . The bounds result from using a minimal amount of sensory information , by assuming as many evidence streams ( spike-trains from MT neurons ) as alternatives; that is , C = N . Thus , this rMSPRT instance gives the upper bound on optimal expected decision times ( exact for N = 2 alternatives , approximate for N = 4 ) per condition ( given combination of coherence and N ) . Assuming C > N would predict even shorter optimal expected decision times ( see [20] ) . We assume that during the random dot motion task ( Fig 1a–1c ) , the evidence streams for every possible saccade come as simultaneous sequences of inter-spike intervals ( ISI ) produced in MT . On each time step , fresh evidence is drawn from the appropriate ( null or preferred direction; see Methods ) ISI distributions extracted from MT data ( Fig 1f ) . By repeating the simulations for thousands of trials per condition , we can compare algorithm and monkey performance . Using these data-determined MT statistics , the ( r ) MSPRT predicts that the mean decision time on the dot motion task is a decreasing function of coherence ( Fig 3a ) . For comparison with monkey reaction times , the algorithm’s reaction times are the sum of its decision times and estimated non-decision time , encompassing sensory delays and motor execution . For macaques 200–300 ms of non-decision time is a plausible range [30 , 31] . Within this range , monkeys tend not to reach the predicted upper bound of reaction time ( Fig 3a ) . The ( r ) MSPRT framework suggests that decision times directly depend on the discrimination information in the evidence . Discrimination information here is measured as the divergence between pairs of distributions of ISIs ( those in Fig 1f ) produced simultaneously by MT neurons responding to the same stimulus: one where they were tuned to the dominant motion direction of the dots ( it was their preferred; solid lines in Fig 1f ) and another where they were not ( it was a null direction; dashed lines ) . Intuitively , the larger this divergence or difference , the easier and hence faster the decision . We can estimate how much discrimination information monkeys used by asking how much the exact inference performed by ( r ) MSPRT would require to obtain the same reaction times on correct trials as the monkeys , per condition . We thus find , first , that the discrimination information available for decision is very similar across N ( Fig 3b ) , implying that monkeys use MT sensory information consistently . Second , and most important , we find that monkeys tended to use less discrimination information than that in ISI distributions in their MT when making the decision . In contrast , the ( r ) MSPRT uses the full discrimination information available . This implies that the decision-making mechanism in the monkey brain lost large proportions of MT discrimination information ( Fig 3c ) . Since these ( r ) MSPRT decision times are upper bounds , this in turn means that this loss of discrimination information in monkeys ( Fig 3c ) is the minimum . To verify if this information loss alone could account for the monkeys’ deviation from the ( r ) MSPRT upper bounds , we depleted the discrimination information of its input distributions to exactly match the estimated monkey loss in Fig 3c per condition . We did so only by modifying the mean and standard deviation of the null direction ISI distribution , to make it more similar to the preferred distribution ( exemplified in Fig 3d ) . Using these information-depleted statistics , the mean reaction times predicted by the ( r ) MSPRT in correct trials closely match those of monkeys ( Fig 4a ) . Importantly , this involved no parameter fitting . Instead , we used the fact that for ( r ) MSPRT the mean total information for a decision is constant given error rate and N; this implies that longer decision times could only result from reducing the discrimination information in the evidence . Strikingly , although this information-depletion procedure is based only on data from correct trials , the ( r ) MSPRT now also matches closely the mean reaction times of monkeys from error trials ( Fig 4b ) , which are consistently longer than those of correct trials ( S1 Fig ) . Moreover , for both correct and error trials the ( r ) MSPRT accurately captures the relative scaling of mean reaction time by the number of alternatives ( Fig 4a and 4b ) . The reaction time distributions of the algorithm closely resemble those of monkeys in that they are positively skewed and exhibit shorter right tails for higher coherence levels ( Fig 4c–4f ) . These qualitative features are captured across both correct and error trials , and 2 and 4-alternative tasks . Together , these results support the hypothesis that the primate brain approximates an algorithm similar to the rMSPRT , ‘starved’ of sensory discrimination information . The above shows that the ( r ) MSPRT family of exact inference algorithms can account for the dependence of choice reaction times on task difficulty , trial outcome , and the number of alternatives . But replicating behaviour alone does not tell us if the brain implements a similar computation during decisions . We thus asked whether the inner variables of the rMSPRT could account for the known dynamics of neural activity in cortex and striatum during the dot-motion task . To answer this , we must first map its components to a neural circuit . The rMSPRT is the first probabilistic model of decision able to handle recursion and arbitrary signal delays , which means that in principle it could map to a range of feedback neural circuits . Because cortex [1–5] , basal ganglia [6 , 32] and thalamus [33] have been implicated in decision-making , we sought a mapping that could account for their collective involvement . In the visuo-motor system , MT projects to the lateral intra-parietal area ( LIP ) and frontal eye fields ( FEF ) —two ‘sensorimotor cortex’ areas . The basal ganglia receives topographically organized afferent projections [34] from virtually the whole cortex , including LIP and FEF [35–37] . In turn , the basal ganglia provide indirect feedback to the cortex through thalamus [38 , 39] . This arrangement motivated the feedback embodied in rMSPRT . Multiple parallel recurrent loops connecting cortex , basal ganglia and thalamus can be traced anatomically [38 , 39] . Each loop in turn can be sub-divided into topographically organised parallel loops [39 , 40] . Based on this , we conjecture the transient organization of these circuits into N functional loops , for decision formation , to simultaneously evaluate the possible hypotheses . Our mapping of computations within the rMSPRT to the cortico-basal-ganglia- thalamo-cortical loop is shown in Fig 5 , capturing the most prominent functional features of such circuits . For instance , it has been demonstrated that the striato-nigral and the subthalamo-nigral pathways of the basal ganglia compete during decision formation [41] . The computations predicted by rMSPRT to map on the striatum , subthalamic nucleus , and substantia nigra pars reticulata ( SNr; see S3 Fig ) , provide a qualitative formalization of this phenomenon . Also , negative log-posteriors will tend to decrease for the best supported hypothesis and increase otherwise . This is consistent with the idea of basal ganglia output nuclei ( e . g . SNr ) selectively removing inhibition from a chosen motor program while increasing inhibition of competing ones [17 , 32 , 42 , 43] . Lastly , our mapping of rMSPRT provides an account for the spatially diffuse cortico-thalamic projection [44] , previously unaccounted for by probabilistic models of decision . It predicts that the projection conveys a constantly-increasing , hypothesis-independent baseline that does not affect the inference carried out by the cortico-basal-ganglia-thalamo-cortical loop , but may produce the offset required to facilitate the cortical re-use of inhibitory , fed-back decision information from the basal ganglia ( see S2 Fig ) . This increasing baseline may form part of the hypothesis-independent drive dubbed the “urgency signal” by [31] , revealed after averaging LIP population responses across choices . All this is consistent with current views on the active modulation of information transmitted to the cortex by thalamus [45] . The mapping of rMSPRT to cortico-subcortical circuits produces key , testable predictions . First , that sensorimotor areas like LIP or FEF in the cortex evaluate the plausibility of all available alternatives in parallel , based on the evidence produced by MT , and join this to any initial bias . Second , that as these signals traverse the basal ganglia , they compete , resulting in a decision variable per alternative . Third , that the basal ganglia output nuclei use these to assess whether to make a final choice and what alternative to pick . Fourth , that decision variables are returned to sensorimotor cortex via thalamus , to become a fresh bias carrying all conclusions on the decision so far . The rMSPRT thus predicts that evidence accumulation happens uninterruptedly in the overall , large-scale loop , rather than in a single site . With the mapping above , we can compare the dynamics of rMSPRT computations to those of recorded activity during decision-making in area LIP and striatum . We first consider the dynamics around decision initiation . During the dot motion task , the mean firing rate of LIP neurons deviates from baseline into a stereotypical dip soon after stimulus onset , possibly indicating the reset of a neural integrator [1 , 14] . LIP responses become choice- and coherence-modulated after the dip [1] . This also occurs when firing rates deviate from the initial baseline in striatum , where no dip is exhibited [6] . We therefore reasoned that LIP and striatal neurons engage in decision formation from the bottom of the dip or deviation from baseline ( respectively ) and model their mean firing rate from then on . After this , mean firing rates “ramp-up” for ∼ 40 ms in LIP , then “fork”: they continue ramping-up if dots moved towards the response ( or movement ) field of the neuron ( inRF trials; Fig 6a , solid lines ) or drop their slope if the dots were moving away from its response field ( outRF trials; dashed lines ) [1 , 3] . Striatal neurons exhibit an analogous ramp-and-fork pattern of response ( Fig 7c and 7d ) . The magnitude of LIP firing rate is inversely proportional to the number of available alternatives ( Fig 6a and 6b ) [3 , 46]; a phenomenon also recorded in other visuo-motor sites , notably in the superior colliculus [47] and FEF [48–50] . The model LIP ( sensorimotor cortex ) in rMSPRT captures each of these properties: activity ramps from the start of the accumulation , forks between putative in- and out-RF responses , and scales with the number of alternatives ( Fig 6c ) . Under this model , inRF responses in LIP occur when the likelihood function represented by neurons was best matched by the uncertain MT evidence; correspondingly , outRF responses occur when the likelihood function was not well matched by the evidence . The rMSPRT embodies a mechanistic explanation for the ramp-and-fork pattern in the two cases of Eq 9 . Initial accumulation ( steps 0–2 in our simulations; feedforward inference ) occurs before the feedback has arrived at the model sensorimotor cortex , resulting in a ramp . The forking ( step 3; start of feedback inference ) is the point at which the posteriors from the output of the model basal ganglia first arrive at sensorimotor cortex to be re-used as priors . By contrast , non-recursive MSPRT ( without delayed feedback of posteriors ) predicts well-separated neural signals throughout ( Fig 6e ) . With recursion as the key difference , our framework suggests , first , that the ramp-and-fork pattern gives away the existence of an underpinning delayed inhibitory drive within a looped architecture—here from the model basal ganglia . Second , that the fork represents the time at which updated signals representing the competition between alternatives ( posterior probabilities in the rMSPRT ) are first made available to the sensorimotor cortex . The rMSPRT further predicts that the scaling of activity in sensorimotor sites by the number of alternatives is due to cortico-subcortical loops becoming transiently organized as N parallel functional circuits , one per hypothesis . This would determine the baseline output of the basal ganglia . Until task related signals reach the model basal ganglia output , it codes the initial priors for the set of N hypotheses . Their output is then an increasing function of the number of alternatives ( Fig 6f ) . This increased inhibition of thalamus in turn reduces baseline cortical activity as a function of N . The inverse proportionality of cortical activity to N in macaques during decisions ( Fig 6a and 6b; [3 , 46 , 48 , 49] ) and the direct proportionality of the firing rate to N in their SNr [42] lend support to this hypothesis . The rMSPRT also captures key features of dynamics at decision termination . For inRF trials , the mean firing rate of LIP neurons peaks at or very close to the time of saccade onset ( Fig 6b ) . By contrast , for outRF trials mean rates appear to fall just before saccade onset . The rMSPRT can capture both these features ( Fig 6d ) when we allow the algorithm to continue updating after the decision rule ( Eq 10 ) is met . The decision rule is implemented at the output of the basal ganglia and the model sensorimotor cortex peaks just before the final posteriors have reached it . The rMSPRT thus predicts that the activity in LIP lags the actual decision . This prediction may explain an apparent paradox of LIP activity . The peri-saccadic population firing rate peak in LIP during inRF trials ( Fig 6b ) is commonly assumed to indicate the crossing of a threshold and thus decision termination . Visuo-motor decisions must be terminated well before saccade to allow for the delay in the execution of the motor command , conventionally assumed in the range of 80–100 ms in macaques [9 , 30] . It follows that LIP peaks too close to saccade onset ( ∼ 15 ms before ) for this peak to be causal . The rMSPRT suggests that the inRF LIP peak is not indicating decision termination , but is instead a delayed read-out of termination in an upstream location . In the rMSPRT , the striatum relays the input from sensorimotor cortex as an inhibitory drive for downstream basal ganglia nuclei . The rMSPRT has three free parameters that shape the ramp-and-fork of its inner variables , but do not alter inference . We have set their value to show that mapped variables can match the pattern in sensorimotor cortical neural dynamics ( see Methods ) ; below we show how these predictions depend on the parameter values . Nonetheless , the rMSPRT with these parameters also captures the ramp-and-fork pattern of activity in the monkey striatum ( compare panels c , d to e , f in Fig 7 ) . LIP and striatal firing rates are also modulated by dot-motion coherence ( Fig 7a–7d , 7k , 7l ) . Following stimulus onset , the response of these neurons tends to fork more widely for higher coherence levels ( Fig 7a , 7c and 7k ) [1 , 3 , 6] . The increase in activity before a saccade during inRF trials is steeper for higher coherence levels , reflecting the shorter average reaction times ( Fig 7b , 7d and 7l ) [1 , 3 , 6] . The sensorimotor cortex or striatum in the rMSPRT shows coherence modulation of both the forking pattern ( Fig 7e and 7m ) and slope of activity increase ( Fig 7f and 7n ) . rMSPRT also predicts that the apparent convergence of peri-saccadic LIP activity to a common level during inRF trials ( Fig 7b and 7l ) is not required for inference and so may arise due to additional neural constraints . We take up this point in the Discussion . Our proposed mapping of the rMSPRT’s components ( Fig 5 ) makes testable qualitative predictions for the mean responses in basal ganglia and thalamus during the dot motion task . For the basal ganglia output , likely from the oculomotor regions of the SNr , rMSPRT ( like MSPRT ) predicts a drop in the activity of output neurons during inRF trials and an increase in outRF ones . It also predicts that these changes are more pronounced for higher coherence levels ( Fig 7g , 7h , 7o and 7p ) . These predictions are consistent with recordings from macaque SNr neurons showing that they suppress their inhibitory activity during visually- or memory-guided saccade tasks , in putative support of saccades towards a preferred region of the visual field [42 , 51 , 52] , and enhance it otherwise [52] . In detection tasks like visually- or memory-guided ones , the decision cues are extremely obvious . Hence , the accompanying recorded neural-activity transients may be argued to encode very short evidence-accumulations . After all , the accumulation of a single observation ( e . g . an ISI ) is the simplest , albeit degenerate case of evidence accumulation . For visuo-motor thalamus , rMSPRT predicts that the time course of the mean firing rate will exhibit a ramp-and-fork pattern similar to that in LIP ( Fig 7i , 7j , 7q and 7r ) . The separation of in- and out-RF activity is consistent with the results of [33] who found that , during a memory-guided saccade task , neurons in the macaque medio-dorsal nucleus of the thalamus ( interconnected with LIP and FEF ) , responded more vigorously when the saccade target was flashed within their response field than when it was flashed in the opposite location . Understanding how a neural system implements an algorithm is complicated by the need to identify which features are core to executing the algorithm , and which are imposed by the constraints of implementing computations using neural elements—for example , that neurons cannot have negative firing rates , so cannot straightforwardly represent negative numbers . The three free parameters in the rMSPRT allow us to propose which functional and anatomical properties of the cortico-basal-ganglia-thalamo-cortical loop are workarounds within these constraints , but do not affect inference . One free parameter enforces the baseline activity that LIP neurons maintain before and during the initial stimulus presentation ( Fig 7a and 7k ) . Varying this parameter , l , scales the overall activity of LIP , but does not change the inference performed ( Fig 8a ) . Consequently , this suggests that the baseline activity of LIP depends on N but does not otherwise affect the inference algorithm implemented by the brain . The second free parameter , wyt , sets the strength of the spatially diffuse projection from cortex to thalamus . Varying this weight changes the forking between inRF and outRF computations but does not affect inference ( Fig 8b ) . The third free parameter , n , sets the overall , hypothesis-independent temporal scale at which sampled input ISIs are processed; changing n varies the slope of sensorimotor computations , even allowing all-decreasing mean firing rates ( Fig 8c ) . By definition , the log-likelihood of a sequence tends to be negative and decreases monotonically as the sequence lengthens . Introducing n is required to get positive simplified log-likelihoods , capable of matching the neural activity dynamics , without affecting inference . Hence , n may capture a workaround of the decision-making circuitry to represent these whilst avoiding signal ‘underflow’ , by means of scaling the input data . Traditionally , evidence accumulation is exclusively associated with increasing firing rates during decision , and previous studies have questioned whether the often-observed decision-correlated yet non-increasing firing rates ( e . g . in outRF conditions in Fig 7a , 7c and 7k and [1–3 , 5 , 53 , 54] ) are consistent with accumulation [22 , 23] . The diversity of patterns predicted by rMSPRT in sensorimotor cortex ( Fig 8 ) solves this by demonstrating that both increasing and non-increasing activity patterns can house evidence accumulation . The recursive computation implied by the looped cortico-basal-ganglia-thalamo-cortical architecture has several advantages over local or feedforward computations . First , recursion makes trial-to-trial adaptation of decisions possible . Priors determined by previous stimulation ( fed-back posteriors ) , can bias upcoming similar decisions towards the expected best choice , even before any new evidence is collected . This can shorten reaction times in future familiar settings without compromising accuracy . Second , recursion provides a robust memory . A posterior fed-back as a prior is a sufficient statistic of all past evidence observations . That is , it has taken ‘on-board’ all sensory information since the decision onset . In rMSPRT , the sensorimotor cortex only need keep track of observations in a moving time window of maximum width Δ —the delay around the cortico-subcortical loop— rather than keeping track of the entire sequence of observations . For a physical substrate subject to dynamics and leakage , like a neuron in LIP or FEF , this has obvious advantages: it would reduce the demand for keeping a perfect record ( e . g . likelihood ) of all evidence , from the usual hundreds of milliseconds in decision times to the ∼ 30 ms of latency around the cortico-basal-ganglia-thalamo-cortical loop ( adding up estimates from [55–57] ) . The rMSPRT decides faster than monkeys in the same conditions because monkeys do not make full use of the discrimination information available in their MT ( Fig 3b ) . However , this performance gap arises partially because rMSPRT is a generative model of the task . Thus , this assumes that knowledge of coherence is available by decision initiation , which in turn determines appropriate likelihoods for the task at hand . Any deviation from this generative model will tend to degrade performance , whether it comes from one or more of: the coherence to likelihood mapping [58] , the inherent leakiness of neurons , or correlations between spikes or between neurons ( see [20] ) . In this respect , we must consider , first , that the activity dip ∼ 170 ms after stimulus onset is assumed to indicate decision engagement at the LIP level . By then , MT neurons have been reliably modulated by motion coherence for about 120 ms ( starting ∼ 50 ms after stimulus onset; see S4 Fig for details ) , giving a sizeable window to adjust LIP ‘likelihood functions’ to match the decision at hand . Whether this window is large enough or if trial-by-trial ‘likelihood adjustment’ occurs at all remain as interesting questions for future experimental explorations . Second , that LIP neurons change their coding during learning of the dot motion task and MT neurons do not [59] , implying that learning the task requires mapping of MT to LIP populations by synaptic plasticity [60] . Consequently , even if the MT representation is perfect , the learnt mapping only need satisfice the task requirements , not optimally perform . Excellent matches to monkeys’ performance in both correct and error trials , and hence their speed-accuracy trade-offs , were obtained solely by accounting for lost information in the evidence streams . No noise was added within the rMSPRT itself . Prior experimental work reported perfect , noiseless evidence integration by both rat and human subjects performing an auditory task , attributing all effects of noise on task performance to the variability in the sensory input [61] . Our results extend this observation to primate performance on the dot motion task , and further support the idea that the neural decision-making mechanism can perform perfect integration of uncertain evidence . Neurons in LIP , FEF [4] , and striatum exhibit a ramp-and-fork pattern during the dot motion task . Analogous choice-modulated patterns have been recorded in the medial premotor cortex of the macaque during a vibro-tactile discrimination task [53] and in the posterior parietal cortex and frontal orienting fields of the rat during an auditory discrimination task [5] . The rMSPRT indicates that such slow dynamics emerge from decision circuits with a delayed , inhibitory drive within a looped architecture . This suggests that decision formation in mammals may use a common recursive computation . A random dot stimulus pulse delivered earlier in a trial has a bigger impact on LIP firing rate than a later one [2] . This highlights the importance of capturing the initial , early-evidence ramping-up before the forking . However , multiple models omit it , focusing only on the forking ( e . g . [9 , 10 , 13] ) . Other , heuristic models account for LIP activity from the onset of the choice targets , through dots stimulation and up until saccade onset ( e . g . [12 , 14–16] ) . Nevertheless , their predicted firing rates rely on two fitted heuristic signals that shape both the post-stimulus dip and the ramp-and-fork pattern . In contrast , the ramp-and-fork dynamics emerge naturally from the delayed inhibitory feedback in rMSPRT during decision formation . rMSPRT qualitatively replicates the ramp-and-fork pattern for individual coherence levels and given number of alternatives , N ( Fig 6 ) . However , the peak of the accumulated evidence in the model sensorimotor cortex of rMSPRT does not converge to a common value around decision termination during inRF trials . Consequently , it predicts that the apparent convergence of LIP activity to a common value ( Figs 6b and 7b and 7l ) is not part of the inference procedure , but reflects other constraints on neural activity . One such constraint is that these brain regions engage in multiple other computations , some of which are likely orthogonal to solving the random dot motion task . The neural activity recorded during decision tasks may then be a transformation of inference computations , by mixing them with all other simultaneous computations . Consistent with this , the successful fitting of previous computational models to neural data [12 , 14–16] has been critically dependent on the addition of heuristic signals for unknown constraints . While beyond the scope of this study , which examined whether a normative mechanism could explain behaviour and electrophysiology during decisions , adding similar heuristic signals to the rMSPRT would likely allow a quantitative reproduction of the peri-saccadic convergence of LIP activity . Inputs to the rMSPRT were determined solely from MT responses during the dot-motion task , and it has only three free parameters , none of which affect inference . It is thus surprising that it renders emergent predictions that are consistent with experimental data . First , our information-depletion procedure used exclusively statistics from correct trials . Yet , after depletion , rMSPRT matches monkey behaviour in correct and error trials ( Fig 4 ) , suggesting a mechanistic connection between them in the monkey that is naturally captured by rMSPRT . Second , the values of the three free parameters were chosen solely so that the model LIP activity resembled the ramp-and-fork pattern observed in our LIP data-set ( Fig 6a and 6c ) . As demonstrated in Fig 8 , the ramp-and-fork pattern is a particular case of two-stage patterns that are an intrinsic property of the rMSPRT , guaranteed by the feedback of the posterior after the delay Δ has elapsed ( Eq 5 ) . Nonetheless , the algorithm also qualitatively matches LIP dynamics when aligned at decision termination ( Fig 6b and 6d ) . Third , the predictions of the time course of the firing rate in SNr and thalamic nuclei naturally emerge from the functional mapping of the algorithm onto the cortico-basal-ganglia-thalamo-cortical circuitry . These are already congruent with existing electrophysiological data; however , their full verification awaits recordings from these sites during the dot motion task . These and other emergent predictions are an encouraging indicator of the explanatory power of a systematic framework for understanding decision formation , embodied by the rMSPRT . The rMSPRT contains all previous instances of the MSPRT [17 , 18 , 25 , 26 , 62] as special cases . It generalizes them by allowing the re-use of posteriors at any given time in the past as priors for present inference , via recursion . The ( r ) MSPRT also contains the sequential probability ratio test when N = 2 , and its continuous-time equivalent , the popular drift-diffusion model ( e . g . [4 , 6 , 9 , 61 , 63–66] ) . While a valuable basic model of decision-making , the drift-diffusion model is restricted to N = 2 alternatives and does not address neural mechanisms . First , it assumes that evidence for decisions comes as a continuous Gaussian process whose presence in the brain is unproven . Since the decision times predicted by the model critically hinge on this process and its statistics ( typically disconnected from the statistics of sensory neural activity ) , this limitation also obscures the interpretation of the drift-diffusion model’s behavioural predictions . Second , its single decision variable must restrict itself to the half-plane closest to the choice threshold associated to one of its two hypotheses if such hypothesis is to be chosen; hence , the drift-diffusion model can account for forking dynamics , but not for the preceding ramping observed in experimental data . In contrast , the rMSPRT natively captures decisions among any number of alternatives ( N ≥ 2 ) , can explain ramp-and-fork dynamics , and does so using neural evidence for decisions in its natural format: spike-trains with statistics extracted from MT recordings . Biophysical models that directly address neural implementations of decision making are predominantly based on winner-take-all competition between neurons representing different hypotheses [8 , 11–14 , 16 , 67 , 68] . These provide valuable insights into potential mechanisms by which neural circuits can represent and compute decisions , but do not typically make contact with formal inference procedures ( see [69] ) . The studies of [13 , 68] are possible exceptions , since they make the analogy between the predictions of their neural-network model and those of exact , Bayes-based inference . Conversely , the rMSPRT shows how a normative decision-making algorithm can account for cortical and subcortical activity . As such , the rMSPRT provides target , exact-inference computations for future biophysical models . Mapping any formal algorithm to a neural substrate implies proposing assumed computational contributions for the components of the substrate . In mapping the rMSPRT we made two broad classes of assumptions . First , as explained above , that individual substrates implement multiple functions either simultaneously or under different stimulation scenarios ( e . g . experimental paradigms ) . In particular , we assume that during decision-formation the striatum is only required to perform a light-touch , relay-like transformation of its excitatory cortical inputs into inhibitory outputs . This assumption is shared by multiple models of the basal ganglia ( e . g . [70 , 71] ) . The similarity between ramp-and-fork patterns of response across neurons in the LIP [3] , FEF [4] , and striatum [6] during the dot-motion task , is consistent with this ( Fig 7a–7d ) . That said , computational models have shown how the striatum’s intricate microcircuit [72] can give rise to several types of complex responses to simple cortical input , often taking the form of spontaneously appearing neural ensembles [73–75] . Thus a promising avenue for future research is determining if , and how , the dynamics of the striatal micro-circuit can act as a relay-like function during decision formation . Our second class of assumptions is that the omitted connections into and within the basal ganglia may not contribute to the computations essential to inference with cortical inputs . Of note , we have omitted in our mapping the projections from thalamus to striatum [76] or to subthalamic nucleus [77] , as well as the intrinsic connections from subthalamic nucleus or from globus pallidus pars externa ( globus pallidus in non-primates ) to striatum ( e . g . see [77 , 78] ) . Such omitted connections might offer a more robust implementation of inference computations , or may contribute to overcoming the limitations of implementing an algorithm with neurons . Demonstrating the compatibility of anatomical pathways with the mapping of the ( r ) MSPRT is the subject of ongoing research . Success has been achieved in the expansion of the basal-ganglia mapping of the MSPRT to include the pathway from striatum to globus pallidus pars externa and that from the latter to SNr , where the same inference could be done without those pathways [17] . It has also been recently shown that the pallido-striatal connection is compatible with the MSPRT mapping onto the basal ganglia [21] , possibly giving a more robust neural implementation . Both results carry to the rMSPRT . In the same bracket is our inclusion of the cortico-thalamic projection here ( Fig 5 ) . Since this projection is assumed to be hypothesis-independent ( Eq 12 ) , it does not affect the inference done by the rMSPRT . Similar exercises may be able to account for projections from thalamus to striatum or to subthalamic nucleus , and from the latter to striatum , though these are beyond the scope of this study . The rMSPRT provides a starting point to explore all such extended mapping alternatives . We sought to characterize the neural mechanism that underlies decisions using a normative algorithm—the rMSPRT—as a framework . We find it remarkable that , starting from data-constrained spike-trains , our monolithic statistical test can simultaneously account for much of the anatomy , behaviour , and electrophysiology of decision-making . While it is not plausible that the brain implements exactly a specific algorithm , our results suggest that the essential composition of its underlying decision mechanism includes the following . First , that the mechanism is probabilistic in nature—the brain utilizes the uncertainty in neural signals , rather than suffering from it . Second , that the mechanism works entirely ‘on-line’ , continuously updating representations of hypotheses that can be queried at any time to make a decision . Third , that this processing is distributed , recursive , and parallel , producing a decision variable for each available hypothesis . And fourth , that this recursion allows the mechanism to adapt to the observed statistics of the environment in an unsupervised manner , as it can re-use updated probabilities about hypotheses as priors for upcoming decisions . With the currently available range of experimental studies giving us local snapshots of cortical and subcortical activity during decision-making tasks , the rMSPRT shows us how , where , and when these snapshots fit into a complete inference procedure . Behavioural and neural data was collected in three previous studies [3 , 6 , 24] , during two versions of the random dot motion task ( Fig 1a–1c ) . Detailed experimental protocols can be found in each report . Below we briefly summarize them . For comparability across databases , we only analysed data from trials with coherence levels of 3 . 2 , 6 . 4 , 12 . 8 , 25 . 6 , and 51 . 2% , unless otherwise stated . We used data from all neurons recorded in such trials . Our datasets contained between 189 and 213 visual-motion-sensitive MT neurons ( see Table 1; single-cell recordings from [24 , 79] ) , as well as 19 LIP neurons ( data from [3] ) and 48 striatal ones ( from [6] ) whose activity was previously determined to be choice- and coherence-modulated . The behavioural data analysed was that associated to LIP recordings . For MT , we analysed the neural activity between the onset and the vanishing of the stimulus . For LIP and striatum we focused on the period between 100 ms before stimulus onset and 100 ms after saccade onset . To estimate moving statistics of neural activity we first computed the spike count over a 20 ms window sliding every 1 ms , per trial . The moving mean firing rate per neuron per condition was then the mean spike count over the valid bins of all trials divided by the width of this window; the standard deviation was estimated analogously . LIP and striatal recordings were either aligned at the onset of the stimulus or of the saccade; after or before these ( respectively ) , data was only valid for a period equal to the reaction time per trial . The population moving mean firing rate is the mean of single-neuron moving means over valid bins; analogously , the population moving variance of the firing rate is the mean of single neuron moving variances . For clarity , population statistics were then smoothed by convolving them with a Gaussian kernel with a 10 ms standard deviation . The resulting smoothed population moving statistics for MT are in Fig 1d and 1e . LIP and striatal mean firing rates are plotted only up to the median reaction time plus 80 ms , per condition . Analogous procedures were used to compute the moving mean of the computations within simulated algorithms , per time step , rather than over a moving window . These are shown up to the median of termination observations plus 3 time steps . Let x ( t ) = ( x1 ( t ) , … , xC ( t ) ) be a vector random variable composed of scalar observations , xj ( t ) , made in C channels at time t ∈ {1 , 2 , …} ( right-hand side of Fig 9 ) . Let also x ( r: t ) = ( x ( r ) /n , … , x ( t ) /n ) be the sequence of vectors x ( t ) /n , i . i . d . across time , from r to t ( r < t ) . Here n ∈ { R > 0 } is a constant data scaling factor . If n > 1 , it scales down incoming data , xj ( t ) ; this will prove useful ahead when tuning the algorithm to reveal that the dynamics in rMSPRT computations match those of sensorimotor cortex . Note that scaling is only effective from the likelihood on and does not affect the time interpretation of the data . Crucially , since n is hypothesis-independent , it does not affect inference . There are N ∈ {2 , 3 , …} alternatives or hypotheses about the uncertain evidence , x ( 1: t ) —say possible courses of action or perceptual interpretations of sensory data . The task of a decision maker is to determine which hypothesis Hi ( i ∈ {1 , … , N} ) is best supported by this evidence as soon as possible , for a given level of accuracy . To do this , it requires to estimate the posterior probability of each hypothesis given the data , P ( Hi|x ( 1: t ) ) , as formalized by Bayes’ rule . The mechanism we seek must be recursive to match the nature of the brain circuitry . Formally , P ( Hi|x ( 1: t ) ) will be initially computed upon starting priors P ( Hi ) and likelihoods P ( x ( 1: t ) |Hi ) ; however , after some time Δ ∈ {1 , 2 , …} , it will re-use past posteriors , P ( Hi|x ( 1: t − Δ ) ) , Δ time steps ago , as priors , along with the likelihood function P ( x ( t − Δ + 1: t ) |Hi ) of the segment of x ( 1: t ) not yet accounted by P ( Hi|x ( 1: t − Δ ) ) . A mathematical induction proof of this form of Bayes’ rule follows . If say Δ = 2 , in the first time step , t = 1: P ( H i | x ( 1 ) / n ) = P ( x ( 1 ) / n | H i ) P ( H i ) P ( x ( 1 ) / n ) ( 1 ) By t = 2: P ( H i | x ( 2 ) / n , x ( 1 ) / n ) = P ( x ( 2 ) / n , x ( 1 ) / n | H i ) P ( H i ) P ( x ( 2 ) / n , x ( 1 ) / n ) Note that we are still using the initial fixed priors P ( Hi ) . Now , for t = 3: P ( H i | x ( 3 ) / n , x ( 2 ) / n , x ( 1 ) / n ) = P ( x ( 3 ) / n , x ( 2 ) / n , x ( 1 ) / n | H i ) P ( H i ) P ( x ( 3 ) / n , x ( 2 ) / n , x ( 1 ) / n ) ( 2 ) According to the product rule , we can segment the probability of the sequence x ( 1: t ) as: P ( x ( 1 : t ) ) = P ( x ( t − Δ + 1 : t ) , x ( 1 : t − Δ ) ) = P ( x ( t − Δ + 1 : t ) | x ( 1 : t − Δ ) ) P ( x ( 1 : t − Δ ) ) ( 3 ) And , since x ( t ) are i . i . d . , the likelihood of the two segments is: P ( x ( 1 : t ) | H i ) = P ( x ( t - Δ + 1 : t ) | H i ) P ( x ( 1 : t - Δ ) | H i ) ( 4 ) If we substitute the likelihood in Eq 2 by Eq 4 , its normalization constant by Eq 3 and re-group , we get: P ( H i | x ( 3 ) / n , x ( 2 ) / n , x ( 1 ) / n ) = ( P ( x ( 3 ) / n , x ( 2 ) / n | H i ) P ( x ( 3 ) / n , x ( 2 ) / n | x ( 1 ) / n ) ) ( P ( x ( 1 ) / n | H i ) P ( H i ) P ( x ( 1 ) / n ) ) It is evident that the rightmost factor is P ( Hi|x ( 1 ) /n ) as in Eq 1 . Hence , in this example , by t = 3 we start using past posteriors as priors for present inference as: P ( H i | x ( 3 ) / n , x ( 2 ) / n , x ( 1 ) / n ) = P ( x ( 3 ) / n , x ( 2 ) / n | H i ) P ( H i | x ( 1 ) / n ) P ( x ( 3 ) / n , x ( 2 ) / n | x ( 1 ) / n ) So , in general: P ( H i | x ( 1 : t ) ) = { P ( x ( 1 : t ) | H i ) P ( H i ) P ( x ( 1 : t ) ) for t ≤ Δ P ( x ( t - Δ + 1 : t ) | H i ) P ( H i | x ( 1 : t - Δ ) ) P ( x ( t - Δ + 1 : t ) | x ( 1 : t - Δ ) ) for t > Δ ( 5 ) where the normalization constants are P ( x ( 1 : t ) ) = ∑ j = 1 N P ( x ( 1 : t ) | H j ) P ( H j ) P ( x ( t - Δ + 1 : t ) | x ( 1 : t - Δ ) ) = ∑ j = 1 N P ( x ( t - Δ + 1 : t ) | H j ) P ( H j | x ( 1 : t - Δ ) ) Eq 5 is a general recursive form of the Bayes’ rule , designed to accumulate evidence for inference in a recurrent , uninterrupted fashion . By t > Δ , it uses posteriors Δ ≥ 1 time steps in the past as current priors , thereby generalizing a previous common recursive form of the Bayes’ rule that is limited to Δ = 1 ( that in e . g . [18 , 26 , 68 , 80 , 81] ) . Priors updated in this manner are a sufficient statistic of all the evidence observed up to t − Δ . By this ability , and in the general machine-learning sense , any decision algorithm harnessing Eq 5 adapts or learns . Since no labelled examples or teaching signals are required for such learning , the rMSPRT is thence said to be engaged in ongoing unsupervised learning . Ahead we use three key results from [20] as part of our methods , with no overlap between their results and the results of the present study . First , a lognormal-based form of the likelihood function whose component operations they showed are neurally plausible and most consistent with the statistics of MT responses during the random dots task . Second , a crucial link between the statistics of ISIs in the spike-trains used as evidence for decision ( e . g . those of MT during the dots task ) , and continuously-distributed MSPRT decision times . As discussed below , this link enabled us to use simpler , discrete-time algorithms and still interpret their behavioural predictions in continuous time . And third , the fundamental dependence of MSPRT decision times on: ( a ) the discrimination information available in the evidence and ( b ) a constant , fixed for given error rate and N . Since rMSPRT performs identically to MSPRT , all this carries to it . It is apparent that the critical computations in Eq 5 are the likelihood functions . The forms that we consider ahead build upon the simplest shown by [20] , where the number of evidence streams equals the number of hypotheses ( C = N ) ; for instance , a minimum of C = 2 differently-tuned neurons are assumed to provide evidence for a N = 2 choice decision . As discussed by them , more complex ( C > N ) , biologically-plausible likelihood functions can be formulated if necessary; the C < N case would make no sense as it would imply the testing of redundant hypotheses . Although not essential , to simplify the notation when C = N , from now on data in the channel conveying the most salient evidence for hypothesis Hi will bear its same index i , as xi ( j ) . When t ≤ Δ we have: P ( x ( 1 : t ) | H i ) = a ( t ) ∏ j = 1 t f * ( x i ( j ) / n ) f 0 ( x i ( j ) / n ) ( 6 ) this is , the likelihood that xi ( j ) /n was drawn from a distribution , f* , rather than from f0 , that is assumed to have originated xk ( j ) /n ( k ≠ i ) for the rest of the channels . In Eq 6 , a ( t ) = ∏ m = 1 t ∏ k = 1 N f 0 ( x k ( m ) / n ) is a hypothesis-independent factor that does not affect Eq 5 and thus needs not to be considered further . When t > Δ only the observations in the time window [t − Δ + 1 , t] are used for the likelihood function because data before this window is already considered within the fed-back posterior , P ( Hi|x ( 1: t − Δ ) ) . Then , the likelihood function is: P ( x ( t - Δ + 1 : t ) | H i ) = d ( t ) ∏ j = t - Δ + 1 t f * ( x i ( j ) / n ) f 0 ( x i ( j ) / n ) ( 7 ) where again d ( t ) = ∏ m = t - Δ + 1 t ∏ k = 1 N f 0 ( x k ( m ) / n ) needs not to be considered further . Now , for our likelihood functions to work upon a statistical structure like that produced by neurons in MT we need to be more specific . Inter-spike intervals ( ISI ) in MT during the random dot motion task are best described as lognormally distributed [20] and we assume that decisions are made upon the information conveyed by them . Thus , from now on we assume that f* and f0 are lognormal and that they are specified by means μ* and μ0 , and standard deviations σ* and σ0 , respectively . We can then put together the logarithm of Eqs 6 and 7 as the log-likelihood function , yi ( t ) , substituting the lognormal-based form of it reported by [20]: yi ( t ) ={g0Δ+g1∑j=1t[ log ( xi ( j ) /n ) ]2+g2∑j=1tlog ( xi ( j ) /n ) fort≤Δg0Δ+g1∑j=t−Δ+1t[ log ( xi ( j ) /n ) ]2+g2∑j=t−Δ+1tlog ( xi ( j ) /n ) fort>Δ ( 8 ) with g 0 = κ 0 2 2 Θ 0 2 - κ * 2 2 Θ * 2 + log ( Θ 0 Θ * ) g 1 = 1 2 Θ 0 2 - 1 2 Θ * 2 g 2 = κ * Θ * 2 - κ 0 Θ 0 2 where κ = log ( μ 2 / σ 2 + μ 2 ) and Θ2 = log ( σ2/μ2 + 1 ) with appropriate subindices * , 0 . The terms g0Δ in Eq 8 are hypothesis-independent , can be absorbed into a ( t ) and d ( t ) , correspondingly , and thus will not be considered further . As a result of this , the yi ( t ) used from now on is a “simplified” version of the log-likelihood . We now take the logarithm of Eq 5 , define −log Pi ( t ) ≡ −log P ( Hi|x ( 1: t ) ) and substitute the simplified log-likelihood from Eq 8 in the result , giving: - log P i ( t ) = { - z i ( t ) - log P ( H i ) + log ∑ j = 1 N exp ( z j ( t ) + log P ( H j ) ) for t ≤ Δ - z i ( t ) - log P i ( t - Δ ) + log ∑ j = 1 N exp ( z j ( t ) + log P j ( t - Δ ) ) for t > Δ ( 9 ) Where zi ( t ) = yi ( t ) + c ( t ) and the term c ( t ) models a hypothesis-independent baseline . Because of its uniformity across all hypotheses , c ( t ) has no effect on inference . It is defined in detail below . The rMSPRT itself takes the form: D ( t ) = { Choose hypothesis i : if - log P i ( t ) = min j ∈ { 1 , … , N } - log P j ( t ) ≤ θ , at t = T Continue sampling : if min j ∈ { 1 , … , N } - log P j ( t ) > θ , ( 10 ) where D ( t ) is the decision at the discretely distributed time t , θ ∈ ( 0 , −log ( 1/N ) ] is a constant threshold , and T is the decision termination time . Alternatively , an individual threshold per hypothesis can be set as {θ1 , … , θN} , giving a more general formulation . According to our mapping of rMSPRT to the cortico-subcortical loops ( Fig 5 ) , the sensorimotor cortex baseline , c ( t ) ( Eq 9 ) , delayed with respect of the output of the model basal ganglia , is: c ( t + δ y b ) = h ( t - δ b u - δ u y ) + l ( 11 ) It houses a constant baseline l and the thalamo-cortical contribution h ( t − δbu − δuy ) , which in turn is the delayed cortical input to the thalamus h ( t - δ b u ) = w y u ∑ i = 1 N ( z i ( t + δ y b - δ y u ) + log P i ( t - δ b u - δ u y - δ y u ) ) N ( 12 ) Here we have chosen h ( t − δbu ) to be a scaled average of cortical contributions; nevertheless , any other hypothesis-independent function of them can be picked instead if necessary . It would thus not affect inference and render similar results . The definitions above introduce two free parameters l ∈ R + and wyu ∈ [0 , 1 ) that have the purpose of shaping the dynamics of the computations within rMSPRT during decision formation . The range of wyu ensures that the value of computations in the cortico-thalamo-cortical , positive-feedback loop is not amplified to the point of disrupting inference in the overall loop . Crucially , since both parameters are hypothesis-independent , none affects inference . For rMSPRT decisions to be comparable to those of monkeys , they must exhibit the same error rate , ϵ ∈ [0 , 1] . Error rates are taken to be an exponential function of coherence ( % ) , s , fitted by non-linear least squares ( R2 > 0 . 99 ) to the behavioural psychometric curves from the analysed LIP database , including 0 , 9 , and 72 . 4% coherence for this purpose . This resulted in: ϵ = { 0 . 50 exp ( - 0 . 11 s ) , for N = 2 0 . 75 exp ( - 0 . 08 s ) , for N = 4 ( 13 ) Since monkeys are trained to be unbiased regarding choosing either target , initial priors for rMSPRT are set flat ( P ( Hi ) = 1/N for all i ) in every simulation . During each Monte Carlo experiment , rMSPRT made decisions with error rates from Eq 13 . The value of the threshold , θ , was iteratively found to satisfy ϵ per condition . Decisions were made over data , xj ( t ) /n , randomly sampled from lognormal distributions specified for all channels by means and standard deviations μ0 and σ0 , respectively; the exception was a single channel where the sampled distribution was specified by μ* and σ* . This models the fact that MT neurons respond more vigorously to visual motion in their preferred direction compared to motion in a null direction , e . g . against the preferred . As explained in Fig 9 , this effectively simulates macaque MT neural activity during the random dot motion task . The same parameters were used to specify likelihood functions per experiment . We have defined rMSPRT to operate over a discrete time line; however , the brain operates over continuous time . [20] introduced a continuous-time generalization of MSPRT that uses spike-trains as inputs for decision . Thence , the length of ISIs is random and their sum up until decision is , by definition , a continuously distributed time . With all other assumptions equal , they demonstrated that , as an average , the traditional discrete-time MSPRT requires about the same number of observations to decision ( discretely distributed ) , as the maximum number of ISIs among input channels , required by the more general spike-based MSPRT ( also discretely distributed yet occurring over continuous time; Fig 9 ) . This has two key implications . First , that continuous-time spike-trains can be substituted as decision evidence for ( r ) MSPRT by discrete-time stochastic processes—like x ( r: t ) here—as long as their distributions and the statistics that specify them remain equal; with this we gain efficiency on the implementation of discrete- versus continuous-time algorithms in digital computers , as well as simplicity on their analysis and interpretation . Second , and most important to compare the rMSPRT’s performance to experimentally-measured behaviour , that the ( discretely distributed ) number of observations to decision , T , in ( r ) MSPRT has an interpretation as continuously-distributed time . In brief , simulating decision evidence in discrete-time for ( r ) MSPRT as defined here is a simpler , equivalent way to simulate decisions made on the basis of continuous-time spike-trains . In light of this , the expected decision sample size for correct choices , 〈T〉c , required by the ( r ) MSPRT , can be interpreted as the mean decision time τc= ( 〈T〉c+0 . 5 ) μ*n ( 14 ) predicted by the more general continuous-time , spike-based MSPRT , where μ*n is the mean ISI produced by a MT neuron whose preferred motion direction was matched by the stimulus and was thus firing the fastest on average ( Fig 9 ) . When the mean firing rate to a preferred characteristic of the stimulus is larger than that to a non-preferred one ( μ* < μ0 ) —as in MT [24] , middle-lateral , and anterolateral auditory cortex [66]—the hypothesis selected in error trials is that misinformed by channels with mean μ0n which intuitively happened to fire faster than those whose mean was actually μ*n . Hence , the mean decision time predicted by rMSPRT in error trials would be: τe= ( 〈T〉e+0 . 5 ) μ0n , ( 15 ) where 〈T〉e is the mean decision sample size for error trials . An instance of rMSPRT capable of making choices upon sequences of spike-trains is straightforward from the formal framework above and that introduced by [20]; nevertheless , as said , for simplicity here we choose to work with the discrete-time rMSPRT . After all , thanks to Eqs 14 and 15 we can still interpret its behaviour-relevant predictions in terms of continuous time . These are used to compute decision times throughout . We outline here how we use the monkeys’ reaction times on correct trials and the properties of the rMSPRT , to estimate the amount of discrimination information lost by the animals . That is , the gap between all the information available in the responses of MT neurons , as fully used by the rMSPRT ( parameter set Ω ) , and the fraction of such information actually used by monkeys . The expected number of observations to reach a correct decision for ( r ) MSPRT , 〈T〉c , depends on two quantities . First , the mean total discrimination information required for the decision , I ( ϵ , N ) , that depends only on the error rate , ϵ , and N . Second , the ‘distance’ between distributions of ISIs from MT neurons that are simultaneously contributing evidence for decision , while visual motion matches the tuning of some and not others ( e . g . red versus black in Fig 9 ) . This distance is the Kullback-Leibler divergence from f* to f0 K = ∫ x f * ( x ) log 2 ( f * ( x ) f 0 ( x ) ) d x which measures the discrimination information available between the distributions . Using these two quantities , the decision time in the ( r ) MSPRT is [20]: 〈 T 〉 c ≥ I ( ϵ , N ) K , ( 16 ) The product of our Monte Carlo estimate of 〈T〉c in the rMSPRT ( Fig 3a in the Results ) and K from the MT ISI distributions ( Fig 1f ) , gives an estimate of the limit I ( ϵ , N ) in expression 16 , denoted by I ^ ( ϵ , N ) . The ‘mean decision sample size’ of monkeys—hence the superscript m—within this framework corresponds to 〈 T ^ 〉 c m = ( τ ^ c m / μ * n ) - 0 . 5 ( from Eq 14 ) . Here , τ ^ c m is the estimate of the mean decision time of monkeys for correct choices , per condition; that is , the reaction time from Fig 3a minus some constant non-decision time . With 〈 T ^ 〉 c m and I ^ ( ϵ , N ) , we can estimate the corresponding discrimination information available to the monkeys in this framework as K ^ m = I ^ ( ϵ , N ) / 〈 T ^ 〉 c m ( from expression 16 ) . Fig 3b compares K ( red line ) to K ^ m ( blue/green lines and shadings ) for monkeys , using non-decision times in a plausible range of 200–300 ms . Fig 3c shows the discrimination information lost by monkeys as the percentage of K , [ 1 - ( K ^ m / K ) ] × 100 % . Expression 16 implies that the reaction times predicted by rMSPRT should match those of monkeys if we make the algorithm lose as much information as the monkeys did . We did this by producing a new parameter set that brings f0 closer to f* per condition , assuming 250 ms of non-decision time; critically , simulations like those in Fig 4 will give about the same rMSPRT reaction times regardless of the non-decision time chosen , as long as it is the same assumed in the estimation of lost information and this information-depletion procedure . An example of the results of information depletion in one condition is in Fig 3d . We start with the original parameter set extracted from MT recordings , Ω ( ‘preferred’ and ‘null’ densities in Fig 3d ) , and keep μ* and σ* fixed . Then , we iteratively reduce or increase the differences |μ0 − μ*| and |σ0 − σ*| by the same proportion , until we get new parameters μ0 and σ0 that , together with μ* and σ* , specify preferred ( ‘preferred’ in Fig 3d ) and null ( ‘new null’ ) density functions that bear the same discrimination information estimated for monkeys , K ^ m; hence , they exactly match the information loss in the solid lines in Fig 3c . Intuitively , since the ‘new null’ distribution in Fig 3d is more similar to the ‘preferred’ one than the ‘null’ , the Kullback-Leibler divergence between the first two is smaller than that between the latter two . The resulting parameter set is dubbed Ωd and reported in Table 1 . Note that this is not a fitting procedure , which would be merely descriptive . Instead , information depletion takes advantage of the properties of the ( r ) MSPRT to describe the data , but also to predict that the longer decision times of monkeys are explained by a reduction in the discrimination information in the streams of decision evidence . The slight deviation of the mean reaction times of ( r ) MSPRT vs those of monkeys in Fig 4a stems from the expression 16 being an inequality . Due to this , I ^ ( ϵ , N ) is a likely over-estimate of I ( ϵ , N ) . Dividing I ^ ( ϵ , N ) by 〈 T ^ 〉 c m hence gives an over-estimate of the monkey discrimination information , K ^ m . If then rMSPRT uses statistics consistent with this over-estimated K ^ m , it renders under-estimated reaction times . This residual discrepancy can be corrected by further multiplying K ^ m , per condition , by the corresponding ratio of the decision time of the model over that of the monkey , from Fig 4a . Repeating the simulations with the implied parameter set would trivially render rMSPRT reaction times that more exactly match those of monkeys . This will likely carry with it a better match in error trials , which is unconstrained in the procedure . Nonetheless , this exercise gives us the information loss associated to such enhanced match , shown in Fig 3c as dashed lines for a 250 ms non-decision time ( compare to solid lines ) ; this constitutes a further refined measure of the minimum information lost by the animals according to our framework .
Decision-making is central to cognition . Abnormally-formed decisions characterize disorders like over-eating , Parkinson’s and Huntington’s diseases , OCD , addiction , and compulsive gambling . Yet , a unified account of decision-making has , hitherto , remained elusive . Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions , to the knowable function of a novel statistical inference algorithm . Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain , replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it . Validated in this way , our algorithm establishes a basic framework for understanding the mechanistic ingredients of decision-making in the brain , and thereby , a basic platform for understanding how pathologies arise from abnormal function .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "methods" ]
[ "medicine", "and", "health", "sciences", "decision", "making", "reaction", "time", "brain", "vertebrates", "social", "sciences", "neuroscience", "animals", "mammals", "primates", "cognitive", "neuroscience", "cognitive", "psychology", "cognition", "monkeys", "animal", "cells", "basal", "ganglia", "neostriatum", "thalamus", "cellular", "neuroscience", "psychology", "eukaryota", "cell", "biology", "anatomy", "neurons", "biology", "and", "life", "sciences", "cellular", "types", "cognitive", "science", "amniotes", "organisms" ]
2018
A probabilistic, distributed, recursive mechanism for decision-making in the brain
White coat color has been a highly valued trait in horses for at least 2 , 000 years . Dominant white ( W ) is one of several known depigmentation phenotypes in horses . It shows considerable phenotypic variation , ranging from ∼50% depigmented areas up to a completely white coat . In the horse , the four depigmentation phenotypes roan , sabino , tobiano , and dominant white were independently mapped to a chromosomal region on ECA 3 harboring the KIT gene . KIT plays an important role in melanoblast survival during embryonic development . We determined the sequence and genomic organization of the ∼82 kb equine KIT gene . A mutation analysis of all 21 KIT exons in white Franches-Montagnes Horses revealed a nonsense mutation in exon 15 ( c . 2151C>G , p . Y717X ) . We analyzed the KIT exons in horses characterized as dominant white from other populations and found three additional candidate causative mutations . Three almost completely white Arabians carried a different nonsense mutation in exon 4 ( c . 706A>T , p . K236X ) . Six Camarillo White Horses had a missense mutation in exon 12 ( c . 1805C>T , p . A602V ) , and five white Thoroughbreds had yet another missense mutation in exon 13 ( c . 1960G>A , p . G654R ) . Our results indicate that the dominant white color in Franches-Montagnes Horses is caused by a nonsense mutation in the KIT gene and that multiple independent mutations within this gene appear to be responsible for dominant white in several other modern horse populations . Dominant white ( W ) is an autosomal dominant trait that is characterized by coat depigmentation of variable extent . Caused by the absence of melanocytes from the depigmented skin areas , expressivity can range from ∼50% depigmented areas up to a nearly completely white coat . In contrast to horses with grey coat color ( G ) , which are characterized by progressive greying of the hair , white horses show the depigmentation at birth and have a depigmented skin . Eyes are normally pigmented in dominant white horses , probably due to the different origin of the retinal melanocytes , which develop from local neuroectoderm and not from the neural crest , as do the skin melanocytes . In various horse breeds , cases of white or almost white horses born out of solid-colored parents have been reported [1] . Some breed registries have restrictions towards this phenotype , or do not allow the phenotype to be registered . In the Franches-Montagnes Horse population white horses are known and reported to trace back to the white founder mare Cigale , born in 1957 [2] . The Camarillo White Horses , which have a similar depigmentation phenotype , represent another famous line of horses that can be traced back to the white founder stallion Sultan , born in 1912 [3] . According to anecdotal reports from breeders , the dominant white phenotype appears to have originated independently on several occasions in Thoroughbreds . The white coat color phenotype is inherited as a monogenic autosomal dominant trait . In one study , white horses were shown to be obligate heterozygous ( W/+ ) , as the W/W genotype was hypothesized to cause early embryonal lethality [4] . In horses , the four depigmentation phenotypes roan , sabino-1 , tobiano , and dominant white were independently mapped to a region on equine Chromosome 3 ( ECA 3 ) harboring the KIT gene [2 , 5–7] . The sabino-1 spotting pattern is caused by an intronic mutation in the KIT gene , which causes partial skipping of exon 17 [6] . The tobiano spotting pattern is caused by a large chromosomal inversion that disrupts a potential regulatory element downstream of the KIT gene [7] . In contrast to sabino and tobiano , the mutations for roan and dominant white have been reported to cause lethality in the homozygous state in some horse breeds [4 , 8] . KIT is a type III receptor protein-tyrosine kinase and belongs to a protein subfamily including the colony stimulating factor-1 receptor ( CSF1R ) , platelet-derived growth factor receptor ( PDGFR ) , and fms-related tyrosine kinase 3 ( FLT3 ) . KIT contains an extracellular domain composed of five immunoglobulin domains , a single transmembrane domain , a juxtamembrane domain , and an intracellular protein kinase domain that is interrupted by an insertion of about 80 amino acids [9] . The KIT ligand ( KITL ) , also called stem cell factor ( SCF ) , binds to KIT via the second and third extracellular immunoglobulin domains . Ligand binding induces receptor dimerization , thereby activating the intrinsic tyrosine kinase domain through transphosphorylation and further signal transduction [10] . KIT has the potential to participate in multiple signaling pathways , which accounts for its important role in the control of cell differentiation , proliferation , survival , and motility . A complete loss of function of KIT causes prenatal or perinatal lethality due to anemia [11] . KIT signaling is crucial for the development and survival of melanoblasts , mast cells , spermatogonia , and the interstitial cells of Cajal in the gastrointestinal tract [12] . Receptor-inactivating point mutations in the KIT gene often act dominantly or semidominantly and are associated with hypopigmentation , anemia , and/or sterility . The dominant or semidominant inheritance is either due to haploinsufficiency or to the fact that mutated KIT receptors may form heterodimers with wild-type KIT receptors and thus act fully or partially dominant negative . Inactivating KIT mutations cause piebaldism in humans and white or spotted W mutants in mice [13–17] . Gain-of-function mutations in the proto-oncogene KIT are involved in the formation of gastrointestinal stromal tumors , myelogenous leukemia , and mastocytomas [18] . Here , we report the complete genomic organization of the equine KIT gene and an analysis of the KIT gene sequence in horses with depigmentation phenotypes . We identified and sequenced an equine BAC clone harboring the entire KIT gene . This sequence corresponds to positions 6 , 812 , 854–7 , 023 , 775 on scaffold 10 of the first horse genome assembly , which was published during the progress of our work . The genomic organization of the equine KIT gene was inferred by comparison of the genomic sequence with the cDNA sequence from public databases . The equine KIT gene spans a genomic region of about 82 kb and comprises 21 exons , similar to the human KIT gene . The equine KIT mRNA contains an open reading frame of 2 , 919 bp encoding a protein of 972 amino acids . The encoded peptide is predicted to have a molecular weight of 108 . 9 kDa , a pI of 6 . 3 , and 88% identity to the human and 82% identity to the orthologous mouse protein , respectively . We selected four white and four solid-colored Franches-Montagnes horses from a three-generation family for the initial mutation analysis ( see Figure 1 for an overview on phenotypes and Figure S1 for pedigree of the family ) . Comparative sequencing of all 21 exons and adjacent sequences revealed 15 SNPs in these closely related animals ( Table 1 ) . Only one of the 15 polymorphisms showed perfect cosegregation of the genotypes with the dominant white phenotype in the initial family . The cosegregating polymorphism was a C-to-G transversion located in exon 15 ( c . 2151C>G ) , which introduced a premature stop codon in the open reading frame of the KIT protein ( p . Y717X ) . The mutation was predicted to truncate the KIT protein in the middle of the kinase insert domain ( Figure S2 ) . We confirmed the presence of the c . 2151C>G polymorphism in the white horses by sequencing genomic PCR products containing exon 15 in both directions ( Figure 2A ) and performing BccI RFLP analysis of these PCR products . Furthermore , the polymorphism was also confirmed on the transcript level by sequencing reverse transcriptase PCR ( RT-PCR ) products ( Figure 2E ) . We genotyped all available Franches-Montagnes samples ( n = 132 ) in our laboratory for the c . 2151C>G polymorphism . All 20 white horses , descendants of Cigale , were heterozygous for the c . 2151C>G polymorphism ( Figure S1 ) . To exclude the possibility that this variant also occurs in solid-colored horses , a cohort of 112 solid-colored Franches-Montagnes Horses were genotyped and all of them were homozygous for the wildtype C allele at position c . 2151 ( Table S1 ) . Transcripts containing premature termination codons are often subject to nonsense-mediated decay ( NMD ) or nonsense-mediated exon skipping ( NME ) . NMD and NME are thought to be quality-control mechanisms by which cells can limit the expression of aberrant proteins . We performed RT-PCR on leukocyte RNA from a white horse using primers located in exon 13 and exon 16 . Analysis of the RT-PCR products on agarose gels exclusively yielded the complete cDNA-fragments including exon 15 . Therefore , the c . 2151C>G mutation does not seem to induce NME ( unpublished data ) . Direct sequencing of the RT-PCR product from a heterozygous white horse revealed that the mutant transcript is present , albeit at a lower level compared to the wild-type transcript . From the quantitative analysis of the signal intensity ratios in the electropherograms between genomic DNA and cDNA , we estimated that the amount of mutant transcript is about 50% of the amount of wild-type transcript in leukocytes ( Figure 2C ) . The other 50% of mutant transcripts are probably degraded by NMD . We further performed a western blot on protein extracts from skin samples of a dominant white and a solid-colored horse to investigate whether the predicted truncated KIT protein is expressed in skin . The western blot of the solid-colored horse showed a strong band of the expected size ( ∼150 kDa ) for the glycosylated full-length KIT protein . The skin sample from the dominant white horse yielded a weak band at ∼150 kDa and another weak band at ∼120 kDa . The size of the ∼120 kDa band corresponds to the predicted size of the truncated KIT protein , as the p . Y717X mutation should remove 29 kDa of the presumably unglycosylated intracellular part of the protein ( Figure 3 ) . We sequenced all 21 KIT exons in 16 other white or partially depigmented horses from other breeds ( Arabian , Camarillo White Horses , Thoroughbred , Miniature Horse , Shetland Pony ) . Eight of these 16 horses carried nonsynonymous mutations in the KIT coding sequence . Two related white Arabians had a nonsense mutation in exon 4 ( c . 706A>T , Figure 2B ) , which was predicted to truncate the protein in the extracellular domain ( p . K236X ) . A third Arabian horse in the family with minor white spotting did not have the mutation . The mutation showed perfect cosegregation with the dominant white phenotype in the family of the tested Arabians ( Figure S1 ) . It was absent from 20 unrelated solid-colored Arabians and also from 110 solid-colored Franches-Montagnes Horses that were genotyped as controls ( Table S1 ) . Three Camarillo White Horses were heterozygous for a missense mutation in exon 12 ( c . 1805C>T , Figure 2C ) . This mutation affects the intracellular tyrosine kinase domain of the KIT protein and replaces the small side chain of alanine 602 with the much larger side chain of a valine ( p . A602V ) . The mutation was exclusively found in the white horses from the family of the tested Camarillo White Horses ( Figure S1 ) . Camarillo White Horses are an open breed and can be mated to horses from other populations without restrictions . However , only white offspring of such matings can be registered as a Camarillo White Horse . Therefore , it was not possible to analyze solid-colored horses from the same registry as controls . However , the mutation was absent from 169 solid-colored horses of various breeds ( Table S1 ) . Three related white Thoroughbreds were heterozygous for a missense mutation in exon 13 ( c . 1960G>A , Figure 2D ) . This mutation also affects the intracellular tyrosine kinase domain of the KIT protein and leads to a nonconservative exchange of glycine-654 with arginine ( p . G654R ) . The cosegregation of the mutation was confirmed in the family of the tested animals ( Figure S1 ) . This mutation was absent from 17 solid-colored Thoroughbreds and 97 solid-colored Franches-Montagnes Horses ( Table S1 ) . The presence of the c . 1805C>T and c . 1960G>A polymorphisms was independently confirmed by RFLP analyses . We did not find any mutations affecting the KIT coding sequence in the remaining eight horses with depigmentation phenotypes . These horses were five almost completely white Thoroughbreds , one Arabian Horse with minor white spotting , one Miniature Horse with ∼50 % depigmented skin area , and one Shetland Pony with ∼75% depigmented skin area . The data of this study strongly suggest that the c . 2151C>G mutation causes the dominant white phenotype segregating in the Franches-Montagnes Horses . As the mutation represents a nonsense mutation , which leads to the truncation of the functionally important second half of the intracellular tyrosine kinase domain of the KIT protein , it seems justified to assume that this mutation severely affects KIT function . Furthermore , the perfect association of this mutation with the dominant white phenotype in cohorts of 20 white and 112 solid-colored Franches-Montagnes Horses corroborates the causative role of the c . 2151C>G mutation . The observed association would also be compatible with a scenario of a closely adjacent causative mutation , which is in linkage disequilibrium with the c . 2151C>G mutation . However , we regard this as very unlikely , as we can rule out any mutations in the other exons of the KIT gene . Therefore , it would be difficult to postulate a different causative mutation with a more dramatic effect on the KIT protein than the c . 2151C>G mutation , which causes the truncation of more than a quarter of the protein , including the entire second intracellular tyrosine kinase domain . A similar argument holds true for the c . 706A>T mutation , which segregated in a family of white Arabians . This mutation is predicted to truncate more than three quarters of the protein , including ligand binding domain , transmembrane domain , and the entire intracellular part of the KIT protein . The prediction of the functional impact of the two missense mutations found in Thoroughbreds and Camarillo White Horses is not quite as straightforward . However , both mutations affect the functionally important first intracellular tyrosine kinase domain , and comparable mutations of this domain have been shown to cause piebaldism in humans and depigmentation phenotypes in mice ( Figure S2 ) . The c . 2151C>G mutation was confirmed on the genomic and on the cDNA level . Apparently , only about half of the mutant KIT mRNA is cleared by NMD , although it does contain a premature stop codon . Investigation of the mutant protein expression in skin samples of a dominant white ( W/+ ) and a solid-colored ( +/+ ) horse by western blot showed a strong band of the expected size in the solid-colored ( +/+ ) horse and weak bands corresponding to the sizes of the wild-type and the truncated protein in a dominant white ( W/+ ) horse . Thus , the western blot indicated that the truncated protein is indeed expressed . It seems conceivable that a truncated KIT protein lacking the second half of the intracellular tyrosine kinase domain forms inactive dimers with wild-type KIT proteins and acts as a dominant-negative protein . The observed variation in the coat color phenotypes of horses with the c . 2151C>G mutation ( Figure 1A–1C ) could be explained by different efficacies of NMD in different individuals and in different body regions . If the mutant transcript is efficiently cleared by NMD , then the remaining wild-type allele could possibly produce enough functional KIT protein to facilitate pigmentation to some extent . However , the more that the truncated KIT protein is expressed , the less likely it is that enough functional dimers of wild-type KIT proteins can mediate proper KIT signaling . Our data indicate allelic heterogeneity among dominant white horses from different breeds . Thus , our study represents another example where different mutations in a single gene have been described for a Mendelian trait in domestic animals similar to the situation in , e . g . , brown coat color in dogs or syndactyly in cattle [19 , 20] . At this time , it is not known whether the depigmentation of the other reported white horses is caused by as-yet undescribed mutations at the KIT locus or whether mutations in other genes can also cause this phenotype . The striking phenotype and the autosomal dominant inheritance facilitate the identification of founder animals . In each of the four investigated families , the white founder animals born out of solid-colored parents are known: for the Franches-Montagnes Horses , it is the white mare Cigale , born in 1957 . In the Arabian family , the presumed founder stallion was born in 1996 . The white stallion Sultan , born in 1912 , is the reported founder of the Camarillo White Horses . The white founder animal of the Thoroughbred family segregating the c . 1960G>A mutation is most likely a stallion born in 1946 . In line with the recent origin of these mutation events , the four proposed candidate causative mutations of this study segregate only within the four respective families . In contrast , all of the other 14 KIT polymorphisms that were discovered during the initial mutation analysis segregate in at least two distinct horse populations , indicating that they are much older and spread into different horse populations by the ongoing admixture , which is typical for many modern horse breeds . KIT gene mutations have been described in humans with piebaldism [13–15] , in W mouse mutants [16 , 17] , and in dominant white pigs [21] . White spotting or white coat color is a common trait in many breeds of domestic animals , but in many instances the molecular mechanisms for these depigmentation phenotypes are still unknown . In the horse , a mutation in the EDNRB gene encoding the endothelin receptor B causes the overo spotting pattern in the heterozygous state . When this mutation is present in the homozygous state , completely depigmented foals are born that usually die within the first few days of life , due to intestinal aganglionosis [22] . The equine KIT gene plays a central role in equine pigmentation , as at least four distinct depigmentation phenotypes are known to be associated with mutations at the equine KIT locus . Of the equine KIT mutations , so far , only the mutations for sabino-1 and tobiano have been elucidated at the molecular level . The mutations for the sabino-1 and tobiano spotting patterns do not change the KIT coding sequence , but rather reduce the expression of functional KIT transcripts . Tobiano ( TO ) acts strictly autosomal dominant , and TO/TO horses are viable , fertile , and phenotypically indistinguishable from TO/+ horses [7] . Sabino-1 ( SB1 ) acts semidominant , and SB1/SB1 horses are viable and almost completely white , whereas SB1/+ horses show a characteristic sabino spotting pattern [6] . Dominant white ( W ) produces a variable but rather severe depigmentation phenotype in heterozygous horses ( W/+ ) . In the mouse , more than 90 different Kit alleles are known . Many of these mutations produce some degree of white spotting in the heterozygous state , which can range from tiny white belly spots to >99% depigmentation . Many KIT regulatory mutations exist that produce severe pigmentation phenotypes in the heterozygous state . However , some of the murine structural mutations , such as the KitW-42J mutation , also lead to an almost complete depigmentation in the heterozygous state . In the mouse , mutations causing a pronounced dominant depigmentation phenotype typically also lead to mild anemia and reduced male fertility even in the heterozygous state [23] . We are not aware of any specific health problems in the studied white horses . At least two of the white Thoroughbreds with the c . 1960G>A mutation successfully competed in horse races , indicating a very good general fitness . There are very little data on fertility in white horses; however , one white Franches-Montagnes stallion was successfully used for artificial insemination , and all routine sperm parameters from this stallion were normal . Therefore , from the limited available data , it appears that heterozygous KIT mutations may have less detrimental effects in horses on hematopoiesis and fertility than in mice . In horses , dominant white was reported to cause embryonic lethality in the homozygous state [4] . However , this report on the embryonic lethality was derived from the analysis of offspring phenotype ratios in a single herd segregating one or more unknown mutations . As there is now evidence for allelic heterogeneity , it remains to be proven whether all equine dominant white mutations cause embryonic lethality in the homozygous state . While this is certainly likely for the two nonsense mutations found in Franches-Montagnes Horses and Arabians , it should not necessarily be assumed for the two reported missense mutations or for any of the other as-yet unknown W mutations . White horses have always fascinated their human owners . The majority of “white” horses probably carry the greying-with-age mutation [24] , which means that they are born solid colored and become white at the age of four to six years . However , there are also a number of historical reports that explicitly mention white-born horses resembling the phenotype of dominant white horses [1 , 25] . Two thousand years ago , the Romans already knew of the phenotypic differences of depigmented horses , which they described as candidus ( white ) or glaucus ( grey ) [26] . The Roman historian Tacitus described the use of sacred white horses for auguries by German tribes [27] . The so-called white horse of the Saxons is depicted on the flags of the German states of Lower Saxony and North Rhine-Westphalia . It is thus of considerable historic interest to trace the origins of white horses , particularly because the nature of their white color can have different causes , some of which are KIT mutations such as those described here . We do not know whether the Roman terms candidus and glaucus actually correspond to our modern coat color designations of white and grey . Archaeogenetics on historic DNA samples may help to identify the genetic constitution of these horses . In conclusion , we have identified the probable causative mutation for the dominant white phenotype in Franches-Montagnes Horses . We have also identified three additional candidate causative mutations in Arabians , Camarillo White Horses , and Thoroughbreds . The knowledge of these mutations will allow genetic testing and should help to assign more precise coat color descriptions for partially or completely depigmented horses . All 21 KIT exons were analyzed in 138 horses of six different breeds . The animals consisted of 118 solid-colored horses ( 112 Franches-Montagnes , six Arabian ) , four white Franches-Montagnes , and 16 horses registered as maximal sabino ( eight Thoroughbreds from three independent families , three related Arabians , three related Camarillo White Horses , one Miniature Horse , and one Shetland Pony ) . These 16 horses had been typed for the absence of the sabino-1- and tobiano-causing mutations [6 , 7] . In the Franches-Montagnes breed , horses with spotting phenotypes ( sabino , tobiano , and overo ) may not be registered; therefore , we assumed these mutations to be absent from the Franches-Montagnes population . Sixteen additional white Franches-Montagnes Horses were genotyped for the presence of the c . 2151C>G mutation . Additional solid-colored animals from various breeds ( Arabian , Missouri Fox Trotter , Quarter Horse , Spanish Mustang , Spotted Draft , Spotted Mountain Horse , and Thoroughbred ) were tested for the absence of the four candidate causative mutations . Genomic DNA was isolated from peripheral blood or hair roots using standard methods . RNeasy spin columns were used to isolate total RNA from a solid-colored horse ( skin , small intestine , colon , and testis ) and a white horse ( skin ) according to the manufacturer's protocol ( Qiagen ) . Additionally , total RNA was isolated from white blood cells of the white horse using TRIzol reagent ( Invitrogen ) according to the manufacturer's protocol . The BAC clone CH241-440E11 from the CHORI-241 library was predicted to contain the equine KIT gene , based on BAC end sequence comparative mapping [28] . DNA from this clone was isolated using the Qiagen large construct kit ( Qiagen ) . The purified BAC DNA was sheared to approximately 2–5 kb fragments using a nebulizer , and a shotgun plasmid library was prepared in the vector pCR4Blunt-TOPO ( Invitrogen ) . Template DNA for sequencing was prepared using TempliPhi ( GE Healthcare ) and shotgun plasmid clones were sequenced to approximately 6-fold coverage using the BigDye v3 . 1 kit and an ABI 3730 capillary sequencer ( Applied Biosystems ) . After sequencing a random collection of plasmid subclones , the remaining gaps were closed by a primer walking strategy . Sequence data were assembled with Sequencher 4 . 6 ( GeneCodes ) . Comparison of the obtained genomic DNA sequence with a published KIT cDNA sequence ( AJ224645 ) allowed the annotation of the exons . Primers for the amplification of each of the 21 KIT exons with flanking regions were designed with the software Primer3 ( http://frodo . wi . mit . edu/cgi-bin/primer3/primer3_www . cgi ) after masking repetitive sequences with RepeatMasker ( A . F . A . Smit and P . Green , http://repeatmasker . genome . washington . edu/ ) . The sequences of the primers are listed in Table S2 . PCR products were amplified in 20 μl reactions using AmpliTaq Gold DNA polymerase ( Applied Biosystems ) and checked for yield and purity on agarose gels . Direct sequencing of the PCR products was performed after shrimp alkaline phosphatase ( Roche ) and exonuclease I treatment ( New England Biolabs ) . PCR products were sequenced as described above using both PCR primers as sequencing primers . In some instances , additional internal sequencing primers were used . PCR products were subjected to RFLP analyses to confirm the presence of three nonsynonymous mutations . The presence of the c . 1805C>T mutation was verified using the enzyme HaeIII . The c . 1960G>A mutation was verified with DdeI , and the c . 2151C>G mutation with BccI . The restriction fragments were separated on standard agarose gels and genotypes were determined from the resulting band patterns . Aliquots of 1 μg total RNA were reverse transcribed into cDNA using 20 pmol ( T ) 24V primer and Omniscript reverse transcriptase ( Qiagen ) . Two microliters of the cDNA were used as a template in PCR . PCRs were performed as described above . Epidermis from a solid-colored and a white horse was fixed in formalin-buffered saline and embedded in paraffin . Tissue sections ( 5 mm ) were dewaxed in xylene for 7 min , dehydrated in alcohol , and then rinsed with PBS . For exposure and detection of KIT protein , antigen retrieval was performed in Tris-EDTA ( pH 9 ) in the microwave for 15 min . Nonspecific binding was blocked by incubating the sections in 5% normal donkey serum ( Dako ) in Tris-buffered saline for 30 min . Negative control studies were performed without primary antibody . We used a goat antibody directed against the extracellular domain of mouse c-kit ( R&D Systems ) at a concentration of 2 μg/ml . Binding was detected using an alkaline phosphatase donkey-anti-goat IgG ( Jackson Immuno Research ) at a dilution of 1:200 for 60 min . Sections were washed in PBS and subsequently visualized using BCIP/NBT ( Dako ) . For skin protein extraction , minced skin samples were incubated overnight at 4 °C with RIPA extraction buffer ( Pierce ) containing 25 mM Tris-HCl pH 7 . 6 , 150 mM NaCl , 1% NP-40 , 1% sodium deoxycholate , and 0 . 1% SDS , complemented with Halt protease inhibitor cocktail ( Pierce ) and 8 M urea . After centrifugation at 15 , 000 xg for 10 min at 4 °C , the supernatants were collected and protein concentration was determined using a Bradford assay ( Bio-Rad ) . Protein extracts ( 20 μg ) were boiled for 5 min in reducing sample buffer and separated by 12% SDS-PAGE . Proteins were electrically transferred to a polyvinylidene difluoride ( PVDF ) membrane . After blocking with 5% skim milk , the membrane was incubated with a chicken IgY affinity-purified polyclonal antibody directed against the N-terminus of human KIT ( GenWay ) diluted 1:1 , 000 . Detection was performed using an alkaline phosphatase–conjugated anti-IgY secondary antibody ( Jackson Immuno Research ) diluted 1:5 , 000 and BCIP/NBT ( Dako ) . The DNA sequence reported in this manuscript has been submitted to the European Molecular Biology Laboratory ( EMBL ) database ( http://www . ebi . ac . uk/embl/ ) under accession number AM420315 . The National Center for Biotechnology Information ( NCBI ) Entrez database ( http://www . ncbi . nlm . nih . gov/sites/gquery ) accession number for scaffold 10 of the first horse genome assembly is NW_001799714 , and the accession for a partial equine KIT mRNA sequence is AF055037 . This sequence was used as a reference for numbering the positions of the sequence variants .
White horses have always been highly valued by their human owners . Their important role in history is reflected by their widespread use as heraldic animals ( e . g . , on the flags of the German states of Lower Saxony and North Rhine-Westphalia ) . In the Swiss Franches-Montagnes Horse population , a completely white mare named Cigale was born out of solid brown parents in 1957 . The white phenotype is inherited as an autosomal dominant trait and all living white Franches-Montagnes Horses are descendants of Cigale . We sequenced the KIT gene in white and solid-colored Franches-Montagnes Horses and found a mutation that inactivates the gene product and thus leads to a lack of pigment-forming cells in the skin of white horses . We then analyzed white horses from other populations and found three additional independent candidate causative mutations in white Thoroughbreds , Arabians , and Camarillo White Horses . The research thus revealed independent mutation events leading to white coat color in different horse populations . Our findings will allow genetic testing and a more precise classification of horses with white coat color .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods", "Supporting", "Information" ]
[ "dermatology", "mammals", "horse", "eukaryotes", "vertebrates", "animals", "genetics", "and", "genomics" ]
2007
Allelic Heterogeneity at the Equine KIT Locus in Dominant White (W) Horses
Despite its morphological similarity to the other species in the Drosophila melanogaster species complex , D . sechellia has evolved distinct physiological and behavioral adaptations to its host plant Morinda citrifolia , commonly known as Tahitian Noni . The odor of the ripe fruit of M . citrifolia originates from hexanoic and octanoic acid . D . sechellia is attracted to these two fatty acids , whereas the other species in the complex are repelled . Here , using interspecies hybrids between D . melanogaster deficiency mutants and D . sechellia , we showed that the Odorant-binding protein 57e ( Obp57e ) gene is involved in the behavioral difference between the species . D . melanogaster knock-out flies for Obp57e and Obp57d showed altered behavioral responses to hexanoic acid and octanoic acid . Furthermore , the introduction of Obp57d and Obp57e from D . simulans and D . sechellia shifted the oviposition site preference of D . melanogaster Obp57d/eKO flies to that of the original species , confirming the contribution of these genes to D . sechellia's specialization to M . citrifolia . Our finding of the genes involved in host-plant determination may lead to further understanding of mechanisms underlying taste perception , evolution of plant–herbivore interactions , and speciation . Every animal must locate and identify sufficient food to meet its biological requirements . For herbivorous insects , this results in an endless battle with their host plants [1] . For example , some plants develop a chemical defense system that causes toxicity to generalist herbivores [2] . In response , generalist herbivores may then evolve a behavioral system to avoid such toxic plants . If an insect species acquires resistance to a plant toxin , however , it may reap an ecological advantage by gaining exclusive access to the toxic plant and may subsequently evolve as a specialist herbivore with a specific preference towards that plant . Such physiological and behavioral specialization plays an important role in the evolution of divergent ecological interactions between herbivores and their host plants . Nevertheless , it does not necessarily follow that ecological specialization for a particular host plant drives speciation of herbivores itself . Such specialization may not be sufficient to maintain divergence between populations at an early stage of speciation , in the face of potential gene flow via hybridization between evolving populations . The role of ecological specialization in speciation remains , therefore , to be proven [3] . Thus , it is necessary to identify the genes and molecular mechanisms responsible for ecological adaptation if we are to understand whether ecological adaptation can be a cause , or merely a consequence , of speciation [4] . Behavioral adaptation of herbivorous insects to their host plants involves the evolution of the chemosensory system [5–7] . With the recent identification of olfactory and gustatory receptors [8] , knowledge of the genetic and molecular mechanisms of insect olfactory and gustatory system markedly progressed . Recent analysis of genomic information from several insect species has also revealed that the number of genes encoding these receptors varies considerably between species , indicating a close relationship between the genomic constitution of chemoreceptor gene families and the species-specific lifestyles of insects [9–11] . Thus , it is likely that the genes responsible for ecological adaptation are to be found among these receptor-encoding and receptor-related genes . Genetic studies of Drosophila have also contributed to a substantial amount of our knowledge of “speciation genes” [4] . However , these studies have primarily focused on genes that cause reproductive isolation , and genetic analysis of ecological adaptation is relatively rare . This is , in part , due to the surprisingly limited information about Drosophila in the wild , compared with those flies reared in the laboratory as a sophisticated model system of genetics . In fact , we know little about their natural foods in the wild , except for a few species . Drosophila sechellia is a specialist of Morinda citrifolia , which is commonly known as Tahitian Noni [12] . Although D . sechellia shows a preference for and resistance to the ripe fruit of M . citrifolia , its most closely related species , D . simulans and D . mauritiana , as well as D . melanogaster , are generalists and die upon contact with M . citrifolia , and thus avoid the fruit [13 , 14] . Because of genetic resources available for D . melanogaster and D . simulans , D . sechellia is an ideal organism with which to explore the genetics of ecological specialization . Analysis of quantitative trait loci ( QTL ) between D . sechellia and D . simulans has already identified the chromosomal regions responsible for the interspecies difference in resistance to the toxicity of M . citrifolia [15] . However , D . sechellia's preference for M . citrifolia was explained only by the transformation of olfactory sensilla resulting in an increase of the ab3 subtype that responds to the host odorant methyl hexanoate ( MH ) [16] . These findings successfully describe the present status of D . sechellia's specialization for M . citrifolia , but the evolutionary history , especially how an ancestral population started to use the toxic plant as its host , has been unexplained . Here , for the first time , we have identified genes involved in D . sechellia evolution . These genes are responsible for the behavioral differences between species in their responses to hexanoic acid ( HA ) and octanoic acid ( OA ) , the toxins contained in the ripe fruit of M . citrifolia , which give it its characteristic odor . Having identified the genetic factors constituting D . sechellia's adaptation to M . citrifolia , we are now able to discuss more confidently whether host-plant specialization can drive D . sechellia speciation . We previously reported that the behavioral difference ( preference/avoidance ) between D . sechellia and D . simulans in response to HA , one of the main components of odor from the ripe fruit of M . citrifolia , is controlled by at least one gene on the second chromosome [17] . Further analysis of the introgression lines between D . sechellia and the D . simulans second chromosome marker strain ( net b sd pm ) indicated that the behavioral difference is linked to the marker pm , which is on the distal end of the right arm of the second chromosome ( I . Higa and Y . Fuyama , unpublished data ) . Considering the fact that the overall structure of the second chromosome is conserved between D . simulans and D . melanogaster , we mapped the locus in more detail using a series of D . melanogaster deficiency strains lacking a terminal part of the right arm of the second chromosome . Because D . sechellia's preference for HA is a recessive trait to D . melanogaster's avoidance [17] , the interspecies hybrids between D . sechellia and D . melanogaster deficiency strains that lack a region containing the responsible gene ( s ) were expected to show the D . sechellia–like phenotype , i . e . , preference for HA . Two deficiency strains , Df ( 2R ) exu1 and Df ( 2R ) AA21 , showed preference for HA when they were crossed with D . sechellia , defining the responsible locus within a very small chromosomal region , in combination with Df ( 2R ) exu2 , which showed avoidance to HA when crossed with D . sechellia ( Figure 1A ) . Because the break points of these deficiency chromosomes had been deduced from cytological observations , we determined the position of these break points precisely by PCR-direct sequencing of genomic DNA from hybrids between D . melanogaster deficiency strains and D . sechellia ( Figure 1B ) . According to the left break point of Df ( 2R ) exu1 and the left break point of Df ( 2R ) exu2 , the locus was narrowed down within about 200 kilobases ( kb ) of the genomic region that contains 24 predicted genes . There is no large deleted region in the Df ( 2R ) AA21 chromosome around this area , which is inconsistent with the result that Df ( 2R ) AA21 also showed preference for HA when crossed with D . sechellia . While examining the marker sequences used in break-point determination of Df ( 2R ) AA21 , however , we incidentally found that this chromosome has a small , ten–base pair ( bp ) deletion in the first exon ( open reading frame [ORF] ) of the Odorant-binding protein 57e ( Obp57e ) gene resulting in a frame-shift mutation ( Figure 1C ) . Insect OBP is a protein secreted into the lymph of chemosensory hairs , and it has been shown to play a crucial role in chemosensation [18] . Thus , it seemed likely that Obp57e is a gene responsible for the interspecies difference in response to HA . However , when Obp57e ORF sequences from D . melanogaster , D . simulans , and D . sechellia are compared , there is no D . sechellia–specific alteration except for L11I , which does not affect the result of signal peptide–sequence prediction ( Figure 1D ) . Thus , D . sechellia Obp57e ORF is supposed to be functionally intact , suggesting that the interspecies difference is not in the structure of the gene product , but rather in gene expression . Quantitative reverse-transcriptase polymerase chain reaction ( RT-PCR ) analysis revealed that the level of Obp57e transcripts is higher in the legs of D . sechellia than in D . melanogaster and D . simulans ( Figure 2 ) . This could be due to an elevated transcription activity in particular cells and/or a widened expression pattern . According to the lacZ reporter experiment , D . melanogaster Obp57e is expressed only in four cells associated with chemosensory hairs on the fourth and fifth segments of each tarsus , the most terminal part of an insect leg [19] . We confirmed that as short as 450 bp of the upstream region of Obp57e completely reproduces the reported expression pattern ( Figure 3A–3C ) . We then cloned the corresponding region from D . simulans and D . sechellia , and introduced it into D . melanogaster with a green fluorescent protein ( GFP ) reporter gene . The D . simulans sequence successfully reproduced the same expression pattern as observed in D . melanogaster ( Figure 3D ) . However , the D . sechellia sequence failed to drive GFP expression in any parts of the fly body ( Figure 3E ) , indicating that the function of the D . sechellia sequence to promote gene expression is altered . Indeed , when the upstream sequence of Obp57e is compared between species , a 4-bp insertion was found in the D . sechellia Obp57e upstream sequence ( Figure 3H ) . GFP expression was restored by removing the inserted 4-bp nucleotides from the D . sechellia sequence , showing that this 4-bp insertion abolishes the function of the D . sechellia Obp57e promoter sequence in D . melanogaster ( Figure 3F and 3G ) . Nevertheless , the results of GFP reporter experiments are inconsistent with that of quantitative RT-PCR analysis , thus , the exact expression pattern of Obp57e in D . sechellia remains unclarified . Therefore , it is necessary to evaluate using more direct methods whether Obp57e is truly responsible for the interspecies difference in behavioral response to HA . We generated D . melanogaster knock-out flies for Obp57e , as well as for its neighbor Obp57d , and for both Obp57d and Obp57e , by gene targeting ( Figure 4 ) . The ends-out method was employed to achieve precise gene replacement in the gene-dense Obp57d/e region ( Figure 4A ) . To avoid side effects on transcription of surrounding genes , the marker gene ( 3 kb ) was excised by Cre recombinase , leaving only 34 bp of the loxP sequence . Each donor construct was designed such that the ORF was removed exactly from the ATG translation initiation site , but a putative poly-A additional signal was left intact , ensuring the termination of residual transcription that may affect the expression of downstream genes via read-through events ( Figure 4B ) . The loss of transcripts from the targeted gene was confirmed by quantitative RT-PCR in each knock-out strain ( Figure 2 ) . We observed , however , an unexpected interaction between Obp57d and Obp57e in their expression control . The amount of Obp57e transcripts was higher in Obp57dKO flies than in the w1118 control strain . On the other hand , the amount of Obp57d transcripts decreased in the legs of Obp57eKO flies . Because each knock-out strain lacks the intron and the ORF , these regions may contain elements that influence the expression of the other gene . Each knock-out strain responded to HA differently from the control strain in the trap assay ( Figure 5 ) . Obp57dKO and Obp57eKO avoided HA , whereas females of Obp57d/eKO preferred it , suggesting that not only Obp57e , but also Obp57d , is involved in the behavioral difference observed in the screening assay . In fruit flies , host plants are largely determined by the oviposition site preference of adults . Thus , we also examined the oviposition site preference of knock-out flies in response to HA . Indeed , Obp57eKO and Obp57d/eKO seem to prefer lower concentrations of HA than the control flies , although the difference is not statistically significant ( Figure 6 , Tables 1–4 ) . The direction of behavioral alteration was , however , not the same as that found in the trap assay for Obp57d/eKO . We also examined oviposition site preference in response to OA , the main toxic component in Morinda fruit . Because of its toxicity at high concentrations , the oviposition assay was carried out at concentrations lower than those of HA . Obp57dKO and Obp57eKO preferred higher concentrations of OA . This preference was particularly obvious for Obp57dKO , which was comparable to that of D . sechellia . Contrary to the responses to HA and OA , knock-out strains preferred concentrations of acetic acid and butyric acid similar to those preferred by control flies , showing that the alteration of behavioral responses in these knock-out strains is specific to HA and OA . Our observation of the behavior of Obp57dKO , Obp57eKO , and Obp57d/eKO revealed that these strains are qualitatively different from each other in their responses to HA and OA . This strongly suggests that Obp57d , as well as Obp57e , is involved in D . sechellia's behavioral adaptation to M . citrifolia . Nevertheless , none of these knock-out strains was identical to D . sechellia in behavior . This is consistent with the results of quantitative RT-PCR analysis in which no knock-out strain exhibited an expression profile identical to that of D . sechellia , proving that this species is not a simple null mutant of Obp57d and/or Obp57e . Rather , D . sechellia seems to be a neomorphic mutant with an altered expression control of these genes . To examine the functions of Obp57d and Obp57e in D . simulans and D . sechellia , we cloned these genes from D . simulans and D . sechellia and introduced them into the D . melanogaster Obp57d/eKO strain . Because an interaction between the two genes was observed with respect to their expression control , a genomic fragment spanning both Obp57d and Obp57e was used for genetic transformation . The resulting transformant flies showed altered responses to HA and OA in the oviposition site–preference assay ( Figure 6; Tables 3 and 4 ) . Obp57d/eKO; simObp57d/e flies avoided HA as D . simulans does . Conversely , Obp57d/eKO; secObp57d/e flies preferred high concentrations of OA as D . sechellia does . These results clearly showed that the Obp57d/e genomic region contains genetic information responsible for , at least in part , the interspecies differences in behavioral responses to HA and OA . However , these transgenic flies are not complete mimicries of the original species . Although D . simulans avoided OA , as well as HA , the response of Obp57d/eKO; simObp57d/e flies to OA was not significantly different from that of the D . melanogaster control strain ( Figure 6; Table 4 ) . The responses of these two transgenic strains in the trap assay were also different from that of the original species ( Figure 5 ) . Consistent with the results of the oviposition assay , D . simulans avoided HA and D . sechellia preferred it . Obp57d/eKO; simObp57d/e females , however , did not avoid HA , and both sexes of Obp57d/eKO; secObp57d/e flies did not prefer it . Indeed , the expression profiles of Obp57d and Obp57e were not exactly the same between the transgenic strains and the corresponding original species ( Figure 2 ) . Although the genomic fragments seemed to reproduce the native expression better than the GFP reporters , there still remains significant differences in expression profile , particularly between Obp57d/eKO; simObp57d/e and D . simulans . These differences suggest a contribution of additional loci to Obp57d/e expression , and thus to the interspecies differences in behavioral responses to HA and OA . Nevertheless , the Obp57d/e genomic region from D . simulans and D . sechellia could reproduce , at least in part , the behavioral pattern of the original species in an otherwise D . melanogaster genomic background , proving that a genetic difference in this region is actually involved in interspecies differences in behavioral responses to odorants contained in M . citrifolia . It should be particularly noted that the Obp57d/e region is alone sufficient for the strong avoidance of HA by D . simulans , which is a key trait in the evolution of D . sechellia's adaptation to M . citrifolia , as discussed below . LUSH ( OBP76a ) , the best studied OBP in D . melanogaster , functions as an adaptor molecule in vaccenyl acetate ( VA ) recognition by an odorant receptor , OR67d [20] . Mutants lacking LUSH lose their neuronal response to VA; thus , they do not respond to VA behaviorally [18] . However , our Obp57d/eKO flies retained their behavioral responses to HA and OA , suggesting that OBP57d/e do not function as adaptors for HA and OA . Rather , they seem to modulate dose-dependent responses to HA and OA , which might be achieved by other proposed functions of OBP , such as the titration or degradation of ligands [21] . There are qualitative differences in the behavioral responses to HA and OA between Obp57dKO and Obp57eKO flies . These differences might reflect functional diversification between OBP57d and OBP57e . However , the elimination of either Obp57d or Obp57e affected the expression level of the other in these knock-out flies . Obp57d removal by gene targeting increased Obp57e expression level , and Obp57e removal repressed Obp57d expression . Thus , we cannot exclude the possibility that the behavioral differences between the knock-out strains are caused by an altered expression level of either gene . A more operative method such as the Gal4-UAS system could be used to separate promoters from ORFs , thus minimizing the interaction between these two genes in expression control . It would then be possible to examine the molecular functions of OBP57d and OBP57e independently . The results from our GFP reporter experiments and quantitative RT-PCR analysis are inconsistent . This inconsistency is also a feature of previous studies . Galindo and Smith [19] showed that the reporter constructs with 3 kb of upstream sequence from Obp57d and Obp57e were expressed in four cells in each leg , which matches the results of our GFP reporter experiments . However , using RT-PCR analysis , Takahashi and Takano-Shimizu [22] detected the transcripts not only in tarsi , but also in labella and wings . Together with the results of our quantitative RT-PCR analysis , it is clear that the reporter constructs do not reflect the complete expression pattern of Obp57d/e . The difference could be , at least in part , due to the lack of coding region in the reporter constructs . In fact , the elimination of a coding region of either Obp57d or Obp57e affected the expression level of the other gene in Obp57dKO and Obp57eKO , suggesting the involvement of ORFs and/or an intron in expression control ( Figure 2 ) . Furthermore , the introduction of the Obp57d/e genomic region from D . simulans and D . sechellia reproduced the expression of Obp57d/e in the head as well as in the legs , which was not observed in GFP reporter experiments . Although the Obp57d/e genomic region contains a considerable part of the genetic information that controls Obp57d/e expression , it is still not sufficient to explain all the differences in the expression profile between the species; genetic factors at loci other than Obp57d/e are also likely to be responsible . There are two possibilities for such factors: ( 1 ) Trans-acting factors such as a transcription factor that is necessary for Obp57d/e expression , could control expression by determining which type of cell expresses Obp57d/e , or by determining transcription level in particular Obp57d/e-expressing cells . ( 2 ) Developmental factors determining the cell fate to become Obp57d/e-expressing cells , could increase/decrease the number of Obp57d/e-expressing cells by transforming cell fate at the expense of other cell types . In fact , ab1 and ab2 sensilla on antennae are transformed into ab3 sensilla in D . sechellia [16] . Such cell-type transformation might have occurred also in Obp57d/e-expressing cells . Genes of these two categories could be identified by , for example , screening of mutants that alter the Obp57d/e > GFP expression pattern . D . sechellia's adaptation to M . citrifolia consists of genetic changes at many loci . Although there are likely to be additional genetic differences between D . sechellia and D . simulans , the present status of D . sechellia's adaptation to M . citrifolia can be explained by alterations in three classes of genetic factors , as follows . Factors responsible for resistance to the host-plant toxin OA: genes of this class are mapped to at least five loci scattered over all major chromosome arms [15] , suggesting that the alleles at these loci were fixed independently from each other during the course of D . sechellia evolution . Factors responsible for the olfactory preference for M . citrifolia: D . sechellia can detect Morinda fruit from as far as 150 m away [23] . Consistent with this observation , the number of olfactory sensilla specifically tuned to the host odor MH is increased in D . sechellia [16] ( but also note that MH is commonly found in many other plants ) . In contrast , however , there are no data showing that D . simulans avoids Morinda fruit purely on the basis of olfactory cues; all behavioral assays , including our trap assay , enable flies to come in direct contact with the odor source . There is also no neural response to HA and OA from the antennae of either D . melanogaster or D . sechellia [16] . We therefore assume that the olfactory cues from Morinda fruit are fundamentally attractive to Drosophila , and not repulsive even to D . simulans . D . sechellia has an enhanced preference specifically tuned to the Morinda blend of olfactory cues , in which MH is a functionally major component . Genes responsible for this enhanced preference are thought to function in cell fate determination during neuronal development [16] , but the number of genes involved is not yet known . Factors responsible for the D . simulans' avoidance of Morinda fruit: we found this behavior to be based on gustatory cues , and confirmed that the introduction of the Obp57d/e region from D . simulans made D . melanogaster avoid HA in the same manner as D . simulans ( Figure 6 ) , proving that D . simulans' avoidance of HA-containing media as an oviposition site is determined by Obp57d/e . These two genes are physically close to each other and are thus treated as a single locus in the following discussions . Here , we discuss the order of allele fixation at the loci responsible for D . sechellia's adaptation to M . citrifolia . In particular , we focus on the issue of which mutation was the first to be fixed , because it must have played a key role in D . sechellia's evolution . We speculate on this with respect to the ecological validity of each phenotype in light of natural selection . We assume that the first mutation arose at a single locus , and examine the resulting phenotype in an ecological context . ( 1 ) If the first mutation occurred at a resistance QTL , the resulting phenotype would be partially resistant to M . citrifolia . However , this phenotype is ecologically “silent” because these flies avoid Morinda fruit and may not lay eggs on it ( a mutation on the resistance QTL cannot be advantageous unless a fly's behavior is changed ) . ( 2 ) If the first mutation was for the enhanced preference for the host odorant , flies should be attracted to Morinda fruit . This phenotype would conflict with the gustatory avoidance of Morinda fruit . The consequence of conflicting olfactory and gustatory cues is unpredictable , but we hypothesize that , at least in oviposition behavior , gustatory avoidance would override olfactory preference . Olfactory preference for a plant that is not acceptable as an oviposition site is ecologically inconsistent and obviously disadvantageous . ( 3 ) If the first mutation was at the Obp57d/e locus , the resulting phenotype would be the loss of gustatory avoidance of M . citrifolia . This seems to be also disadvantageous because flies would die upon contact with Morinda fruit because of their lack of resistance to it . However , there are circumstances that might enable an evolving population to survive and reproduce . The toxicity of Morinda fruit declines as it rots and OA degenerates [13] . Thus , there will be a point at which the toxicity is potentially low enough to be counteracted by the nutritional gain from the fruit . Moreover , because M . citrifolia flowers and fruits throughout the year , newly eclosing adults are likely to mate and reproduce on the same Morinda tree . Such conditions may not be optimal with regard to the quality of nutrients , but could potentially provide a niche with fewer competitors and may result in selection for a resistance to host toxicity . Altogether , among the three traits constituting D . sechellia's adaptation to M . citrifolia , only the loss of avoidance provides an ecologically realistic scenario for specialization without any other phenotypic changes . The above discussion , of course , does not exclude the possibility of a simultaneous fixation of the alleles responsible for D . sechellia's adaptation to M . citrifolia . Nevertheless , it is parsimonious to assume that if there was a single causative mutation at an early stage of D . sechellia's adaptation to M . citrifolia , it was the mutation at the Obp57d/e locus that led to the loss of avoidance . D . sechellia , together with D . mauritiana , D . simulans , and D . melanogaster , serves not only as a subject of genetic analysis of reproductive isolation , but also as a good model for genetic analysis of ecological adaptation . There are more than 50 Obp genes in the D . melanogaster genome . Studies of natural variation at these loci will provide insight into the contribution of ecological interactions to the genomic constitution . The fly strains used were w1118 for D . melanogaster , S357 for D . simulans , and SS86 for D . sechellia [17] . Adult flies were collected immediately after eclosion , and staged for 3 d at 25 °C with a cotton plug soaked with liquid medium ( 5% yeast extract and 5% sucrose ) . Staged flies were used for the trap assay , the oviposition site–preference assay , and quantitative RT-PCR analysis . A 30-ml glass flask containing 20 ml of HA solution in 0 . 05% Triton-X and a control flask containing the same amount of 0 . 05% Triton-X were placed in a plastic cage covered with a lid made of wire mesh . Up to 100 staged flies were introduced into the cage and kept in a dark , ventilated chamber overnight at 25 °C . The response index was calculated as RI = ( Nh − Nw ) / ( Nh + Nw ) , where Nh is the number of flies trapped in HA solution and Nw is that of flies in the control trap . The PCR primers used are listed in Table 5 . To amplify a fragment of about 300–600 bp from genomic DNA extracted from the interspecies hybrids between D . melanogaster deficiency strains and D . sechellia , each primer was designed within the ORF of predicted genes , with the expectation that there is enough conservation of sequences between the two species . PCR products were subjected to direct sequencing with the same primer used for amplification . The deficiency chromosome was considered to cover the position when the sequence derived from D . melanogaster or those from both D . melanogaster and D . sechellia were detected , and it was not considered to cover when only the D . sechellia sequence was detected . Signal peptide sequence was predicted using SignalP 3 . 0 [24] . The genomic sequence upstream of Obp57e was PCR amplified with the primer pair 5′- ( NotI ) GCGGCCGC-GCGGTGGCACCCAAAATCAAT-3′ and 5′- ( BamHI ) AAAGGATCC-ACTTGCTATATTCCTAGGGAA-3′ . PCR products were cloned into pGreenPelican [25] , and then introduced into D . melanogaster by the established P element–based transformation method . To remove the inserted 4 bp from the sechellia > GFP construct , the vector was PCR amplified using the KOD-plus enzyme ( Toyobo , http://www . toyobo . co . jp/e/ ) that does not append a T on the ends with the primers 5′-GATTATCCATTATATTGAAATTTAATTGC-3′ and 5′-ACATTTTTAATTGCACACACATTCAG-3′ , and self-ligated after phosphorylation . At least five independent transformant lines for each construct were examined for GFP expression . Disruption of Obp57d and Obp57e was carried out by the ends-out method using the vectors provided by Dr . Sekelsky [26] . A hsp70-white marker gene was excised from pBS-70w with SphI and XhoI and subcloned into the SmaI site of pBSII after blunting to obtain pBSII-70w . The Obp57d upstream region amplified with the primer pair 5′- ( EcoRI ) AAAGAATTC-TTAATACGAGTATATCCCAGCAAAATCGAT-3′ ( P1 ) and 5′- ( BamHI-loxP ) GGATCC-ATAACTTCGTATAGCATACATTATACGAAGTTAT-CAAACTAGTTGAAGATATCATAG −3′ and the downstream region amplified with the primer pair 5′- ( PstI-loxP ) CTGCAG-ATAACTTCGTATAATGTATGCTATACGAAGTTAT-GGACAAGTACTACGATACTGG −3′ and 5′- ( NotI ) GCGGCCGC-TATGAACACTCGCCGTGGTC-3′ ( P2 ) were subcloned into pP{EndsOut2} with hsp70-white excised from the pBSII-70w with BamHI and PstI . The Obp57e upstream region amplified with the primer pair 5′- ( BamHI-loxP ) GGATCC-ATAACTTCGTATAGCATACATTATACGAAGTTAT-ACTTGCTATATTCCTAGGGAA −3′ and P1 and the downstream region amplified with the primer pair primers 5′- ( PstI-loxP ) CTGCAG-ATAACTTCGTATAATGTATGCTATACGAAGTTAT-GCGGCCGAGAAGTATGTTTC-3′ and P2 were subcloned into pP{EndsOut2} , similarly to the case of Obp57d . The Obp57d upstream region and the Obp57e downstream region were used for the Obp57d/e targeting vector . The fly transformation and targeting crosses were carried out as described by Sekelsky ( http://rd . plos . org/pbio . 0050118 ) . Two , one , and three knock-out lines were obtained for Obp57d , Obp57e , and Obp57d/e , respectively . Each knock-out line was backcrossed to the w1118 control strain for five generations . Genomic fragments including Obp57d/e were PCR cloned from D . simulans and D . sechellia with the primers P1 and P2 , and cloned into the pCaSpeR3 transformation vector . The w1118; Obp57d/eKO strain was transformed with these vectors by the established method . At least three independent transformant lines were obtained for each construct . RNA was extracted from the legs or heads of 20 staged females using an RNeasy Micro kit ( Qiagen , http://www1 . qiagen . com ) . cDNA was made using a SuperScript III First-strand Synthesis System ( Invitrogen , http://www . invitrogen . com ) with the oligo ( dT ) 20 primer . Quantitative RT-PCR was carried out with the Chromo 4 realtime PCR analysis system ( BioRad , http://www . bio-rad . com ) using SYBR Premix ExTaq ( Takara , http://www . takara-bio . com ) with primers 5′-TTATTTTGGAAATTCAATTTAGAACTGCCG-3′ and 5′-TGATTCGGCTATATCTTCGTCTATTCCTTG-3′ for D . melanogaster Obp57d , 5′-TGCGCAAATGTTCTCGCTAACACTT-3′ and 5′-ATTCTCCATCACTTGGTGGGCTTCATA-3′ for D . melanogaster Obp57e , 5′-TTATTTTGGAAATTCAGTTTAGAATTTCCG-3′ and 5′-AATTGCTTCAGCTATATCTTCGTCTATTCC-3′ ( P3 ) for D . simulans Obp57d , 5′-TGCGCAAACGTTCTTGCTTACACTT-3′ and 5′-GGCCATTTCTCCATCACTTGGTTG-3′ ( P4 ) for D . simulans Obp57e , 5′-TTGGAAATTCAGTTTAGAAATTCTGAATGT-3′ and P3 for D . sechellia Obp57d , 5′-TGTGCGCAAATGTTCTTGCTTACACTT-3′ and P4 for D . sechellia Obp57e , and 5′-GCTAAGCTGTCGCACAAATG-3′ and 5′-TGTGCACCAGGAACTTCTTG-3′ for rp49 of all species . Either of a primer pair was designed at an exon boundary to ensure amplification only from spliced transcripts . Staged females were individually supplied with media ( 1% yeast extract [Gibco , http://www . invitrogen . com/content . cfm ? pageid=11040] ) and 0 . 8% Bacto Agar [Gibco] ) containing an acid at four concentrations ( 0 mM , 10 mM , 20 mM and 30 mM for acetic acid , butyric acid , and HA; and 0 mM , 2 . 5 mM , 5 mM , and 7 . 5 mM for OA ) simultaneously , and allowed the choice of medium for oviposition in a dark , ventilated box overnight at 25 °C . The number of eggs laid on each medium was scored , and the weighted mean of acid concentration was calculated for each individual . At least 36 individuals were tested for each strain with three replications . Obp57d/e sequence data have been deposited under the GenBank ( http://www . ncbi . nlm . nih . gov/Genbank ) accession numbers AB232138–AB232143 .
Most herbivorous insects specialize on one or a few host plants; understanding the processes and genetics underlying this specialization has broad implications across biology . Drosophila sechellia , a fruit fly endemic to the Seychelles , feeds exclusively on the ripe fruit of Morinda citrifolia , a tropical plant commonly known as Tahitian Noni . Although other fruit flies never approach this fruit because of its toxins , D . sechellia is resistant and is actually attracted by the same toxins . D . sechellia is a close relative of D . melanogaster , an established model species of genetics . By comparing D . melanogaster and D . sechellia , we revealed that two genes encoding odorant-binding proteins , Obp57d and Obp57e , are not only involved in the fruit fly's taste perception , but can also change the behavioral response of the flies to the toxins contained in the fruit . By knowing how an insect's food preference is determined by its genes , we can gain insight into how insect lifestyles evolve and investigate whether such changes can lead to the formation of new species . We can also begin to understand how to manipulate insects' behavior by changing their preference for particular substances .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods", "Supporting", "Information" ]
[ "ecology", "arthropods", "eukaryotes", "evolutionary", "biology", "drosophila", "neuroscience", "animals", "genetics", "and", "genomics", "insects" ]
2007
Odorant-Binding Proteins OBP57d and OBP57e Affect Taste Perception and Host-Plant Preference in Drosophila sechellia
Meiosis is a specialized cell division used by diploid organisms to form haploid gametes for sexual reproduction . Central to this reductive division is repair of endogenous DNA double-strand breaks ( DSBs ) induced by the meiosis-specific enzyme Spo11 . These DSBs are repaired in a process called homologous recombination using the sister chromatid or the homologous chromosome as a repair template , with the homolog being the preferred substrate during meiosis . Specific products of inter-homolog recombination , called crossovers , are essential for proper homolog segregation at the first meiotic nuclear division in budding yeast and mice . This study identifies an essential role for the conserved Structural Maintenance of Chromosomes ( SMC ) 5/6 protein complex during meiotic recombination in budding yeast . Meiosis-specific smc5/6 mutants experience a block in DNA segregation without hindering meiotic progression . Establishment and removal of meiotic sister chromatid cohesin are independent of functional Smc6 protein . smc6 mutants also have normal levels of DSB formation and repair . Eliminating DSBs rescues the segregation block in smc5/6 mutants , suggesting that the complex has a function during meiotic recombination . Accordingly , smc6 mutants accumulate high levels of recombination intermediates in the form of joint molecules . Many of these joint molecules are formed between sister chromatids , which is not normally observed in wild-type cells . The normal formation of crossovers in smc6 mutants supports the notion that mainly inter-sister joint molecule resolution is impaired . In addition , return-to-function studies indicate that the Smc5/6 complex performs its most important functions during joint molecule resolution without influencing crossover formation . These results suggest that the Smc5/6 complex aids primarily in the resolution of joint molecules formed outside of canonical inter-homolog pathways . Meiosis is the cell division by which haploid gametes are created in sexually reproducing organisms . It is specialized to preserve the chromosome number among generations and to create genetic diversity in a population . Meiosis begins with the replication of each homologous parental chromosome ( homolog ) into a pair of sister chromatids . Two sequential rounds of DNA segregation then follow . The first , MI , segregates the homologs away from each other , while the second , MII , separates the sister chromatids . This leads to the formation of four haploid cells from a single diploid parent . Prior to homolog segregation , programmed DNA double-strand breaks ( DSBs ) are induced that are repaired through a process called homologous recombination . In budding yeast and mice , recombination is essential for proper homolog segregation at MI . Together with sister chromatid cohesion , recombination facilitates segregation by creating stable attachments between the maternal and paternal homologs , thus ensuring their correct organization in preparation for anaphase I [1] . Meiotic DSBs are catalyzed by the enzyme Spo11 [2] , [3] . After DSB induction , the ends of the DSB are resected to form single-stranded DNA overhangs that can invade a homologous sequence for repair . An initial DNA joint molecule ( JM ) is then formed following exchange of the broken end with a homologous sequence ( Figure S1 ) . The JM is further processed and enzymatically resolved according to its composition to generate two types of products: Those that mutually exchange DNA sequences between the homologs to physically attach them , called crossovers ( COs ) , and those that repair without mutual exchange , called non-crossovers ( NCOs ) [4] , [5] . Initial stabilization after invasion of the break end forms a transient JM called a single-end invasion ( SEI ) ( Figure S1 ) [6] . Displacement of the invading strand of the SEI , such as in helicase-mediated unwinding by the BLM ortholog Sgs1 , followed by ligation with the free DSB end , forms a NCO in a process called synthesis-dependent strand annealing ( SDSA ) ( Figure S1A ) [6]–[8] . Alternatively , the SEI can be stabilized and processed to form a stable JM intermediate known as a double-Holliday junction ( dHJ ) ( Figure S1B ) [9] . The dHJ must be cleaved by endonucleases or dissolved using a helicase in combination with a topoisomerase in order to be processed into its products [5] , [10] . During meiosis , NCOs and dHJ-JMs form concurrently while COs form after dHJ disappearance , indicating that COs are the main products of dHJ resolution ( Figure S1C ) [11] , [12] . NCOs , on the other hand , are primarily formed via SDSA [11] . Regulating the formation and resolution of dHJ-JMs is essential for homolog segregation at MI , and several factors have been identified that specifically promote CO formation without influencing overall DSB repair [10] . Most of these proteins belong to the meiosis-specific ZMM ( Zip1-4 , Mer3 , Msh4 , Msh5 , Spo16 ) family , which stimulate COs by stabilizing dHJ formation [13]–[15] . The phosphatase PP4 ( Pph3/Psy2 ) also promotes proper CO formation by stabilizing SEIs [16] . Moreover , recent evidence has implicated the mismatch repair components Exo1 and the MutLγ complex Mlh1–Mlh3 as crossover-specific JM resolution factors [17] . While the ZMM proteins regulate the majority of COs in budding yeast and mice , a subset is dependent on the endonuclease Mus81-Mms4 [18]–[20] . In fission yeast , however , all COs form via the Mus81-Eme1 ( Mus81-Mms4 in budding yeast ) pathway and are derived from single , rather than double , HJs [21]–[24] . Chromatin in budding yeast is organized in a loop-axis configuration [25] . Meiotic DSB hotspots are located in the DNA loops while recombination is carried out close to the meiotic axis [26] , [27] . Normal DSB induction is dependent of the tethering of DSB hotspot sequences to accessory DSB proteins at the axis prior to break induction [28]–[30] . Hence , proper meiotic recombination relies on correct loop-axis configuration and events that change this architecture alter recombination events and outcomes [27]–[31] . Despite the presence of the sister chromatid , the homologous chromosome is preferred as a repair template during meiosis [32] . This inter-homolog ( IH ) bias is due to combined efforts of mechanisms that promote invasion of the homolog strand , and components of the meiotic axis that physically block sister invasion [32]–[37] . The meiotic axis includes the cohesin subunit Rec8 , which is required for proper axis formation and loop organization [38] . In the absence of Rec8 , the loop-axis configuration is perturbed and DSBs form at low levels with altered distribution as compared to wild-type cells [39] , [40] . The axis-organizing function of Rec8 is also needed to maintain IH bias during the SEI-to-dHJ transition , even though Rec8 is actually a promoter of inter-sister ( IS ) recombination most likely due to its role in sister chromatid cohesion ( see below ) [40] . The presence of IH-promoting axis components antagonize the IS bias created by Rec8 to allow IH events to dominate [40] . To further promote IH-recombination , the ZMM proteins form a structure called the synaptonemal complex ( SC ) between the homologs . The SC holds the homologs close to one another during recombination , thereby facilitating homolog-directed strand invasion [14] , [15] . Together these mechanisms establish a bias for IH recombination but do not eliminate IS recombination , with the possibility that up to one-third of all wild-type recombination events may be directed to the sister [40] , [41] . These IS repair events rarely go via a detectable JM intermediate , most likely due to the decreased preference for recombination via a IS-JM in combination with fast turnover rates for IS-JMs that may arise [42] . If inefficiently resolved , an inter-sister DNA link on the telomere-proximal side of a CO will inhibit the segregation of homologs at MI , making it crucial for cells to properly process inter-sister recombination events . As stated , the cohesin complex is a meiotic axis component required for proper recombination . It is also essential for sister chromatid cohesion during mitosis and meiosis [43] . Cohesin is a member of the evolutionarily conserved structural maintenance of chromosomes ( SMC ) family of proteins , which also includes the Smc5/6 complex . Components of the Smc5/6 complex were first identified as repair proteins working in the homologous recombination pathway [44]–[46] . The complex consists of eight subunits: Smc5 , Smc6 , Nse1 , Mms21 ( Nse2 ) and Nse3-6 , and assists in the reduction of topological stress during replication as well as DSB repair in post-replicative vegetative cells [46]–[50] . Cells harboring mutations in SMC5 , SMC6 or MMS21 accumulate recombination intermediates following DNA damage inflicted during mitotic S phase [51]–[53] . Mutating genes involved in the resolution of aberrant recombination structures at blocked replication forks , such as MUS81-MM4 , SGS1 and TOP3 , aggravates this phenotype [54]–[56] . Recent studies have pointed to a role for the Smc5/6 complex during meiotic recombination as well . A study in C . elegans showed that the Smc5 and Smc6 proteins are required to process recombination structures in germ line cells [57] . In fission yeast , nse1-3 are needed for proper meiotic chromosome segregation [58][59] . In addition , fission yeast cells harboring mutations in nse6 accumulate meiotic JMs in the form of single HJs that resemble those found in cells lacking the endonuclease Mus81 [59] . Although the HJs are DSB-dependent , the nse6 mutant used in this study was not meiosis-specific and accumulated recombination intermediates during mitosis and pre-meiotic S phase as well [59] . Thus , the meiotic intermediates observed may have been a consequence of lesions accumulated prior to meiotic induction . A study in budding yeast was also unable to isolate a meiosis-specific phenotype for mutants of the Smc5/6 protein complex . The segregation block in these smc6 mutants was not DSB-dependent and most likely caused by defects accumulated during mitosis or pre-meiotic S-phase [60] . Due to the discrepancies between these studies , the meiotic function of the Smc5/6 protein complex remains unclear . In this study , we employed meiosis-specific alleles of genes encoding for the Smc5/6 complex to investigate the meiotic role of the complex in the budding yeast Saccharomyces cerevisiae . Cells lacking components of the Smc5/6 complex during meiosis experience a segregation block that is dependent on DSB formation . Mutants are normal in meiotic prophase progression and DSB repair and have no significant defects in sister chromatid cohesion . Return-to-function studies indicate that the complex works at later stages of meiotic recombination . This function is most critical at times of JM resolution , and cells with non-functional Smc6 accumulate high levels of JMs in the form of both IS- and IH-JM intermediates . CO and NCO levels remain unchanged , indicating that the majority of IH-JMs are processed normally , and suggesting that most of the unresolved JM intermediates are derived from inter-sister recombination events . These findings demonstrate that the Smc5/6 protein complex is directly involved in meiotic recombination and suggest that Smc6 plays a key role in resolving recombination intermediates during meiosis , especially those that form between sister chromatids . To initially address the meiosis-specific function of the Smc5/6 protein complex , the temperature-sensitive smc6-56 allele was utilized . This mutant has known mitotic recombination defects at high temperature [51] , [61] . At permissive temperature , smc6-56 cells underwent normal meiotic divisions and formed viable spores ( Figure S2A ) . When meiosis was carried out at non-permissive temperature from the time of meiotic induction , the smc6-56 mutant exhibited a mixture of two phenotypes: cells that did not appear to have entered the meiotic program and accumulated as mononucleates , and cells that failed to segregate chromosomes but formed spores ( Figure S2B ) . A mixed cell population was also observed in a previous study when cells with the temperature-sensitive allele smc6-9 were grown at non-permissive temperature from the time of meiotic induction [60] . The authors of this paper concluded that the meiotic defects in smc6-9 cells were largely due to problems acquired during mitosis or pre-meiotic S phase [60] . The mononucleate population in the smc6-9 and smc6-56 mutants resembles that observed in mitotic cells harboring the smc6-56 allele , in which approximately half of the cells arrest in G2/M after replication at non-permissive temperature [49] . To focus on non-replicative meiotic functions , smc6-56 cells were allowed to complete pre-meiotic replication at permissive temperature before shifting to non-permissive temperature ( Figure 1A , Figure S2C ) . Under such “soft-shift” conditions , the smc6-56 mutant only formed cells containing one unsegregated DNA mass outside four empty spores ( Figure 1B ) . To confirm that this defect was not caused by high temperature and reflected the true meiotic phenotype of a smc5/6 mutant , meiotic-null ( mn ) alleles of SMC5 , NSE4 and NSE2 were constructed by replacing their endogenous promoters with the mitosis-specific CLB2 promoter [62] . Because CLB2 is not down-regulated until after pre-meiotic S phase , replication defects were avoided using this system [63] , [64] . As in the smc6-56 mutant , smc5-mn , nse4-mn and nse2-mn mutants were not able to segregate their chromosomes and instead formed cells with one DNA mass outside of four empty spores ( Figure 1B ) . This demonstrates that the smc6-56 phenotype reflects a meiotic function of the Smc5/6 complex . In S . cerevisiae , spores form around duplicated spindle pole bodies regardless of DNA location [65] . Thus the “one DNA mass outside of four empty spores” phenotype of smc5/6 mutants suggests that they complete the meiotic program . To test this hypothesis , spindle morphology was monitored in the smc6-56 mutant . In line with the idea that smc5/6 mutants do not hinder meiotic progression , smc6-56 cells were able to duplicate their spindle-pole bodies and elongate their spindles despite abnormal spindle morphology due to failure to segregate the DNA ( Figure 1C ) . To further challenge the assumption that smc5/6 cells complete the meiotic program , meiotic progression was analyzed by scoring the dynamics of Zip1 axes . Zip1 is a ZMM component of the SC [66] . Cells that are unable to complete recombination form incomplete Zip1 axes and do not progress past prophase [67] . Mutants lacking the transcription factor Ndt80 can initiate recombination but fail to signal downstream factors necessary to complete recombination and exit prophase and accumulate with full Zip1 axes [68]–[70] . Zip1 axes were formed and removed normally in smc6-56 , smc5-mn and nse4-mn mutants ( Figure 1D ) . The smc6-56 mutant was also normal in the timing and morphology of Zip1 and Rec8 axes ( Figure 1E ) . Together , these data demonstrate that cells lacking Smc5/6 components fail to segregate their DNA but do not halt the meiotic cell cycle . To test if the segregation block in Smc5/6 complex mutants was due to meiotic recombination , nuclear divisions were monitored in a spo11Δ background . Cells devoid of SPO11 do not initiate meiotic recombination and improperly segregate their DNA since they lack attachments between the homologs [2] . Even though the resulting spores are unviable , DNA segregation can be monitored within the cells . Deletion of SPO11 in smc6-56 , smc5-mn , nse4-mn and nse2-mn mutants abolished the segregation block ( Figure 1F ) , indicating that the segregation defect in these cells is the result of problems during DSB repair . To test whether the nuclear division failure was due to break-independent sister entanglements , segregation was examined in cells containing the smc6-56 mutation in a spo11Δ spo13Δ background . SPO13 is required to prevent biorientation of sister kinetochores at meiosis I , and , in the absence of recombination , spo13Δ cells undergo a single meiotic division , segregating sister chromatids to form cells with two viable , diploid spores called dyads [71] , [72] . The spo11Δ spo13Δ smc6-56 mutant segregated its sisters efficiently and formed viable dyads under soft-shift conditions ( Figure S3 ) . These data confirm that the segregation block in smc6 mutants is not due to recombination-independent sister entanglements . To further study meiosis in smc6-56 cells , sister chromatid separation was assessed at sites 35 kb from the centromere and 23 kb from the telomere of chromosome V . These regions were observed using the previously described GFP-tagged Tetracycline repressor/operator ( TetR-GFP/Tet-O ) system . This system is based on endogenously expressed TetR-GFP , which accumulates at multiple copies of Tet-Os inserted at the chromosomal region of interest , thereby allowing its visualization by fluorescence microscopy [73] , [74] . Despite the full segregation block in smc6-56 cells , no major defect in sister chromatid cohesion or sister chromatid separation was observed at the centromere or telomere of chromosome V ( Figure 2A ) . Final levels of sister chromatid separation did not reach those in wild-type cells , but the results showed that sister chromatids were able to separate within the unsegregated DNA masses in smc6-56 mutants . This suggests that the Smc5/6 complex has little influence on meiotic sister chromatid cohesion and implies that the chromosomes in sm6-56 cells are held together by cohesin-independent mechanisms . This notion is further supported by the finding that smc6-56 cells can separate their sister chromatids in a spo11Δ spo13Δ background ( Figure S3 ) . To confirm that remaining cohesin was not the cause of the segregation block in smc6 mutants , cohesin dynamics were monitored on chromosome spreads using an epitope-tagged version of the meiosis-specific cohesin subunit , Rec8 . After being loaded between sister chromatids following DNA replication , Rec8 is removed from chromosome arms at the first nuclear division but maintained at centromeres until MII [75] . If cohesin remains between sister chromatid arms at the first nuclear division , homolog segregation will be blocked due to the inability to resolve COs at the chromosomal level [76] . The smc6-56 mutant was able to properly localize and remove Rec8 from the chromosome axis ( Figure 1E , Figure 2B ) , leading to the conclusion that the segregation block in this mutant is caused by cohesin-independent chromosome attachments . To examine the role of the Smc5/6 complex during meiotic break repair , DSBs were monitored at the HIS4LEU2 hotspot on chromosome III [12][77][78] . In this assay , smc6-56 mutants were able to repair their DSBs efficiently at the two sites analyzed ( Figure 2C ) . To investigate whether smc6-56 mutants have higher levels of break formation , DSB accumulation was investigated in a rad50S background . This mutant cannot resect the ends of the break and accumulates unprocessed DSBs [79] . The smc6-56 rad50S mutant had higher levels of breaks at one DSB site but normal levels at the other ( Figure 2D ) . Whole-chromosome break patterns were similar in smc6-56 rad50S and rad50S on chromosomes III , IV and VI ( and data not shown ) . These data show that DSB repair and distribution are unchanged in smc6 mutants but that overall DSB levels may be higher , at least at specific sites . The segregation block in the smc5/6 mutants is reminiscent of that observed in mutants that are unable to resolve JMs [8] , [17] , [80] , [81] . Factors that promote JM resolution and subsequent prophase exit are activated by the transcription factor Ndt80 . In the absence of NDT80 , cells accumulate in late prophase with unresolved JMs [82] , [82] . To initially assess if the Smc5/6 complex also plays a role during JM resolution , cells in which expression of NDT80 is controlled by an estradiol-inducible promoter ( NDT80-IN ) were utilized [83] . Combining the smc6-56 allele with NDT80-IN allowed the control of Smc6 activity by temperature shifts carried out concurrently to NDT80 induction . The smc6-56 cells were unable to segregate their DNA when taken into the ndt80 arrest at permissive temperature and released at non-permissive temperature ( Figure 3A ) . This was not due to incomplete arrest at the time of temperature upshift and NDT80 induction , since smc6-56 cells kept in the ndt80 block three hours longer before shifting to non-permissive temperature showed the same segregation block ( data not shown ) . At the final time point after release into non-permissive temperature after arrest at permissive temperature , smc6-56 cells were largely inviable ( Figure 3B ) . This suggests that the structures which block segregation are also lethal to the cells . If the smc6-56 mutant instead underwent the ndt80 arrest under soft-shift conditions and was shifted to permissive temperature during release , meiotic divisions were restored and cells completed both MI and MII with wild-type kinetics ( Figure 3C ) . These cells were also viable at the final time point ( Figure 3D ) . These data imply that SMC6 is most critical during JM resolution , and suggest that unresolved JMs are the cause of the segregation block and inviablilty in smc6 mutants . To assess whether JMs accumulate in smc6-56 mutants , recombination was examined at the molecular level at the ectopic URA3-ARG4 locus on chromosome III , which allows the detection of JMs in the form of dHJs using one-dimensional ( 1D ) gel electrophoresis ( Figure S5 ) [84]–[86] . This hotspot was used in combination with NDT80-IN under soft-shift conditions to test the hypothesis that the segregation block in smc6-56 cells is caused by the accumulation of unresolved JMs . The smc6-56 mutant accumulated a ≈3-fold higher number of JMs than the SMC6 strain ( 6 . 6% vs . 2 . 2% at 7 h ) prior to NDT80 induction ( Figure 4A–C ) . Following induction , approximately two-thirds of JMs in the smc6-56 mutant remained unresolved after 24 h . In spite of unresolved recombination intermediates , NCOs and COs accumulated at the same time and level in the smc6 mutant as compared to the SMC6 strain ( Figure 4B , C ) . Recombination products were also observed at wild-type levels at the HIS4LEU2 hotspot in the smc6-56 mutant ( data not shown ) . To better identify JM species , native-native two-dimensional ( 2D ) gel electrophoresis was utilized at the URA3-ARG4 locus in combination with the NDT80-IN system . This method of electrophoresis separates JMs by size in the first dimension and by shape plus size in the second dimension [87] . Prior to NDT80 induction , SMC6 cells accumulated a strong JM spot corresponding to the predicted size for IH-JMs ( P1×P2 ) ( Figure 4D , 7 h ) . This spot was flanked by two weaker regions: a slower-migrating spot predicted to be IS-JMs from P2 ( P2×P2 ) and a faster-migrating , less defined spot corresponding to IS-JMs from P1 ( P1×P1 ) ( Figure 4D ) . To verify the identity of these flanking spots as IS-JMs , recombination was examined in cells lacking the axial element protein Hop1 , in which the sister chromatid is preferred over the homolog as a repair template [42] , [88] . As anticipated , the hop1Δ mutant lacked the middle spot corresponding to IH-JMs and acquired the two outer spots predicted for IS-JMs , with P2×P2 being the dominating IS species ( Figure S6A ) . The indistinctness of the P1×P1 spot is due to the fact that the DSB hotspots at this locus are only located on the P2 homolog , directing the majority of inter-sister repair to this set of sister chromatids ( Figure S5 ) . Similar to the results obtained from the 1D gels , levels of total JMs from the 2D gels were approximately 2 . 5-fold higher in the smc6-56 mutant than in the SMC6 strain prior to NDT80 induction ( Figure 4D–E ) . A homolog-specific probe identified many of these JMs as IS-JMs in the smc6-56 mutant ( Figure S6B ) . Though some JMs in the smc6-56 mutant were resolved following release , about two-thirds of the total persisted at the final time point ( Figure 4E ) . Further examination of JM composition revealed that smc6-56 cells formed JMs composed of a higher ratio of IS-JMs compared to SMC6 cells in the ndt80 arrest ( Figure 4D 7 h , 0 . 43 vs . 0 . 19 of total ) . After NDT80 induction , the ratio of IS-JMs to total JMs increased to over 0 . 6 in smc6-56 cells , though some IH-JMs persisted as well . Similar results were obtained in an independent experiment ( Figure S7A ) . These data indicate that SMC6 prevents the formation of excess JMs and facilitates the resolution of JMs; especially those formed between sister chromatids . To test if SMC6 is needed for JM resolution , JMs were examined under conditions when the Smc6 protein was functional during the ndt80-mediated arrest and then made non-functional during release . In this situation , the smc6-56 mutant was inviable and unable to segregate its DNA ( Figure 3A–B ) . JM formation was normal when smc6-56 cells were arrested at permissive temperature ( Figure 5A–E ) . When shifted to non-permissive temperature at the time of NDT80 induction , JMs were not fully resolved , and no significant decrease in CO or NCO levels was detected ( Figure 5A–E ) . Possible reasons for the counter-intuitive finding that IH-JMs persist without a detectable decrease in CO formation are considered in the discussion . Upon closer examination , the ratio of IS-JMs out of total JMs at the final time point is increased to 0 . 67 from its ratio of 0 . 23 at the time of ndt80 release ( Figure 5D ) . IH-JMs remained as well , but some were apparently resolved , as reflected in the decreased IH-JM ratio and formation of COs at later time points . Similar results were found in an independent experiment ( Figure S7B ) . Together these results implicate a role for SMC6 in the resolution of IS-JMs and , to a lesser extent , IH-JMs that form under normal conditions . When Smc6 is non-functional during ndt80 arrest but functional during release , cells successively completed nuclear divisions ( Figure 3C ) and formed normal levels of CO and NCO products ( Figure 6A–C ) . Prior to NDT80 induction , the smc6-56 mutant formed ≈3-fold higher total JM levels ( Figure 6C , E ) . At this time point , the ratio of IS-JMs to the total on the 2D gels was 0 . 62 in the smc6 mutant , compared to 0 . 20 in the SMC6 strain . When Smc6 function was restored at the time of NDT80 induction , all JMs were resolved ( Figure 6A , C , D , E ) . Similar results were obtained from 2D gels from an independent experiment ( Figure S7C ) . This supports the notion that the rescue in nuclear divisions is due to the restoration of JM resolution . The JMs that accumulated in the absence of SMC6 function were not lethal , as viability was also restored when the cells were shifted to permissive temperature ( Figure 3D ) . These results show that all JMs formed without functional Smc6 can properly be resolved if Smc6 function is restored during JM resolution . To gain additional insights into the function of the Smc5/6 complex during meiotic recombination , an N-terminal epitope-tagged version of Smc6 was used to analyze the complex's binding on chromosome spreads using immunofluorescence . The tagged version of SMC6 was fully functional and neither impeded events during meiotic prophase nor delayed meiotic segregation ( data not shown ) . Smc6-Myc appeared on chromosomes during early prophase around the time of Rec8 foci formation ( Figure 7A ) . When the Rec8 axis began to organize , Smc6's binding became more profuse and formed an axis-like structure . On full-length axes , Smc6 localized at regions with weaker Rec8 signals as well as at sites with more profuse Rec8 signals ( Figure 7C , solid and dashed arrows , respectively ) . Consistent with results from a previous study [60] , Smc6 bound abundantly to the rDNA , seen by the brightly staining Smc6 region ( Figure 7A , green ) corresponding to weak DAPI staining . After late prophase , the Smc6-Myc signal became diffuse and disappeared prior to MI . Removing cohesin seemed to reduce the amount of Smc6 foci and eliminated the axis-like pattern of Smc6 ( Figure 7B ) . Western blotting revealed that Smc6 protein levels were similar in the wild type and in the rec8Δ mutant , indicating that the diminished levels of Smc6 binding were not due to decreased Smc6 protein levels in this cohesin mutant ( Figure S8 ) . This demonstrates that cohesin is required for the proper organization of Smc6 foci on chromosomes and suggests that localization of the Smc5/6 complex is influenced by meiotic axis structure and/or the presence of sister chromatid cohesion . The results presented here suggest that the Smc5/6 complex prevents excessive JM formation and aids in JM resolution during meiosis . This resolution function is particularly critical for JM intermediates formed between sister chromatids . Similar to other mutants defective in JM processing , smc5/6 mutants experience a recombination-dependent segregation block without halting meiotic progression [8] , [17] , [80] , [81] . This could indicate that Smc6 works together with established resolution pathways , such as those mediated by the ZMMs or Sgs1/Mus81-Mms4 . Unlike those mutants , however , the smc6-56 mutant does not lead to any detectable decrease in CO or NCO levels , suggesting that it works predominately outside of canonical meiotic recombination pathways . Given the normal levels of COs and NCOs , and the nature of the persisting JMs , we propose that in the absence of Smc6 , cells accumulate primarily IS-JMs , but also a subset of IH-JMs ( Figure 8 ) . When JM formation occurs without Smc6 function , overall JM levels are 2 . 5–3-fold higher than in cells with functional Smc6 ( Figure 4C , E , Figure 6C , E ) . The ratio of IS-JMs to total JMs in the smc6-56 mutant is twice that in SMC6 cells ( Figure 4D , Figure 6D ) . Although IH-JMs are still the dominating species , the absence of Smc6 diminishes the IH-bias slightly . This may be due to higher levels if IS recombination in the smc6-56 mutant or due to an accumulation of normally transient IS-JM intermediates that cannot be resolved without functional Smc6 . When NDT80 is induced in the continued absence of Smc6 function , about three-fourths of total JMs persist and the IS-JM ratio increases further , though some IH-JMs also persist ( Figure 4C , D ) . Surprisingly , CO formation is normal in spite of persisting IH-JMs . One explanation for this could be that these lingering IH-JMs are not significant enough in number to cause a detectable decrease in CO levels ( Figure 8 ) . As an alternative , extra IH-JMs could come from additional recombination-initiating events , which has been shown to occur in some mutants [11] . The smc6-56 mutant does form slightly higher numbers of DSBs at one break site in the rad50S background ( Figure 2D , DSBII ) . If this also occurs at other sites , it may account for some of the increase in the levels of recombination in the smc6 mutant . More recombination-initiating events would also explain the IH-JMs that are never resolved , despite normal CO levels , when Smc6 is non-functional from the time of meiotic induction ( Figure 4A–D ) . This suggests that cells lacking functional Smc6 accumulate recombination intermediates that will require Smc6 for their resolution . In line with this hypothesis , when cells lacking Smc6 function during JM formation are released from the ndt80 arrest in the presence of functional Smc6 , all JMs are resolved , despite the higher ratio of IS-JMs at the time of release and higher overall JM levels ( Figure 6 ) . COs and NCOs are formed efficiently ( Figure 6B , C ) , and DNA segregation and viability is rescued ( Figure 3C , D ) . This indicates that the JMs formed in the mutant can be properly resolved when Smc6 function is restored ( Figure 8 ) . This reversible phenotype is similar to what has been observed for the inter-sister recombination intermediates which accumulate in mitotic cells lacking Smc6 function [89] . Finally , when Smc6 is functional during JM formation in an ndt80-mediated arrest , both the levels and ratios of JMs are normal ( Figure 5A , C , D , E ) . Upon release into conditions that render Smc6 non-functional , however , three-fourths of total JMs persist and cells are unable to segregate their DNA ( Figure 5C , Figure 3A ) . The remaining JMs are composed of both IS-JMs and IH-JMs , but the ratio of IS-JMs increases upon shift to non-permissive temperature ( Figure 5D ) . A fraction of IH-JMs is resolved , as reflected in the efficient formation of COs and decrease in the IH-JM ratio ( Figure 5A–D ) . One explanation for why these unresolved IH-JMs do not lead to a detectable decrease in CO formation is that they contribute to a very small portion of total CO levels not distinguishable in the assays used here ( Figure 8 ) . NCO formation is also normal , indicating that the remaining JMs are not caused by converted SDSA events ( Figure 5B , C ) . These data suggest that a subset of IH-JMs that form under normal conditions require Smc6 for their resolution , while nearly all IS-JMs seem to rely on Smc6 for their resolution ( Figure 8 ) . This finding correlates with the role of the Smc5/6 complex in the resolution of sister chromatid intermediates during homologous recombination during mitosis in yeast [53] and in germ line cells in C . elegans [57] . Even though the presented evidence suggests a role for the Smc5/6 complex outside of canonical recombination pathways , the possibility that it works together with other recombination pathways cannot be ruled out ( Eva Hoffman , personal communication; Franz Klein , personal communication ) . In a wild-type meiosis , almost all NCOs are derived from the SDSA pathway and do not resolve via a JM intermediate [11] , [12] . In contrast , in cells lacking SGS1 , what should have been SDSA events are instead stabilized and transformed into dHJs [8] . These are later resolved into both NCO and CO products , thereby delaying the timing of NCO formation until JM resolution is induced [8] . With that in mind , the additional JMs in the smc6-56 mutant presented here could come from the conversion of NCO-forming SDSA events into JM intermediates . However , the smc6-56 mutant is not defective in the timing of NCO formation under non-permissive conditions , and forms most of its NCOs prior to NDT80 induction ( Figure 4B , C , Figure 6B , C ) . Final NCO levels are also normal , indicating that the JMs that remain in the smc6-56 mutant are not derived from the conversion of SDSA events into unresolvable JMs . Here we show that the smc6-56 mutant is able to establish sister chromatid cohesion and efficiently localize and remove cohesin from chromosomes ( Figure 2B , Figure 1C ) . Mutants in other subunits of the Smc5/6 complex have been reported to inhibit full removal of meiotic cohesin ( Eva Hoffman , personal communication ) . One explanation for this discrepancy could be that some components of the Smc5/6 complex work in different pathways . The segregation block in an smc5-mn mutant is also reported to be partially rescued when Rec8 is artificially removed from chromosomes ( Eva Hoffman , personal communication ) . While this result could point towards a function for Smc5 in cohesin removal , it could also support the notion that the Smc5/6 complex is needed to resolve IS recombination intermediates . Removing sister chromatid cohesion reduces the likelihood of IS repair , thereby decreasing the level of IS recombination and allowing some smc5-mn cells to segregate their chromosomes . While the smc6-56 mutant can separate some of its sister chromatids at the telomere and centromere on chromosome V , this segregation is not complete ( Figure 2A ) . This is not due to an abnormal version of cohesion , as cells forced to undergo a mitosis-like division in the absence of recombination can separate their sister chromatids ( Figure S3 ) . Instead , the sisters are most likely held together by DNA attachments and not cohesin , as illustrated by data showing that the smc6-56 mutant accumulates unresolved JMs between sister chromatids . In addition , the centromeric and telomeric regions have been suggested to be hotspots for meiotic inter-sister repair [90] , which could explain why less than half of the sister chromatids are able to separate at these regions despite cohesin removal in smc6-56 cells . Smc6 localizes to meiotic chromosomes as well as to the rDNA ( Figure 7A ) . Preliminary evidence suggests that its binding pattern may reveal its precise localization on the meiotic axis , i . e . whether it sits at or between Rec8 sites ( Figure 7C ) . Indeed , abolishing sister chromatid cohesion by removing Rec8 reduces the binding of Smc6 to chromosomes , suggesting that cohesin may guide Smc6 localization ( Figure 7B ) . It is possible that the absence of sister chromatid cohesion reduces the likelihood of inter-sister recombination , which in turn diminishes the loading of Smc6 . Alternatively , or in addition , the stable association of Smc6 to chromosomes may require proper axis formation and/or cohesion as such . Deletion of REC8 only diminishes the binding of Smc6 , indicating that other factors dictate the loading of Smc6 to meiotic chromosomes . It will be interesting to learn what role the Smc5/6 complex plays in meiotic chromatin organization in order to gain further insights into its role during recombination . In conclusion , this study identifies a crucial role for the Smc5/6 complex in processing of recombination intermediates during meiotic recombination . Mutants in the Smc5/6 complex acquire high levels of recombination intermediates between homologs and sister chromatids . The majority of IH-JMs are resolved , as reflected by the decreased ratio of IH-JMs at the final time points and the normal level of COs . IS-JMs , on the other hand , seem to depend on the function of Smc6 for their resolution . We therefore propose that the main impediment to homolog segregation in smc5/6 mutants is unresolved linkages between sister chromatids , though some homolog attachments contribute to the segregation defect as well . Strains used for this investigation are derivatives of SK1 [91] and are shown in Table S1 . Gene deletions and C-terminal epitope tags were introduced using standard methods [92] . The smc6-56 allele was integrated at its endogenous locus and contains three point mutations in the coil-coil region of the protein which render it temperature-sensitive [61] . Meiotic nulls for SMC5 , NSE4 and NSE2 were made by replacing the endogenous promoters with the CLB2 promoter using one-step gene replacement [62] . The NDT80-IN strains have been described [82] , [83] . Liquid media , pre-sporulation and sporulation conditions were done using SPS media according to previously described methods [93] . Cultures were grown with vigorous shaking in baffled flasks at least ten times larger than the culture volume to achieve optimum synchrony . Permissive temperature was defined as 25°C , non-permissive temperature was 33°C . For the soft-shift setup , pre-sporulation plates and cultures were grown at 25°C . Once shifted to sporulation media , the cells were grown for 2 . 5 hours at 25°C before raising the temperature to 33°C . All experiments were performed at least twice with results similar to those presented in the figures here . Expression of NDT80-IN was induced by the addition of β-estradiol at a final concentration of 1 µM 7 h after meiotic induction . The HIS4LEU2 locus used for DSB analysis has been described [6] , [78] . The ectopic locus on chromosome III used for 1D and 2D JM analyses as well as CO/NCO detection is illustrated in Figure S5 and has been described [11][11] . For native-native two-dimensional gel electrophoresis , psoralen cross-linked DNA was extracted from meiotic cultures as described in [94] and references therein . After digesting with XmnI , DNA samples were run on a 0 . 4% SeaKem GTG agarose gel ( Lonza ) lacking ethidium bromide in 1X TBE ( 90 mM Tris-borate , 2 mM EDTA pH 8 ) at 1 V/cm for 24 hours at room temperature . Gels were stained for 10 minutes in 1X TBE containing 0 . 3 µg/mL ethidium bromide , and lanes were excised and laid perpendicular to the direction of current for the second dimension . The gel for the second dimension , 0 . 8% SeaKem GTG agarose ( Lonza ) in 1X TBE plus 0 . 3 µg/mL ethidium bromide , was cast around the gel slices and allowed to harden . Electrophoresis in the second dimension was carried out in 4°C for 6 hours at 4 V/cm in 1X TBE containing 0 . 3 µg/mL ethidium bromide with pumping from the cathode to the anode . Gels were subjected to Southern blot analysis and probed with ARG4 coding sequences ( +165 to +1413 ) . DNA preparation and one-dimensional electrophoresis for JM assays were done as described using conditions that stabilize JM intermediates [95] . JMs were analyzed using XmnI digests probed with ARG4 coding sequences ( +165 to +1413 , argD ) , COs/NCOs were analyzed using XhoI/EcoRI double digests probed with HIS4 coding sequences ( +538 to +718 , hisU ) . DNA was transferred to nylon membranes via downward capillary transfer using standard techniques . After cross-linking the DNA , the membranes were pre-hybridized in Church buffer ( 1% w/v BSA , 1 mM EDTA , 0 . 5 M phosphate buffer , 7% w/v SDS ) for approximately 4 hours at 65°C and hybridized with the radioactively labeled probe overnight at 65°C . After washing , signals were detected on an imaging plate with a FLA-7000 image reader and quantified using Multi Gauge software , all from Fujifilm . Quantifications of 1D and 2D gels were done using Multi Gauge software by selecting equivalent regions of interest , including one to measure the background of the region . Sizes of expected products were determined using molecular weight standards . The signal was corrected for background and divided by the sum of the measured region and the standard region ( in all cases , the parental region ) . Similar blots were treated equally; for instance , regions of interest used to measure CO/NCO species were the same size for each blot . Further details regarding quantifications of JM species from 2D gels are given in Figure S9 . All experiments were performed at least twice with results similar to those presented . Nuclear morphology was scored by DAPI ( 4′ , 6-diamidino-2-phenylindole ) staining of ethanol-fixed cells using standard protocols . In situ immuno-staining of fixed whole cells for microtubule detection was performed using conventional techniques with a monoclonal mouse anti-alpha Tubulin antibody ( DM1A , Abcam ) at a 1∶1000 dilution . Stained slides were mounted and DAPI-stained using ProLong Gold ( Invitrogen ) . Meiotic spreading was done on SuperFrost Plus slides according to the protocol previously described [96] with the exception that 5% Lipsol was used as a detergent . A 1∶500 dilution of rabbit-anti-Zip1 ( gift from K . Schmekel ) was used to detect Zip1 . Smc6-13Myc was detected using 1∶200 mouse-anti-Myc ( Invitrogen ) and Rec8-3HA was detected using 1∶200 rat-anti-HA ( Roche ) . Stained slides were mounted and DAPI-stained using ProLong Gold ( Invitrogen ) . Image acquisition of a single focal plane was done in Volocity ( Perkin Elmer ) with a Leica confocal microscope . Image processing and analysis was carried out in Volocity . Additional methods describing results shown in supporting figures can be found in Text S1 .
Most eukaryotic cells are diploid , which means that they contain two copies of each chromosome – one from each parent . In order to preserve the chromosome number from generation to generation , diploid organisms employ a process called meiosis to form gametes containing only one copy of each chromosome . During sexual reproduction , two gametes ( sperm and eggs in mammals ) fuse to form a zygote with the same chromosome number as the parents . This zygote will develop into a new organism that has genetic characteristics unique from , but still related to , both parents . The reduction of chromosome number and the reshuffling of genetic traits during meiosis depend on the repair of naturally occurring DNA breaks . Improper break repair during meiosis may block meiosis altogether or form genetically instable gametes , leading to fertility problems or defects in the offspring . The study presented here demonstrates the importance of the evolutionarily conserved Smc5/6 protein complex in upholding the integrity of meiotic repair processes . Our results show that cells deficient in components of the Smc5/6 complex lead to inviable meiotic products . Cells lacking functional Smc5/6 complex are unable to direct DNA repair to the proper template and accumulate abnormal repair intermediates , which inhibit the reductive division .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[]
2013
Inhibition of the Smc5/6 Complex during Meiosis Perturbs Joint Molecule Formation and Resolution without Significantly Changing Crossover or Non-crossover Levels
Unlike other dipteran disease vectors , tsetse flies of both sexes feed on blood and transmit pathogenic African trypanosomes . During transmission , Trypanosoma brucei undergoes a complex cycle of proliferation and development inside the tsetse vector , culminating in production of infective forms in the saliva . The insect manifests robust immune defences throughout the alimentary tract , which eliminate many trypanosome infections . Previous work has shown that fly sex influences susceptibility to trypanosome infection as males show higher rates of salivary gland ( SG ) infection with T . brucei than females . To investigate sex-linked differences in the progression of infection , we compared midgut ( MG ) , proventriculus , foregut and SG infections in male and female Glossina morsitans morsitans . Initially , infections developed in the same way in both sexes: no difference was observed in numbers of MG or proventriculus infections , or in the number and type of developmental forms produced . Female flies tended to produce foregut migratory forms later than males , but this had no detectable impact on the number of SG infections . The sex difference was not apparent until the final stage of SG invasion and colonisation , showing that the SG environment differs between male and female flies . Comparison of G . m . morsitans with G . pallidipes showed a similar , though less pronounced , sex difference in susceptibility , but additionally revealed very different levels of trypanosome resistance in the MG and SG . While G . pallidipes was more refractory to MG infection , a very high proportion of MG infections led to SG infection in both sexes . It appears that the two fly species use different strategies to block trypanosome infection: G . pallidipes heavily defends against initial establishment in the MG , while G . m . morsitans has additional measures to prevent trypanosomes colonising the SG , particularly in female flies . We conclude that the tsetse-trypanosome interface works differently in G . m . morsitans and G . pallidipes . During transmission of a pathogen , selection in the invertebrate vector may be of profound importance in dictating which pathogen genotypes are most prevalent in mammalian hosts . This evolutionary pressure can select for particular combinations of pathogen and vector species , and weed out less fit pathogen phenotypes regardless of any competitive advantage in the mammalian host , such as virulence or drug resistance . Tsetse flies ( Diptera: Glossinidae ) serve as vectors of several pathogenic trypanosome species in subsaharan Africa , but typically manifest high levels of resistance to infection [1] , [2] . Resistance mechanisms operate at a number of levels and time points during the trypanosome's complex developmental cycle within the fly . For Trypanosoma brucei , trypanosomes first establish infection in the tsetse midgut ( MG ) , initially in the gut lumen with subsequent invasion of the ectoperitrophic space via the peritrophic matrix ( PM ) enclosing the bloodmeal . The antimicrobial defences operating in the MG , such as antimicrobial peptides , lectins and reactive oxygen intermediates [3] , [4] , [5] , [6] , [7] , ensure that a high proportion of infections are cleared at this early stage . In the laboratory , these defences can be counteracted by , for example , feeding the flies on lectin-binding sugars or anti-oxidants [8] , [9] , [10] or knocking down expression of specific antimicrobial peptides or proteins using RNA interference [4] , [11] . Of the MG infections that persist , few subsequently result in a salivary gland ( SG ) infection and it is evident that the trypanosomes experience a severe population bottleneck , as the SG are invaded and colonised by very small numbers of trypanosomes [12] , [13] . The barriers to SG infection are unknown , but there are several points along this complex pathway where progression may potentially be blocked . From the MG , trypanosomes move anteriorly to invade the proventriculus and penetrate through the PM before migrating to the SG via the foregut . The proventriculus is known to be a highly immunogenic tissue [5] and this could influence the success of trypanosome invasion of the foregut or the differentiation from MG procyclics to migratory forms . Escape of trypanosomes from the proventriculus into the foregut would also be blocked if trypanosomes were unable to penetrate the PM . Little is known of SG immune responses , but these are also likely to be vigorous judging by the frequent failure of migratory trypanosomes to colonise the SG and establish infection [2] , [12] , [13] . A recent survey of genes expressed in tsetse SG revealed a large variety of potential immunity-related molecules , some of which are also expressed by MG and fat body tissues [14] . Unlike other dipteran vectors such as mosquitoes , sand flies and black flies , both male and female tsetse feed on blood and hence serve as trypanosome vectors . Intriguingly , fly sex appears to influence susceptibility to trypanosome infection . Male flies ( Glossina morsitans morsitans , G . m . centralis , G . pallidipes , G . fuscipes fuscipes ) showed higher rates of SG infection with T . brucei than females [15] , [16] , [17] , and it has been suggested that a sex-linked recessive gene is involved [16] . The underlying cause of this sex difference in susceptibility is not known . To investigate sex-linked differences in the development of trypanosome infections in tsetse , we compared the development of MG , proventriculus , foregut and SG infections in male and female flies of G . m . morsitans . Infections developed in the same way in both male and female flies until the final stage of SG invasion and colonisation , when the SG environment in the female fly proved to be much more inhospitable for trypanosomes . Comparison of G . m . morsitans with another tsetse species , G . pallidipes , showed a similar sex difference in susceptibility to SG infection though less pronounced . However , G . pallidipes manifested much greater resistance to MG infection than G . m . morsitans and remarkably little resistance to SG infection . It thus appears that these two tsetse species have evolved very different strategies to counter trypanosome infection . Comparison of male and female G . m . morsitans infected with T . b . brucei J10 confirmed previous findings that male tsetse flies establish greater numbers of SG infections of T . brucei than females [15] , [16] , [17] . While there was no significant difference in MG infection rates , a significantly higher proportion of MG infections progressed to SG infection in male than in female flies . The transmission index ( TI = infected salivary glands/infected MGs ) for male flies was over twice that for female flies ( P = 0 . 045; Fig . 1A ) . The progression of infection in these flies was monitored at points of transition in the developmental cycle to investigate the nature of the barriers to SG infection and influence of fly sex . In established MG infections , the first event we recorded was invasion of the proventriculus by trypanosomes migrating anteriorly within the ectoperitrophic space . In flies dissected 10–14 days after infection , only about three quarters had an infected proventriculus and there was no difference in infection rates between males and females ( Table 1 ) . In the proventriculus , trypanosomes arrest in G2 before undergoing an asymmetric division that yields one short and one long epimastigote; these are migratory stages and the short epimastigote is believed to invade the SG [18] , [19] , [20] . Asymmetric dividers were found in about 75% of infected proventriculi , with no significant difference between male and female flies ( Table 1 ) . The next event is that the migratory trypanosomes invade the foregut and can be found in the salivary exudate or spit , a mixture of regurgitated foregut contents and saliva from the SG produced by flies when they probe a surface with the proboscis [18] , [21] . To examine the foregut contents , we used individually-caged flies , which were allowed to probe onto warm microscope slides 7–28 days after infection; dissection results for these flies at day 28 are shown in Fig . 1A . Trypanosome-positive spit samples were only obtained from those flies subsequently found to have MG infection , but some flies ( about 20% ) with MG infection did not produce a positive spit sample during the whole observation period ( Fig . 1B ) . This reflects the failure of about 40% ( 27 of 64 ) MG infections to infect the proventriculus and produce asymmetric dividers ( Table 1 ) . Only a small proportion of spit-positive flies finally developed SG infection , just over 20% combining males and females ( Fig . 1B ) , which means that in the majority of infections the migratory trypanosomes either failed to reach the SG or to colonise them . Attrition was greater in female than male flies ( Fig . 1B ) , although the sex difference was not statistically significant . The relative proportions of trypanosome developmental stages in individual stained spit samples from male and female flies were similar ( Table 2 ) ; at this early stage of infection , few metacyclics were present . Additionally , the trypanosome composition of the spit sample had no bearing on whether a fly subsequently developed SG infection , as there was no significant difference in numbers of developmental stages in spit samples from flies with or without SG infection when dissected at 28 days ( Table 2 ) . However , there was a significant effect of gender on the rate at which flies became spit-positive , the females lagging behind the males ( Fig . 2: median time to positivity 10 or 14 days for males or females , respectively , P<0 . 05 ) . It was noticed that often very few trypanosomes ( typically <5 ) were present in spit samples from flies that became positive on or after 12 days , the majority of which were female . It is possible that colonisation is adversely affected by the later arrival and smaller numbers of migratory trypanosomes in female compared to male flies . However , this hypothesis was not borne out by statistical analysis of the combined data from male and female flies: of 48 flies that gave their first positive spit sample early ( 7–11 days after infection ) , 9 had positive SG at dissection ( 19% ) , whereas of 29 flies that produced their first positive sample late ( 12–21 days after infection ) , 6 were SG positive at dissection ( 21% ) ( P = 1 . 00 ) . So time of migration to the SG does not affect the success of SG colonisation . We compared infection rates of G . m . morsitans with those of G . pallidipes using the same strain of T . b . brucei , J10 . Without immunosuppressive supplements , MG infection rates were very low in G . pallidipes compared to G . m . morsitans ( Table 3 ) . The addition of N-acetyl-glucosamine ( NAG ) or L-glutathione ( GSH ) to the infected feed has been shown to enhance MG infection rates [8] , [9] in G . m . morsitans by blocking antimicrobial lectins or reactive oxygen species respectively , and this is also evident from the data collected here for G . m . morsitans ( Table 3 ) ; there is no effect of these supplements on SG infection rates except as a result of increased numbers of MG infections [8] , [22] . However , in contrast to G . m . morsitans , NAG appeared to be totally ineffective in boosting numbers of MG infections in G . pallidipes: no infected MG were found with NAG in G . pallidipes compared with 54 . 4% infected MG in G . m . morsitans ( Table 3 ) . The addition of GSH resulted in a large increase in numbers of infected MG for G . pallidipes ( 50 . 0% with GSH versus 1 . 3% without GSH ) , similar to the effect seen in G . m . morsitans ( 81 . 0% with GSH , 11 . 3% without GSH ) , but significantly lower comparing the two fly species ( P = 0 . 018 ) ( Table 3 ) . The high MG infection rates obtained with GSH enabled us to examine SG infection rates in G . pallidipes ( Fig . 3 ) . Comparison with G . m . morsitans showed that transmission was far more efficient in G . pallidipes , despite lower MG infection rates; the SG infection rates and TI for both sexes of G . pallidipes were significantly higher than for G . m . morsitans ( P<0 . 0001; Fig . 3 ) . In fact , all 17 male G . pallidipes with MG infection also had infected SG ( TI = 100% ) compared to only three of 38 male G . m . morsitans , and 13 of 17 female G . pallidipes with MG infection also had infected SG whereas none of 48 female G . m . morsitans with infected MG had infected SG . As for G . m . morsitans , there was a sex difference in TI and G . pallidipes males had a higher TI than females , though this was not significant . Although female G . pallidipes had higher MG and SG infection rates than males , the differences were not significant either ( Fig . 3 ) . The G . pallidipes colony from which our experimental flies were derived suffers from infection with a virus that causes the SG to become much enlarged , a condition called salivary gland hypertrophy ( SGH ) [23] , [24] . Although the prevalence of SGH is relatively low in the colony ( 3 . 8% ) , PCR diagnosis indicates that almost all flies are infected with SGH virus [23] . Viral load is significantly higher in symptomatic flies [24] , suggesting that while most flies control viral infection and are asymptomatic , a minority succumb and develop SGH . As it is not known how SGH affects trypanosome infection , we analysed whether there was an association between trypanosome infection and SGH in G . pallidipes infected with T . b . brucei ( J10 and other strains ) dissected at 28 days or later . The observed prevalence of SGH in our experimental flies at dissection was 11% ( 43 of 402 ) . Of the 43 flies with SGH , 38 had infected SG ( 88% ) , a significantly greater level of infection than flies with normal SG ( 247 SG infected of 359 flies , 69%; P = 0 . 008 ) . Although SGH is positively correlated with trypanosome infection , the large number of SG positive flies without SGH ( 69% ) shows that SGH is by no means essential for SG colonisation by trypanosomes in G . pallidipes . The tsetse fly is unusual among dipteran vectors of disease because both sexes feed on blood and hence transmit pathogenic trypanosomes . However , the sexes are not equally efficient vectors and males have been found to be more susceptible to infection with T . brucei than females [15] , [16] , [17] . To explore the underlying basis of this sex difference , we compared infections in male and female G . m . morsitans at a number of points in the trypanosome's developmental cycle within the alimentary tract and SG of the fly . Levels of attrition were similar in both male and female flies , until the final stage of SG invasion and colonisation . The only difference detected was among the trypanosomes that migrate from the MG to the SG via the foregut: in female flies these appeared later than in males . However , there was no detectable difference in the success of early or late migrating populations in invading and colonising the SG , so differential attrition at the trypanosome-SG interface remains the only underlying explanation for the observed sex difference . It appears that migratory trypanosomes encounter a very hostile environment in the SG . In G . m . morsitans SG colonisation was frequently unsuccessful and only about 20% of flies positive for migratory trypanosomes in spit samples were subsequently found to have SG infection . Compared to the MG , little is known about the functional immune response of the SG to trypanosomes , but there are now detailed studies of the SG transcriptome and proteome that describe an armoury of potential antimicrobial defensive molecules [14] , [25] . Presumably the host-parasite interaction in the SG is intensified by the invasive nature of trypanosome attachment , as the epimastigotes form extensive cell-cell junctions with the epithelial cells via the flagellar membrane [26] . We hypothesize that the SG environment of the female fly is far less hospitable than that found in the male fly , thus leading to lower rates of SG infection in female flies , but the factors accounting for this difference remain to be identified . Why might this sex difference in resistance to trypanosome infection have arisen ? In nature , because of the slow rate of tsetse reproduction , selection for female longevity must be intense . Each female fly gives birth to a fully grown larva every 8–9 days , the first larva being produced about 16 days after emergence and mating . In contrast , male flies reach sexual maturity within a week and can mate several times . For survival of the species , it is thus imperative that female tsetse live at least 24 days . Survival data from the field support this: in Zimbabwe the estimated mean ages of female G . m . morsitans and G . pallidipes were 29 and 48 days respectively , compared to about 15 days for males of both species [27] . Since T . brucei takes a minimum of about two weeks to complete its life cycle , female flies are more likely than males to be exposed to prolonged SG infection . If this is detrimental to fly survival , might trypanosomes themselves have driven the sex difference in resistance to SG infection ? Few studies have addressed the impact of trypanosome infection on tsetse fitness . There was no effect of trypanosome MG infection on tsetse mortality , although fecundity of infected females decreased [28] . Tsetse with SG infection take longer to feed than uninfected flies and show altered composition of the saliva [29] , implying that SG infection may indeed prejudice survival of flies in the wild . We found differences in the host-parasite interaction in G . pallidipes compared to G . m . morsitans and there is a marked species difference in fly susceptibility to T . b . brucei infection . In both G . m . morsitans and G . pallidipes the immune responses of the MG are robust and capable of destroying most trypanosomes before they have a chance to establish infection . These defences can be mitigated by use of NAG or GSH in G . m . morsitans , but only GSH was effective in G . pallidipes . In contrast , whereas only a small proportion of MG infections result in SG infection in G . m . morsitans , the migration of trypanosomes from MG to SG seems to proceed without hindrance in G . pallidipes . A comparative study of the humoral immune response of these two species showed that G . pallidipes has a higher baseline level of attacin in the fat body , proventriculus and midgut than G . m . morsitans; in G . pallidipes attacin levels increased after blood feeding and knockdown of attacin expression by RNA interference increased susceptibility to trypanosome infection [30] . Higher attacin levels may therefore be the underlying cause of the low MG infection rates we observed in G . pallidipes . The fact that immunosuppression with either NAG or GSH failed to work as efficiently in G . pallidipes compared to G . m . morsitans indicates that lectins and reactive oxygen species play a greater part in MG defence in G . m . morsitans . Despite its refractoriness to MG infection , we found that G . pallidipes was far more permissive than G . m . morsitans in allowing progression to SG infection , particularly in male flies . We also found a positive correlation between SG infection and viral SGH in G . pallidipes , suggesting the possibility that susceptibility to SG colonisation is associated with viral infection . This echoes the association of infection with the secondary endosymbiont Sodalis glossinidius with susceptibility to MG infection with trypanosomes [1] , [31] . The G . pallidipes colony shows a high prevalence of SGH virus infection , though relatively few flies have frank SGH . Interestingly the prevalence of SGH is significantly higher in male than female flies [23] . Viral infection may lead to changes in the SG epithelium that favour trypanosome colonisation; alternatively , flies that succumb to viral infection and develop SGH may have lower levels of immunity in the SG . On the other hand , G . pallidipes may naturally manifest low levels of immune defence in the SG , explaining both its susceptibility to virus and trypanosomes . Similar arguments have been rehearsed for the interaction between Sodalis glossinidius and trypanosome infection [1] , [2] , [31] . Our experimental G . pallidipes come from a virus-infected colony and no virus-free flies were available to test . SGH virus has also been reported at low levels in wild G . pallidipes ( reviewed by [24] ) . Natural SG infection rates of G . pallidipes with T . brucei are typically very low ( <0 . 3% , [32] ) , and no SG infections were detected by dissection in recent surveys in Kenya [33] and Tanzania [34] . Since a strong MG immune response by itself is sufficient to block transmission of T . brucei , without any need for deployment of further immune defences in the foregut and SG , there is no inconsistency between our laboratory results and the observed refractoriness of G . pallidipes to trypanosome infection in the field . However , in laboratory G . pallidipes , the decreased ability to block SG colonisation makes G . pallidipes a very useful experimental fly for transmission of T . brucei . Tsetse flies were kept at 25°C and 70% relative humidity and fed on sterile defibrinated horse blood via a silicone membrane . Flies were given the infected bloodmeal for their first feed 24–48 hours post-eclosion , which consisted of cryopreserved bloodstream form trypanosomes of T . b . brucei J10 ( MCRO/ZM/74/J10 [clone 1] ) in defibrinated horse blood ( approximately 106 cells/ml ) . Infective bloodmeals were supplemented if necessary with final concentrations of 60 mM N-acetyl-glucosamine ( NAG ) [8] or 10 mM L-glutathione ( GSH ) [9] to increase infection rates . Results were usually combined from two replicate experiments to increase sample size , except for those shown in Tables 1 and 2 which were each derived from a single batch of flies . Spit samples were obtained from flies as described [13]; male and female flies were sampled on days 8–18 and 7–28 in two replicate experiments . Slides were fixed with 2% paraformaldehyde ( PFA ) , washed three times with phosphate buffered saline ( PBS ) and then incubated with 1∶100× Hoechst 33258 DNA stain for 15 minutes . The slides were mounted using FluorSave reagent and viewed by fluorescence imaging to record the life cycle stage of the parasites using a DMRB microscope ( Leica ) equipped with a Colour Coolview camera ( Photonic Science ) and ImagePro Plus software ( Media Cybernetics ) . Digital images of life cycle stages were quantified using Image J ( http://rsb . info . nih . gov/ij/ ) . Morphology and relative positions of the nucleus and kinetoplast were used to identify developmental stages [18] , [19] , [20] . Cells were assigned to the following developmental stages: long proventricular trypomastigote , asymmetrically dividing cell , short or long epimastigote , metacyclic . Flies were killed by removing the head . Salivary glands were placed into a drop of PBS . Salivary gland hypertrophy ( SGH ) was recorded if the glands were grossly swollen; such glands also appear white rather than transparent . Whole tsetse alimentary tracts , from the proventriculus to the rectum , were placed into a separate drop of PBS . Infection of the proventriculus was examined in flies dissected 10–14 days after the infected feed; the proventriculus was cut from the MG immediately upon dissection and placed in a separate drop of PBS . Organs were viewed as wet mounts in PBS under bright field illumination ( ×100 magnification ) and the presence of trypanosomes recorded . The chi-squared test ( Fisher's exact ) was used for analysis of categorical data using http://www . graphpad . com/quickcalcs/contingency1 . cfm . ANOVA was used for comparison of trypanosome cell types in spit samples from male and female flies . Numbers of trypanosomes were square-root transformed prior to analysis to normalise variances . The rate at which flies became positive for trypanosomes in spit samples was analysed by Kaplan Meier survival followed by Breslow ( generalized Wilcoxon ) testing . ANOVA and Kaplan-Meier data were processed using the statistical package SPSS version 18 . 0 .
In tropical Africa human and livestock diseases caused by parasitic trypanosomes are transmitted by bloodsucking tsetse flies . In the fly , trypanosomes undergo a complex cycle of proliferation and development during their remarkable journey from the midgut to the salivary glands . At every step of the way , the flies mount robust immune defences against trypanosome infection and consequently most flies fail to develop a transmissible infection . Previous work has shown a sex difference in the numbers of salivary gland infections with Trypanosoma brucei: male flies are more susceptible to salivary gland infection than females . Here we explored possible reasons for this . Infections developed in the same way in both male and female flies until the final stage of salivary gland invasion and colonisation . We conclude that the salivary gland environment in the female fly is much more inhospitable for trypanosomes , perhaps because of a greater immune response . Comparison of two different tsetse species showed very different levels of trypanosome resistance in the midgut and salivary glands .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "medicine", "infectious", "diseases", "veterinary", "diseases", "vector", "biology", "neglected", "tropical", "diseases", "protozoology", "biology", "microbiology", "parasitic", "diseases", "veterinary", "science" ]
2012
The Influence of Sex and Fly Species on the Development of Trypanosomes in Tsetse Flies
The ecology and distribution of B . anthracis in Australia is not well understood , despite the continued occurrence of anthrax outbreaks in the eastern states of the country . Efforts to estimate the spatial extent of the risk of disease have been limited to a qualitative definition of an anthrax belt extending from southeast Queensland through the centre of New South Wales and into northern Victoria . This definition of the anthrax belt does not consider the role of environmental conditions in the distribution of B . anthracis . Here , we used the genetic algorithm for rule-set prediction model system ( GARP ) , historical anthrax outbreaks and environmental data to model the ecological niche of B . anthracis and predict its potential geographic distribution in Australia . Our models reveal the niche of B . anthracis in Australia is characterized by a narrow range of ecological conditions concentrated in two disjunct corridors . The most dominant corridor , used to redefine a new anthrax belt , parallels the Eastern Highlands and runs from north Victoria to central east Queensland through the centre of New South Wales . This study has redefined the anthrax belt in eastern Australia and provides insights about the ecological factors that limit the distribution of B . anthracis at the continental scale for Australia . The geographic distributions identified can help inform anthrax surveillance strategies by public and veterinary health agencies . Anthrax is a zoonotic disease caused by Bacillus anthracis , an aerobic , gram-positive spore-forming bacterium . Bacillus anthracis primarily affects herbivores; though most warmed-blooded mammals may be susceptible [1] , including humans . Anthrax is an ancient disease that has caused losses of livestock and wildlife populations prior to and throughout the 20th century and remains enzootic with seasonal variations in many parts of the world [2 , 3] . Transmission remains poorly understood , but ingestion of spores is the dominant hypothesis for herbivores [4] . Grazing mammals ( e . g . cattle , sheep , zebras ) can be infected by ingesting spores present in contaminated soils , while browsers ( e . g . deer ) may also ingest the pathogen with contaminated foliage [5 , 6] . Biting flies may be involved in transmission on some landscapes [7 , 8] and inhalation cannot be ruled out [9]; each mechanism requires further study . In each case , transmission is indirect and occurs where a susceptible host interacts with an environment that supports pathogen persistence . These environments can be characterized and mapped to define areas at risk for anthrax [5 , 10] . The first recorded livestock anthrax in Australia dates to 1847 at Leppington , New South Wales where the disease slowly spread through cattle and sheep movements along stock routes [11] . In Victoria , anthrax was initially reported in the area around Warrnambool in the southwestern area of the state in 1886 . From there , the disease apparently spread throughout the western districts of the state to Melbourne and elsewhere via the transport of infected sheep [12] . Historical records of livestock anthrax from the early 1900s to the 1920s indicate that the disease was more recurrent in New South Wales , where 80 confirmed anthrax outbreaks were recorded during that period [13]; twice as many as reported in Victoria during the same period . The 1930s saw an increase in livestock anthrax in Australia , especially in New South Wales and Victoria . For instance , in New South Wales , a total of 147 outbreaks were officially recorded from 1930 to 1936 [13] , and about 200 during the period 1949–1962 with sheep most commonly infected , while an increase of incidence was observed in cattle in Victoria [12] . Additional outbreaks in Victoria in 1968 caused cattle and sheep deaths on 27 farms in the Yarrawonga/Shepparton area [14] . There is little published literature on anthrax in Australia during the period 1970–1990; though there were confirmed reports throughout NSW and Victoria . Summarizing the available Australian literature , the continent experienced overall reductions in the size and spatial distribution of livestock anthrax outbreaks across the latter half of the 20th century . Similar patterns were documented in the United States [15] and the Ukraine [16] . The majority of anthrax outbreaks in recent decades have taken place across the Australian anthrax belt , which predominantly runs through the center of New South Wales [17] . The geography of the anthrax belt was originally described by Henry [13] and later roughly delineated by Allan [18] and Durrheim et al . [17] to map the extent of the endemic zone in Australia ( Fig 1 ) . This description of the anthrax belt is based solely on locations of disease incidents . The belt lies between the tablelands and the western plains in New South Wales , and reaches from northern Victoria at the southern extent , northward through New South Wales to the southern border of Queensland . Occasionally , outbreaks have occurred outside of the historically defined anthrax belt . For example , an outbreak occurred in 2007–2008 in the Hunter Valley , a valley located ~350 km east of the belt . In that outbreak , 11 dairy farms in the Hunter Valley experienced unusual anthrax outbreaks in the summer of 2007 with clinical cases mainly observed in cattle . The last recorded livestock anthrax cases in the Hunter Valley prior to the 2007–2008 outbreaks occurred in 1939 [17] . An unprecedented livestock epizootic also occurred in the Goulburn Valley in the north of Victoria in the summer of 1997 , affecting 83 dairy farms in the Stanhope/Tatura area . This was the largest anthrax epizootic reported in Australia since official reports of livestock anthrax began in 1914 in Victoria [19] . The Goulburn Valley in northern Victoria borders southernmost New South Wales and intersects the southern extension of the anthrax belt into Victoria [17] . Although the number of reported anthrax outbreaks within the anthrax belt has decreased in recent decades , outbreaks continue within and beyond its currently defined boundaries . Therefore , there is a need for ecological investigations of the distribution of B . anthracis and the identification of all potential risk zones in Australia to better inform anthrax surveillance . Many environmental factors including climate and soil are known to prolong the survival of anthrax spores in the environment . Van Ness [20] postulated that suitable soils with high soil moisture , alkaline pH , and organic nutrients referred to as “incubator areas” may be conducive to the germination , vegetative growth and sporulation of B . anthracis independently of a mammal host . Recent experimental spore germination using a grass-soil model system also supported the possibility that this dynamic state occurs in the soil [21] . However , the study of Dragon et al . [22] demonstrated that in natural conditions , growth of B . anthracis outside a host leads to a rapid loss of virulence , and that vegetative forms cannot compete with other bacteria species in the soil . This latter study supports the “persistent spore theory” according to which , spores persist in the soil for very long periods of time until they come into contact with a susceptible host causing disease [23 , 24] . Irrespective of which of these theories is correct , both recognize that soil is the natural reservoir of anthrax spores , which therefore implies that a greater understanding of the ecological conditions that allow spores to “persist” or “incubate” in the soil environment is essential for the prediction of the potential geographic distribution of B . anthracis . Ecological niche modeling is one approach to estimate the potential geographic distribution of a species and has been applied to map B . anthracis habitat suitability for several landscapes [10 , 25–29] . These approaches relate environmental covariates with historic occurrence data on the species ( e . g . outbreak locations ) using pattern matching genetic algorithms or statistical approaches [30] . Occurrence data are generally obtained from a subset of the landscape accessible by the species [31] and related to larger landscapes described by environmental covariates [5] . Broadly , ecological niche modeling techniques can be divided into presence-absence and presence-only approaches . In the former , the user provides both occurrence locations and locations where the species was not detected . In the latter , the modeling algorithm will exhaustively sub-sample pseudo-absence points from a user-defined amount of the sampling area or background , which has been recommended when spatial information on species’ absence is unavailable [32] or occurrence points derived from idiosyncratic data sources , as is common with historical disease data . Many ecological niche modeling studies have used the presence-only approach to successfully predict the potential geographic limits of organisms in disease ecology [25 , 33–35] , biogeography [36] and conservation biology [37] across spatial scales . Here we used a presence-only modeling approach to predict the geographic distribution of B . anthracis across Australia . A geographic information system ( GIS ) database of historical occurrence of livestock anthrax was constructed using anthrax locations heads-up digitized from Seddon and Albiston [12] and presence data provided by the Department of Economic Development , Jobs , Transport and Resources ( DEDJTR ) in Victoria , the Department of Primary Industries ( DPI ) in New South Wales and the Department of Agriculture , Fisheries and Forestry ( DAFF ) in Queensland , Australia ( Fig 1 ) . To ensure that all occurrence data were anthrax related deaths , only confirmed outbreaks ( carcasses tested positive for B . anthracis or clinical confirmation ) , in the states of Victoria , New South Wales , and Queensland were retained for further analyses ( Fig 2 ) . An outbreak was defined as any location ( infected farm or property ) with one or more anthrax cases . Ideally , to predict the geographic distribution of B . anthracis , one would use occurrence data obtained from positive soil samples indicating the presence of the pathogen in the environment . Instead , outbreak locations were used as a proxy for B . anthracis occurrence data because anthrax-related death occurs after a relative short period of time following infection . For this study , we assumed that there were not great distances between infection source and carcasses . Additionally , in this study , B . anthracis infections and deaths occur on the same farms , and outbreak locations were represented by the geographic coordinates of infected farms . For each outbreak , the latitude and longitude were recorded along with additional attributes including date ( day , month , and year ) , and total number of cases per animal species . Table 1 summarizes the spatial resolution and data collection methods for outbreaks for each state . Duplicate coordinates were removed from the database for ecological niche modeling experiments . We then filtered the database to include one outbreak location per 8x8 km pixel , the resolution of environmental data used for modeling ( hereafter referred to as the spatially unique presence points ) [26] . The ecological niche modeling algorithm , the genetic algorithm for rule-set prediction ( GARP ) utilizes a single point per pixel to indicate the presence of B . anthracis . Using more than one point per grid cell for model development is equivalent of using the same data for both the training and testing of a GARP model , which can lead to inflation of accuracy metrics [26] . We used three groups of environmental coverages including bioclimatic ( temperature and precipitation ) , edaphic ( vegetation and soil properties ) , and topographic ( altitude ) factors known to influence the persistence of B . anthracis in the environment . Bioclimatic variables were downloaded at 30 arc-seconds ( approximately 1x1 km spatial resolution ) from the WorldClim website ( http://worldclim . org ) and are described in detail elsewhere [38] . Vegetation indices ( 8x8 km spatial resolution ) were obtained from the Trypanosomiasis and Land Use in Africa ( TALA ) research group [39] . Soils data were extracted from the harmonized world soil database v1 . 2 ( HWSD ) available at the International Institute for Applied System Analysis ( IIASA ) ( http://www . iiasa . ac . at ) [40] . The HWSD data were available at 1x1km spatial resolution . The variables used for the ecological niche modeling are presented in Table 2 . Correlated environmental variables were eliminated using a Pearson correlation test to retain the variables presented in Table 2 , which were then clipped to the boundary of Australia . Since the environmental data were at different spatial resolutions ( 1x1 km and 8x8 km ) , all data layers were resampled to the coarsest cell size ( 8x8 km ) using the GARP Datasets extension in ArcView 3 . 3 ( Environmental Systems Research institute , Redlands , CA ) . In this study , we employed the genetic algorithm for rule-set prediction ( GARP ) and experiments were performed in DesktopGARP version 1 . 1 . 3 ( DG ) . GARP is an expert-system , machine-learning algorithm that has been tested and widely used for species’ range prediction [32 , 41–43] . Briefly , GARP develops a set of if/then logic string rules to relate observed occurrence data to environmental variables ( bioclimatic , edaphic/substrate and topographic ) [10] . Predicted presence or absence of a species within an ecological space are defined by one of four types of conditional rules including atomic , logit , and range or negated range rules [43] . Atomic rules use specific values or categories for each environmental variable ( e . g . IF temperature = [35°C] AND precipitation = [325 mm] AND pH = [8 . 5] AND ndvi = [0 . 5] THEN species = PRESENCE/ABSENCE ) . Logit rules are fitted logistic regression functions ( e . g . IF temperature*0 . 0078—precipitation*2 . 5 + pH*0 . 0039 + ndvi*0 . 0039 THEN species = PRESENCE ) . Upper and lower bounds for each environmental variable are specified in range rules ( e . g . IF temperature = [14 . 6–19 . 5°C] AND precipitation = [348 . 25–757 . 51 mm] AND pH = [7 . 5–8] AND ndvi = [0 . 01–0 . 25] THEN species = PRESENCE ) . Negated range rules define conditions outside of variable ranges ( e . g . IF NOT temperature = [15 . 5–28°C] AND precipitation = [143–1693 mm] AND pH = [6 . 5–8] AND ndvi = [0 . 25–0 . 45] THEN species = ABSENCE ) . The rules are developed through evolutionary refinement by testing and selecting rules on random draws of presence points from known occurrences data and pseudo-absences localities generated internally from the wider study area . A one-tailed significance χ2 test is then calculated in order to evaluate the quality of a rule at predicting the ecological distribution ( presence or absence ) of the species [43] . The stochastic process of deriving and evolving rules results in random walks through variable space resulting in multiple models . Each model is a set of 50 presence/absence rules that are projected onto the geographic landscape to estimate the potential geographic distribution of the species as a binary output ( absence = 0 , presence = 1 ) . Spatially unique presence points ( N = 96 anthrax outbreak locations ) were partitioned into training and independent test datasets for model building and evaluation . The geospatial modeling environment ( GME , www . spatialecology . com ) was used to randomly select 75% of the occurrence data points ( n = 72 ) for models building and 25% of the points ( n = 24 ) for calculating accuracy metrics [44–46] . To evaluate the effects of randomly sub-setting presence points , the selection process was repeated 10 times to develop 10 different GARP experiments . For each experiment , we ran up to 200 models with a maximum of 1 , 000 iterations and a convergence limit of 0 . 01 . We allowed GARP to internally partition training data into a 75%/25% for model development and rule selection . We used the best subset procedure to select the best 20 models under a 10% hard omission threshold and a 50% commission threshold . Those 10 best subset models from each GARP experiment were then imported in ArcMap and summated using the raster calculator tool in the Spatial Analyst extension . The resulting composite raster layer , with pixel values ranging from 0 to 10 , is a surface depicting the potential geographic distribution of B . anthracis in Australia . The higher the pixel values , the greater the potential that the environmental conditions will support pathogen persistence [25] . Model agreements from 0 to 5 were reclassified as not suitable and those greater or equal to 6 were considered most suitable to support B . anthracis persistence [26] . Model accuracy for each GARP experiment was calculated with the 25% independent testing data withheld from model building . Three metrics were used to measure accuracy: the area under curve ( AUC ) in a receiver operating characteristic ( ROC ) analysis , omission ( a measure of false negatives ) and commission ( the proportion of the landscape falsely predicted as present ) [44 , 47] . The AUC was used to evaluate the overall performance of each composite predictive model ( 10-best subset model ) . An AUC of 0 . 5 indicates a random model whereas an AUC of 1 suggests a perfect model [42 , 47] . Total omission was calculated as the percent of independent test points predicted absent by the composite predictive model and the average omission as the average omission across each of the 10 best models . Total and average commissions are the percent of pixels predicted as presence by the composite predictive model and the average of this value for the 10 best models , respectively [48] . Overall predicted area and the accuracy metrics were used to rank the 10 GARP composite predictive models . The best composite predictive model with the higher AUC value and lower omission error was retained to describe the potential geographic distribution of B . anthracis for Australia ( S1 Fig ) and to perform the rule-set analysis . Rule types from each of the 10 best models in the highest ranked experiment were extracted using a python script ( K . M . McNyset , US NOAA ) to illustrate the relative number of each rule type [35] . From each rule-set , dominant rules that cumulatively predicted over 90% of the landscape were also identified in order to extract maximum and minimum values of the environmental variables of each presence rule type . The median of minimum and maximum values for each covariate in a given rule were calculated in Microsoft Excel 2010 and plotted as bar graphs to illustrate the ranges of each covariate [49] . Each GARP experiment reached convergence of accuracy ( 0 . 01 ) prior to the maximum 1000 iterations . The accuracy metrics of all ten GARP experiments are ranked and summarized in S1 Table . Metrics indicated all ten experiments were accurate and predicted highly similar geographic distributions . The potential geographic distributions of B . anthracis predicted by the 10 GARP experiments are illustrated in S1 Fig . Experiment number 5 had the highest AUC score and lowest omission errors; its AUC score was 0 . 966 and significantly different from a line of no information ( p<0 . 01 ) . And the total and average omission errors were 0 . 00% and 0 . 83% respectively , meaning that all independent testing data were correctly predicted by each of the 10 models in the best subset . The total and average commission for experiment number 5 were 6 . 24% and 12 . 15% of the landscape , respectively ( Table 3 ) . Broadly , experiment number 5 predicted areas that stretch from north Victoria to northeast Queensland and running parallel with the eastern coastal region of Australia ( Fig 3 ) . The predicted areas also expand from northwest Victoria into small areas in the south of South Australia . In the southern part of Western Australia , the predicted geographic space of B . anthracis spans an area from the south to the southwest of the state . The interior of the country and the state of Tasmania were not predicted to be suitable for B . anthracis persistence ( based on the conservative criteria of 6 or more models in a best subset ) . S2 Table summarizes the rule types , number and proportion of each of the 10 best subset models from GARP experiment 5 . Range rules represented 97 . 8% of the rules in rule-set , whereas negated rules accounted for only 1 . 8% . There were only 2 logit rules kept in experiment 5 . There were no atomic rules . Fig 4 illustrates narrow median range values for the following environmental variables: soil pH , calcium sulfate , organic content , and annual precipitation . This study aimed to improve our understanding of the landscape ecology of B . anthracis and to predict the geographic distribution of the pathogen across Australia . We revised the geographic extent of the historical anthrax belt [17] that was defined by reported outbreaks and did not explicitly consider ecological conditions . Here we modeled the geographic distribution of B . anthracis based on environmental covariates known to be correlated with pathogen persistence enabling a quantitative redefinition of the anthrax belt . The distribution of B . anthracis has long been associated with environmental factors including soil and climatic parameters [20 , 22 , 50] . Incorporating these covariates into an ecological niche modeling framework provides a more accurate estimation of the geographic distribution of the pathogen , and therefore risk of anthrax , for Australia . The predicted areas of B . anthracis are distinctly separated into two anthrax zones: the southeast-northeast and southwest corridors ( Fig 3 ) . The southeast-northeast corridor , hereafter referred to as the ‘redefined anthrax belt’ , parallel the Eastern Highlands , stretching from north Victoria to central eastern Queensland through New South Wales where it traverses the western region of the Hunter Valley . The redefined anthrax belt extends far beyond Durrheim et al . [17] and captures many of the historical anthrax locations ( Figs 5 and S2 ) . In Victoria , the models also predicted the northern area of Goulburn Valley . This prediction includes South Australia along the Spencer Gulf on the southern coast of Australia in an area disjunct from the redefined anthrax belt . In a second disjunct area in Western Australia , the models predict part of the Nullarbor Plain on the Great Australian Bight coast , and the Darling Range in the Perth area . The rule-set analysis indicated that the predicted ecological niche of B . anthracis is defined by a narrow range of high soil pH , low organic content , calcium sulfate , and annual precipitation ( Fig 4 ) . Across the best subset , a single rule per model captured nearly all of the predicted presence ( S3 Fig ) . This is in contrast to the models developed for the United States , where presence rules captured presence with rules delineating eastern or western conditions [15] or presence rules in Kazakhstan dominated by northern and southern rules [49] . Historically , livestock anthrax was widespread in Australia , in particular Victoria and New South Wales . A comparison of past ( 1914–1963 and 1968–1995; Table 4 ) and recent epizootics ( 1996–2013; included in the model building process ) confirmed a decrease in the number and spatial extent of anthrax outbreaks in the affected states , New South Wales and Victoria . This decrease is most likely due to the implementation of improved surveillance measures , livestock vaccination , the destruction of infected carcasses by burning , site decontamination and quarantine of affected livestock and properties [13] . A similar pattern of decrease of anthrax incidence was observed in the United States [15] and Ukraine [16] . In the United States , the use of an efficacious vaccine , along with better anthrax disease management strategies also resulted in a decrease in number of reported endemic counties from the 1950s onwards . In Ukraine , mass vaccination campaigns and effective control measures ( burning of contaminated carcasses and sites decontamination ) resulted in a reduction of anthrax foci from the early 1970s to the post-soviet period ( 1991 to the present day ) [16] . It has been reported that during the mid-19th century , intensification of farming activities in Australia was associated with the use of unsterilized bone meal imported from India as a mineral supplement fed to livestock and as a fertilizer which led to the introduction of the pathogen [12] . The pathogen likely spread within Australia through the movement of diseased livestock along the southeast to northeast coastal corridor , and the contamination of stock routes with B . anthracis spores [12] . Contemporary livestock movement trajectories produced by the AusVet Animal Health Services [51] and East and Foreman [52] agree with historical livestock movements [12] . These movement trajectories perfectly intersect with areas of high model agreement . The predicted geographic distribution of B . anthracis defines some suitable areas with no historical outbreak records , which may be due to over-prediction of the models . Nevertheless , it is worthwhile to note that over-predicting the geographic distribution of a species does not necessarily infer prediction error . The potentially over-predicted geographical distribution areas may represent an accurate illustration of the spatial extent of B . anthracis [53] , despite the lack of presence records that could be used for testing the accuracy of our model in those areas . For example , using GARP , Blackburn et al . [25] successfully predicted suitable distributional areas for B . anthracis in the northwest corner of Montana , US , that had experienced anthrax outbreaks in 2005 although specific localities were unavailable for modeling . In South Australia , it has been reported that twenty three cattle died from anthrax in 1906 on a government farm at Islington [12] , and six years later the disease also occurred in a metropolitan piggery at Unley after feeding pigs the carcasses of two horses , that had previously died from anthrax [12] . The source of infection at Islington was not mentioned , and the reported cases at Unley were not associated with direct contact to soil spores . However , these two areas overlap with the high agreement areas of our GARP models . The models did not predict two outbreak locations that were withheld from model building , one in Western Australia and the other in Queensland . The anthrax cases in Western Australia were recorded in 1994 on three cattle properties in a localized area north of Walpole , where 29 cattle died from unknown sources from January to April 1994 [54] . In 1993 , one cow died from anthrax on a grazing property near Rockhampton in Queensland , apparently from ingestion of contaminated feed [55] . In each case , the affected properties were outside of the predicted areas . Since anthrax is primarily a soil-borne disease , we hypothesize that these isolated cases , as well as the early outbreaks in the south coast areas of Victoria outside the predicted geographic distribution areas ( S2 Fig ) , are likely attributable to causes other than ingestion of spores at grazing sites . Anthrax was first recognized in Victoria in 1879 at Warrnambool followed by other areas in the south west of the state . The disease was later identified in southern and central Victoria following shipment of diseased sheep [12] . Seddon and Albiston [12] thought it is unlikely that the initial outbreak in the southwest of Victoria resulted from the spread of the disease from southern New South Wales , indicating that the introduction of the disease into this area came from other sources , followed by rapid spread over long distances to new areas by movement of stock by rail . The later distribution of the disease into the north of Victoria is considered to be most probably due to stock traveling over the border from NSW [12] . The distribution of anthrax throughout Victoria has changed over time with the majority of outbreaks post-1968 falling within the predicted zone and those prior to 1968 falling outside of this zone ( Table 4 ) . We hypothesize that the presence of disease incidents along the south coast of Victoria outside of the predicted geographic distribution prior to 1968 may represent constant reintroductions of the disease into these areas , given their proximity to ports and transport routes combined with possible short term survival and local spread . This study redefines the anthrax belt of Australia , which is presently defined by the location of anthrax cases , by integrating ecological niche modeling and GIS . This approach provides insights about the ecological factors that limit the distribution of B . anthracis at the continental scale for Australia . The geographic distributions presented here can help inform anthrax surveillance strategies by public and veterinary health agencies .
This study explores the spatial ecology of Bacillus anthracis , the causative agent of anthrax disease , in Australia . Globally , anthrax is a neglected zoonotic disease that primarily affect herbivores and incidentally humans and all warm-blooded animals . Here , we used historic anthrax outbreaks for the period 1996–2013 and environmental factors in an ecological niche modelling framework to quantitatively define the ecological niche of B . anthracis using a genetic algorithm . This was projected onto the continental landscape of Australia to predict the geographic distribution of the pathogen . The ecological niche of B . anthracis is characterized by a narrow range of ecological conditions , which are geographically concentrated in two disjunct corridors: a dominant corridor paralleling the Eastern Highlands runs from north Victoria to central east Queensland through the centre of New South Wales , while another corridor was predicted in the southwest of Western Australia . These findings provide an estimate of the potential geographic distribution of B . anthracis , and can help inform anthrax disease surveillance across Australia .
[ "Abstract", "Introduction", "Methods", "Results", "Discussion" ]
[ "livestock", "medicine", "and", "health", "sciences", "ecology", "and", "environmental", "sciences", "ecological", "niches", "pathology", "and", "laboratory", "medicine", "pathogens", "population", "dynamics", "bacillus", "microbiology", "geographical", "locations", "australia", "bacterial", "diseases", "farms", "population", "biology", "bacteria", "bacterial", "pathogens", "veterinary", "science", "infectious", "diseases", "anthrax", "veterinary", "diseases", "zoonoses", "medical", "microbiology", "microbial", "pathogens", "bacillus", "anthracis", "agriculture", "people", "and", "places", "ecology", "oceania", "biology", "and", "life", "sciences", "organisms", "geographic", "distribution" ]
2016
Redefining the Australian Anthrax Belt: Modeling the Ecological Niche and Predicting the Geographic Distribution of Bacillus anthracis
The IL-27R , WSX-1 , is required to limit IFN-γ production by effector CD4+ T cells in a number of different inflammatory conditions but the molecular basis of WSX-1-mediated regulation of Th1 responses in vivo during infection has not been investigated in detail . In this study we demonstrate that WSX-1 signalling suppresses the development of pathogenic , terminally differentiated ( KLRG-1+ ) Th1 cells during malaria infection and establishes a restrictive threshold to constrain the emergent Th1 response . Importantly , we show that WSX-1 regulates cell-intrinsic responsiveness to IL-12 and IL-2 , but the fate of the effector CD4+ T cell pool during malaria infection is controlled primarily through IL-12 dependent signals . Finally , we show that WSX-1 regulates Th1 cell terminal differentiation during malaria infection through IL-10 and Foxp3 independent mechanisms; the kinetics and magnitude of the Th1 response , and the degree of Th1 cell terminal differentiation , were comparable in WT , IL-10R1−/− and IL-10−/− mice and the numbers and phenotype of Foxp3+ cells were largely unaltered in WSX-1−/− mice during infection . As expected , depletion of Foxp3+ cells did not enhance Th1 cell polarisation or terminal differentiation during malaria infection . Our results significantly expand our understanding of how IL-27 regulates Th1 responses in vivo during inflammatory conditions and establishes WSX-1 as a critical and non-redundant regulator of the emergent Th1 effector response during malaria infection . IL-27 , a member of the IL-12 super-family , was initially described as a Th1 polarising cytokine due to its ability to increase the sensitivity of CD4+ T cells to IL-12 and to promote T-bet expression [Reviewed 1 , 2] . More recently , however , IL-27 has been shown to exert diverse suppressive effects on CD4+ T cells during pro-inflammatory conditions [reviewed 1 , 2] . IL-27 limits IFN- γ production by CD4+ T cells during various infections [3]–[7] , attenuates the development , but not necessarily maintenance , of Th17 responses by limiting retinoid-related orphan receptor ( ROR ) c expression [8]–[11] and stimulates IL-10 production by multiple effector CD4+ T cell populations [12]–[14] . All of these effects are mediated via Signal Transducers and Activators of Transcription ( STAT ) 1 and/or STAT 3 dependent pathways . Finally , IL-27 orchestrates the development of adaptive , IL-10-producing regulatory T cell subsets through induction of c-MAF , Aryl hydrocarbon Receptor ( AhR ) , inducible T-cell co-stimulator ( iCOS ) and IL-21 pathways [15] , [16] . IL-27 is thus a key cytokine that shapes the direction and strength of the T cell response . Despite reports describing the capacity of IL-27 to limit IFN-γ production by CD4+ T cells during inflammation [3]–[7] , very little work has been performed to understand the molecular basis of this regulatory pathway in vivo . IL-27 does not appear to regulate the initial priming or differentiation of Th1 cells during infection [3] , [7] , unless IL-4 is present , when IL-27 is required to limit Th2 differentiation and enable Th1 responses to develop [17] . Thus , IFN-γ production by CD4+ T cells is essentially unaltered in IL-27R deficient ( WSX-1−/− ) mice during the early stages of many infections and excessive IFN-γ production , in general , only occurs after day 10 [3] , [7] suggesting that WSX-1 regulates established effector CD4+ T cells rather than naive or newly primed cells . This temporal control may relate to disparate downstream STAT signalling of the IL-27 receptor in naive and effector CD4+ T cells [18] . It is possible that WSX-1 signalling could regulate the effector phase of the Th1 response by suppressing the proliferation and expansion of effector Th1 cells and/or by promoting apoptosis of effector Th1 cells , in both cases reducing the magnitude of the Th1 response . Alternatively , WSX-1 could subvert or destabilise the Th1 differentiation programme in maturing Th1 cells , converting Th1 cells into non-Th1 cells [19] . Whilst IL-27 has been shown to limit IL-2 production and therefore inhibit Th1 proliferation in vitro [20] , [21] , the role of IL-27 in promoting Th1 cell apoptosis or controlling Th1 cell programming has not been investigated . Moreover the specific pathways through which WSX-1 may modulate these processes in Th1 cells in vivo during infection remain poorly described To define the molecular pathways by which WSX-1 regulates emergent Th1 responses during inflammation , we have utilised the Plasmodium berghei ( P . berghei ) NK65 model of murine malaria . We have previously shown that WSX-1 signalling suppresses IFN-γ production by CD4+ T cells during this infection and that WSX-1 is essential for preventing CD4+ T cell dependent immunopathology [7] . We now demonstrate that Th1 priming and the early effector phase of the Th1 response are unaffected by lack of IL-27 signalling during P . berghei NK65 infection , but that in WSX-1−/− mice the Th1 response fails to reach a plateau after day 9 of infection leading to the formation of Killer cell Like Receptor Group 1 ( KLRG-1 ) -expressing , terminally differentiated , Th1 cells . Thus , IL-27 signalling constrains the developing Th1 immune response during malaria infection by establishing an upper threshold limit of T-box transcription factor TBX21 ( T-bet ) expression and suppressing the Th1 molecular programme . Finally we provide mechanistic evidence that IL-27 signalling controls the magnitude and pathogenic activity of the Th1 response by limiting IL-12 dependent signals and that this is independent of IL-10 and Foxp3 regulatory mechanisms . Our data thus provide important new information on how IL-27 regulates CD4+ T cell responses during infection . To investigate whether WSX-1 suppresses IFN-γ production by effector CD4+ T cells during malaria infection by down regulating classical Th1 responses , we compared expression of the prototypic Th1-associated transcription factor , T-bet , by splenic effector ( CD44+CD62Llow ) CD4+ T cells in P . berghei NK65-infected WT and WSX-1−/− mice . WT mice developed a slow , gradually ascending infection and succumbed with hyperparasitaemia between days 20—25 post-infection ( p . i . ) ( Figure S1 ) . In contrast , parasite levels were significantly lower in infected WSX-1−/− mice from day 7 of infection , but WSX-1−/− mice succumbed to infection on day 13/14 with severe and fatal immunopathology ( Figure S1 ) . Frequencies and numbers of splenic effector CD4+ T-bet+ T cells were equivalent in naïve WT and WSX-1−/− mice , showing that there were no intrinsic differences in T cell polarization in WSX-1−/− mice under homeostatic conditions ( Figure 1A–C ) . Percentages and absolute numbers of splenic effector CD4+ T-bet+ T cells increased at a similar rate in WT and WSX-1−/− mice until day 9 of infection ( Figure 1A–C ) . The effector CD4+T-bet+ T cell population plateaued , or even contracted slightly , in WT mice from day 9 of infection , whereas the effector CD4+T-bet+ T cell population continued to expand in WSX-1−/− mice with both frequencies and numbers of effector CD4+T-bet+ T cells being significantly higher in WSX-1−/− mice than in WT mice on days 11 and 14 ( Figure 1A–C ) . Similarly , significantly higher frequencies of malaria specific splenic effector CD4+ T cells produced IFN-γ in WSX-1−/− mice than in WT mice on day 14 of infection ( Figure S2A , B ) , corresponding with higher plasma levels of IFN-γ [7] . Thus , loss of WSX-1 signalling leads to dysregulated T-bet expression and exaggerated Th1 responses specifically after day 9 of infection . To assess whether aberrant IFN-γ production by CD4+ T cells in WSX-1−/− mice during infection [3]–[7] was simply due to WSX-1-mediated repression of T-bet expression within the effector population , or was also due to the suppression of T-bet+Th1 cell functionality on a cell per cell basis , we examined the capacity of splenic T-bet+ effector CD4+ T cells from WT and WSX-1−/− mice to produce IFN-γ and TNF following in vitro Phorbol 12-Myrisate 13-Acetate ( PMA ) /ionomycin restimulation . Lack of WSX-1 did not affect the proportion of Th1 cells that were IFN-γ+ , TNF+ or both IFN-γ+TNF+ on days 0 , 7 or 9 of infection ( Figure 1D , E and results not shown ) ; however , significantly higher frequencies of T-bet+Th1 cells derived from WSX-1−/− mice co-produced IFN-γ and TNF on day 14 of infection ( Figure 1D , E ) compared with cells from WT mice . Moreover , T-bet+ Th1 cells from WSX-1−/− mice produced significantly more IFN-γ on a per cell basis ( as measured by mean fluorescence intensity ( MFI ) of IFN-γ expression ) on days 9 , 11 and 14 , and significantly more TNF on day 14 of infection ( Figure 1D , G ) . Similarly , T-bet+ Th1 cells from infected WSX-1−/− ( D14 p . i . ) mice produced significantly more IFN-γ on a per cell basis when stimulated with malaria antigen compared with cells from WT mice ( Figure S2C , D ) . Thus , from day 9 of infection onwards , WSX-1 not only restricts the magnitude of the Th1 population ( by limiting T-bet expression ) , but also constrains the quality and effector functionality of malaria-specific T-bet+ Th1 cells on a cell-per-cell basis . Our results show that WSX-1 signalling does not restrict the Th1 response during malaria infection by suppressing cellular proliferation or promoting apoptosis ( Figures S3 , S4 ) . We therefore hypothesised that the temporal dysregulation in the magnitude ( and quality ) of the Th1 response in malaria-infected WSX-1−/− mice was a direct consequence of the reinforcement of Th1 molecular programming in WSX-1−/− mice , potentiating T-bet expression and terminal differentiation of effector CD4+T-bet+ T cells . To address this hypothesis , we determined the maturation status of Th1 cells during the course of malaria infection in WT and WSX-1−/− mice by measuring expression of the terminal differentiation marker , KLRG-1 . T cell terminal differentiation occurs under strong and continuous polarising signals [22]–[24] and , although short lived , terminally differentiated cells are likely to be more stable than incompletely polarised cells [19] , [25] . Very few effector CD4+ T-bet+ T cells expressed KLRG-1 in either WT or WSX-1−/− mice on days 0 , 7 and 9 of infection ( Figure 2A–C ) . Similarly , the vast majority of effector CD4+ T-bet+ cells from WT mice failed to express KLRG-1 on days 11 or 14 infection ( Figure 2A–C ) . In contrast , in WSX-1−/− mice the frequencies , and correspondingly the total numbers , of effector CD4+ T-bet+ T cells expressing KLRG-1 rapidly increased between day 9 and day 11 of infection , such that more than 50% of all splenic effector CD4+ T-bet+ cells expressed KLRG-1 on day 14 of infection ( Figure 2A–C ) . Thus , abrogation of WSX-1 signalling led to the maturation and terminal differentiation of a large proportion of the Th1 cell population during malaria infection concomitant with the increase in frequencies and total numbers of splenic Th1 cells after day 9 of infection ( Figure 1A–C ) . Intriguingly , KLRG-1 expression was almost entirely restricted to the effector CD4+ T-bet+ population and very few T-bet−effector CD4+ T cells expressed KLRG-1 in either WT or WSX-1−/− mice on day 14 of infection ( Figure 2D ) . KLRG-1 expressing Th1 cells in infected WSX-1−/− mice appeared highly proliferative but were not more potent sources of IFN-γ or TNF than the KLRG-1− Th1 cells on any examined day following PMA/ionomycin stimulation ( Figure S5 ) , and produced only slightly more IFN-γ on day 14 of infection following malaria-antigen stimulation ( results not shown ) , suggesting that they may be atypical terminally differentiated cells . To identify the molecular pathways through which WSX-1 represses Th1 cell terminal differentiation and thereby restricts the magnitude of the Th1 response during infection , we performed a phenotypic analysis of the splenic effector CD4+ T-bet+ T cells in WT and WSX-1−/− mice immediately prior to ( day 9 ) and following ( day 14 ) dysregulation of the Th1 response in WSX-1−/− mice . We observed no differences in expression ( MFI ) in any of the examined molecules by effector CD4+T-bet+ T cells derived from naïve WT and WSX-1−/− mice , demonstrating that there were no intrinsic differences in the regulation of effector CD4+ T-bet+ T cells in naïve WSX-1−/− mice ( Figure 3 ) . Similarly , phenotypes of effector CD4+ T-bet+ T cells from WT and WSX-1−/− mice were similar on day 9 of infection , with the notable exception of CD25 ( IL-2Rα ) , IL-18R and CD226 which were all expressed at significantly higher levels on cells from WSX-1−/− mice , and B and T lymphocyte attenuator ( BTLA ) , which was expressed at lower levels on cells from WSX-1−/− mice ( Figure 3A–D ) . In contrast , on day 14 of infection , CD25 , IL-12Rβ1 , IFN-γR , IL-18R , IL-15R , cytotoxic T lymphocyte antigen-4 ( CTLA-4 ) , Lymphocyte activation gene-3 ( LAG-3 ) , T cell immunoglobulin and musin domain containing protein-3 ( Tim-3 ) and CD226 , were all expressed at higher levels by effector CD4+ T-bet+ T cells derived from WSX-1−/− mice compared to cells from WT mice , whereas Programmed cell death protein 1 ( PD-1 ) and BTLA were both expressed at lower levels by cells from WSX-1−/− mice ( Figure 3A–D ) . CD28 , iCOS , 4-1BB and CD27 were expressed at comparable levels on effector CD4+ T-bet+ T cells from WT and WSX-1−/− mice ( results not shown ) . CD25 , IL-12Rβ1 , IL-15R , IL-21R , LAG-3 , TIM-3 and CD226 were all expressed at higher levels by Th1-KLRG-1+ T cells than by Th1-KLRG-1− T cells from WSX-1−/− mice , but the differences in expression were less than the differences observed between Th1 cells from infected WT and WSX-1−/− mice ( Figure S6 ) . Thus , dysregulation of the Th1 response in WSX-1−/− mice during malaria infection is associated with temporal and cell-intrinsic changes in multiple stimulatory and inhibitory pathways that could independently or synergistically affect Th1 cell maturation and/or function . CD25 and IL-12Rβ1 were significantly upregulated on splenic Th1 cells from WSX-1−/− mice compared with cells from WT mice on Day 14 . IL-12 is a well-characterised Th1-promoting signal and IL-2 is a T cell growth factor , both of which have also been shown to promote the development of terminally differentiated CD8+ T cells [22]–[24] . Thus , we examined the functional relevance of upregulated IL-12R and IL-2R expression on effector CD4+ T-bet+ T cells in promoting Th1 terminal differentiation and hyperactivity in WSX-1−/− mice . We first assessed whether effector CD4+ T-bet+ T cells from WSX-1−/− mice were hyper-responsive to IL-2 and IL-12 . Unstimulated ( ex vivo ) Th1 cells from WT and WSX-1−/− mice on day 14 of infection displayed equivalent levels of pSTAT4 and pSTAT5 expression ( Figure 4A , B ) . In contrast , effector CD4+ T-bet+ T cells from WSX-1−/− mice on days 9 and 14 of infection were hyperresponsive to both rIL-12p70 and rIL-2 , and significantly upregulated pSTAT4 and pSTAT5 respectively following in vitro stimulation ( Figure 4A , B ) . In comparison , effector CD4+ T-bet+ T cells from infected WT mice did not significantly upregulate pSTAT4 or pSTAT5 following rIL-12 or rIL-2 activation ( Figure 4A , B ) . T-bet+ effector CD4+ T cells from WSX-1−/− mice preferentially responded to both IL-12 and IL-2 compared with T-bet− effector CD4+ T cells from WSX-1−/− mice , demonstrating that IL-2 and IL-12 hyperresponsiveness was restricted to the Th1 ( T-bet+ ) lineage of cells ( Fig . 4 C , D ) , but there was no differences in the responsiveness of Th1-KLRG-1+ and Th1-KLRG-1− cells from WSX-1−/− mice to either IL-2 or IL-12p70 ( Figure 4E , F ) . Nevertheless , IL-12Rβ1− and IL-2R− ( CD25− ) Th1 cells from WSX-1−/− mice ( day 14 of infection ) responded poorly to IL-12 and IL-2 activation , confirming the functional relevance of increased cytokine receptor expression by Th1 cells in WSX-1−/− mice ( results not shown ) . In line with these data , plasma IL-12p70 concentrations were significantly higher in WSX-1−/− mice than in WT mice on day 14 of infection ( Figure 4G ) . Multiple innate MHC-II+ cell populations produced higher amounts of IL-12 in infected WSX-1−/− mice ( day 13 of infection ) compared with corresponding cells from WT mice , indicating that WSX-1 signalling , directly or indirectly , broadly suppresses the innate compartment during infection; however , CD8+ DCs appear to be the most potent source of IL-12 in infected WSX-1−/− mice ( Figure S7A ) . Increased numbers of macrophages and dendritic cells were also observed in the spleens of infected WSX-1−/− mice ( D13 p . i ) than in infected WT mice ( Figure S7B , C ) . Surprisingly , however , plasma IL-2 concentrations did not differ between infected ( D14 ) WT and WSX-1−/− mice ( Figure 4G ) and CD4+ T cells from infected ( D14 p . i ) WSX-1−/− mice produced significantly less IL-2 than CD4+ cells derived from infected WT mice ( Figure 4H ) . We next determined whether IL-12 and/or IL-2 signals led to over-expansion and terminal differentiation of Th1 cells in WSX-1−/− mice during malaria infection . Administration of anti-IL-2 mAb to WSX-1−/− mice from day 7 of infection ( when Th1 responses are similar in WT and WSX-1−/− mice ) failed to restrict the Th1 response; frequencies and total numbers of effector CD4+ T-bet+ T cells ( Figure 5A–C ) , as well as frequencies and numbers of KLRG-1+ effector CD4+T-bet+ T cells ( Figure 5D–F ) , were similar in WSX-1−/− mice treated with anti-IL-2 and control ( untreated ) WSX-1−/− mice . In contrast , anti-IL-12p40 treatment from day 7 of infection ( beginning immediately prior to increase in IL-12 production in WSX-1−/− mice ) significantly reduced the frequencies and numbers of effector CD4+ T-bet+ T cells ( to WT levels ) and repressed the development of KLRG-1+ terminally differentiated cells ( Figure 5A–F ) . Anti-IL-12p40 treatment did not affect the frequencies or numbers of effector CD4+ T-bet+ T cells in WT mice ( results not shown ) . Clodronate liposome administration from day 7 of infection , which depleted both macrophage and dendritic cell populations , significantly suppressed IL-12p70 production and consequently also reduced Th1 cell terminal differentiation ( Figure S7D–I ) . Crucially , whilst anti-IL-2 treatment did not modulate parasite burdens ( results not shown ) , and consequently did not prevent development of fatal immunopathology , anti-IL-12p40 treatment negatively affected parasite control but significantly reduced the level of tissue-immunopathology ( Figure 5G , H ) . Thus , WSX-1 signalling establishes a restrictive threshold for the emergent Th1 response during infection , preventing pathogenic terminal differentiation of Th1 cells , by repressing IL-12p40-dependent signals . IL-27 promotes IL-10 production by various populations of T cells during inflammatory conditions [12]–[16] . As we , and others , have shown an important role for IL-10 in limiting immunopathology during malaria infection [7] , [14] , [26] , [27] , we determined whether elevated T-bet expression by effector CD4+ T cells and increased Th1 cell terminal differentiation in WSX-1−/− mice during infection was due to lack of IL-10 . Intriguingly , ablation of IL-10 production and IL-10R1 expression did not lead to a marked increase in the frequencies or total numbers of effector CD4+T-bet+ T cells during infection ( Figure 6A–C ) . Consistent with this , lack of IL-10 and IL-10R1 led to only a marginal increase in frequencies and total numbers of KLRG-1+ effector CD4+T-bet+ T cells and their numbers were significantly lower in IL-10−/− and IL-10R1−/− mice than in WSX-1−/− mice ( Figure 6D–F ) . Thus , these data strongly indicate that WSX-1 signalling controls pathogenic Th1 responses during malaria infection through IL-10 independent mechanisms . IL-27 can suppress the maintenance and functionality of natural Foxp3+ regulatory T cells ( Foxp3+ Treg ) [28]–[31] . However , it has also been suggested that Foxp3+ Treg numbers can collapse during highly pro-inflammatory events , due to conversion into Th1 cells and apoptosis , initiating a pro-inflammatory feedback loop leading to development of immune mediated pathology [32] . Although the role of Foxp3+ Treg during malaria is far from clear [26] , [33]–[35] , Foxp3+ Treg can , in other models , regulate Th1 cell homeostasis [36] . Thus , as the final part of this study , we determined whether Foxp3+ Treg numbers and/or phenotype were modulated in WSX-1−/− mice during malaria infection . The frequencies and absolute numbers of splenic CD4+ Foxp3+ T cells were largely comparable in WT and WSX-1−/− mice at all time points ( Figure 7A–C ) . Interestingly , the proportion of CD4+Foxp3+ T cells co-expressing T-bet increased in both WT and WSX-1−/− mice during the course of malaria infection ( Figure 7A , D ) , and significantly higher frequencies and numbers of CD4+Foxp3+T-bet+ T cells were observed in WSX-1−/− mice compared with WT mice on days 9 and 11 of infection , although cell numbers were low ( Figure 7D , E ) . Very few splenic CD4+Foxp3+ T cells expressed IFN-γ in naïve or malaria-infected WT or WSX-1−/− mice and there was only a transient difference in the frequencies and numbers of CD4+Foxp3+ IFN-γ+ cells in WT and WSX-1−/− mice on day 9 of infection ( Figure 7F–H ) . Moreover , there were no major differences in the frequencies or numbers of CD4+Foxp3+ T cells expressing CXCR3 ( Th1-adapted Treg [37] in either the spleen or livers of naive or infected WT and WSX-1−/− mice ( Figure 7I , J and results not shown ) . These data suggest that a small proportion of Foxp3+ Treg either polarise to a specialised Th1-regulatory phenotype [37] , or convert into non-regulatory effector cells [32] during malaria infection , and that WSX-1 may play a very minor and transient role in regulating this adaptation . Crucially , however , depletion of Foxp3+ regulatory cells throughout the course of malaria infection , using DEREG mice , did not significantly increase the level of Th1 cell differentiation or lead to development of KLRG-1+ Th1 cells ( Figure S8 ) . Thus , Foxp3+ T cells do not regulate the magnitude or terminal differentiation of the Th1 population during malaria infection . In this study we have defined the molecular mechanisms by which IL-27 restricts Th1 immune responses during infection . Whilst it is well established that WSX-1 signalling limits IFN-γ production by T cells during infection and inflammation [1] , [2] , our study is the first to identify that it does so specifically by preventing the generation of terminally differentiated KLRG-1+ Th1 cells . We have demonstrated that although WSX-1 signalling modulates the expression of multiple stimulatory and inhibitory receptors on Th1 cells during infection , including PD-1 and BTLA , individual neutralisation of IL-12p40 from day 7 of infection was sufficient to prevent aberrant T–bet expression , abrogate the development of terminally differentiated KLRG-1+ Th1 cells and attenuate T-cell dependent immunopathology in malaria infected WSX-1−/− mice . Thus , the dominant immunoregulatory role of IL-27 – signalling via WSX-1 - in preventing hyperactive Th1 responses in vivo during malaria infection appears to be the downregulation of IL-12-dependent pathways . We have shown that Th1 cells derived from malaria-infected WSX-1−/− mice are hyper responsive to IL-12p70 and that that IL-12p70 protein levels are significantly higher in WSX-1−/− mice than in WT mice at the later stages of infection , when the Th1 cell responses start to diverge . It has previously been shown that macrophages and dendritic cells derived from WSX-1−/− mice are hyper-responsive to TLR signalling and produce more IL-12p40 [5] , [38] than WT cells and that IL-27 reduces IL-12p40 production by macrophages in vitro [5] . Therefore , it is perhaps unsurprising that we found that macrophages and dendritic cells , in particular the CD8+ DC subset that is the dominant source of IL-12 in various other infections [39] , expressed higher levels of IL-12 in malaria infected WSX-1−/− mice than in infected WT mice . However , T cell intrinsic WSX-1 expression has also been shown to be required to limit T cell proliferation and IFN-γ production in vivo during infection [3] . Consequently , it is currently unclear whether the dysregulated IL-12 pathway in WSX-1−/− mice during infection , and the corresponding development of KLRG-1+ Th1 cells , is due to intrinsic loss of WSX-1 mediated regulation within the innate system , specifically by macrophages and dendritic cells , or whether it is a consequence of abrogated WSX-1 expression on CD4+ T cells , which subsequently leads to amplification of the innate immune response , initiating a positive inflammatory feedback loop . We are currently examining the relative importance of CD4+ T cell intrinsic and extrinsic WSX-1 signalling in limiting the IL-12 pathway , and hence Th1 cell differentiation , in vivo during infection . Th1 cell proliferation and apoptosis were relatively unaltered in WSX-1−/− mice during the course of malaria infection , suggesting that Th1 hyperactivity in WSX-1−/− mice during malaria infection was not due to differences in cellular expansion or survival . It has previously been shown that malaria infection promotes a biphasic effector T cell response in WT mice , with Th1 responses established early in infection being replaced by Th2-dominant responses later in infection [40] . As IL-4 mRNA levels are significantly lower in CD4+ T cells from WSX-1−/− mice than from WT mice on day 13 of infection ( 7 ) our results suggest that the transition from Th1 to Th2 based immunity does not occur in WSX-1−/− mice during malaria infection . Thus , our results indicate that WSX-1 signalling limits Th1 cell terminal differentiation and establishes an upper threshold of T–bet expression within the effector CD4+ T cell population by inducing instability within the Th1 molecular programme , causing incompletely polarised Th1 cells – which exhibit significantly higher functional flexibility than repeatedly restimulated Th1 cells [25] - to lose T–bet expression and convert into non-Th1 cell populations , such as Th2 cells . Whilst Th1 cells are believed to be more stable than Th17 and iTreg cells [19] , the signals that reciprocally enforce and oppose the fidelity of the Th1 molecular programme during infection or inflammation in vivo are poorly defined [19] . Our data indicate that IL-27 may be one such cytokine that orchestrates Th1 cell conversion in vivo to reduce immune mediated pathology during infection . The molecular cues that govern the terminal differentiation of effector CD4+ T cells are less well characterised than those that control development of effector CD8+ T cells but our data suggest that there are some similarities – and some important differences – between the two processes . Strong and prolonged IL-12 , IL-15 and IL-2 ( CD25 dependent ) signalling induces the graded expression of T-bet and B lymphocyte-induced maturation protein 1 ( Blimp1 ) in CD8+ T cells , promoting the development of short-lived , terminally differentiated effector ( KLRG-1+ , CD127lo ) CD8+ T cells at the expense of long-lived memory populations , [22]–[24] , [41]–[44] . In contrast , our data suggest that IL-12 , but not IL-2 , is the key cytokine driving Th1 cell terminal differentiation during infection , presumably through STAT4 positive enforcement of T-bet expression . Whilst anti-IL-12p40 treatment also potentially abrogated IL-23 activity we do not believe IL-23 plays a major role in promoting Th1 cell terminal differentiation in malaria-infected WSX-1−/− mice . IL-23 is not overproduced in WSX-1−/− mice during malaria infection and Th17 responses are not amplified in malaria-infected WSX-1−/− mice [7] , indicating that IL-23 does not exert strong activity in infected WSX-1−/− mice . It is also interesting that loss of IL-27 immunoregulation specifically leads to Th1 cell terminal differentiation during malaria infection and very few non-Th1 cells express KLRG-1 . This suggests that there is as specific imbalance in signals that promote Th1 cell terminal differentiation in WSX-1−/− mice during malaria infection and that disparate cues , which are unaffected in infected WSX-1−/− mice , orchestrate terminal differentiation of other CD4+ T cell subsets . Indeed , IL-4 is expressed at lower levels in malaria infected WSX-1−/− mice than in WT mice [7] . In addition , it is also possible that during malaria infection direct IL-27R signalling specifically inhibits Th1 molecular programming . As IL-27 can induce IL-10 production by effector CD4+ T cell populations [7] , [12]–[16] , including during malaria infection [7] , [14] , we initially hypothesized that the hyperactive Th1 phenotype observed in WSX-1−/− mice would be recapitulated in IL-10−/− or IL-10R1−/− mice . Indeed , we and others have shown that IL-10 is required to limit morbidity and mortality during malaria infection [7] , [14] , [26] , [27] . Surprisingly , however , the Th1 response was quantitatively and qualitatively similar in IL-10R1−/− mice and WT mice during malaria infection . These data strongly suggest that WSX-1 does not regulate Th1 responses in vivo during infection specifically through IL-10-dependent mechanisms . Consistent with this , IL-27 has previously been shown to mediate IL-10-independent mechanisms [13] . Thus , under physiological conditions , IL-27 and IL-10 appear to have discrete immunoregulatory functions in vivo during malaria infection . We have also shown that the Foxp3+ regulatory T cell population is largely unaltered in WSX-1−/− mice during malaria infection; the frequency , absolute number and phenotype ( T-bet , CXCR3 and IFN-γ ) of Foxp3+ Tregs were essentially the same in infected WT and WSX-1−/− mice . Thus , although we cannot be entirely sure that the Foxp3 Tregs maintain their regulatory function during malaria infection in WSX-1−/− mice , there is no evidence that WSX-1 regulates the collapse of the Foxp3+ T cell population during malaria infection . Moreover , it does not appear that WSX-1 controls the functional adaptation of Foxp3+ Tregs to become Th1-Foxp3+ Treg ( CXCR3+Foxp3+ ) during malaria infection , as is observed during T . gondii infection [45] . Irrespective of the role of IL-27 in modifying the nature of the Foxp3+ regulatory cell compartment , we have shown that depletion of Foxp3+ regulatory T cells throughout the course of malaria infection does not lead to the expansion or terminal differentiation of Th1 cells . Thus , combined , our results strongly indicate that IL-27 controls Th1 responses during malaria infection through Foxp3+ regulatory T cell independent mechanisms . In summary , our study has significantly expanded our understanding of how IL-27/WSX-1 signalling regulates Th1 responses in vivo during infection . We have shown that WSX-1 signalling regulates the molecular programming of Th1 cells , inhibiting the formation of terminally differentiated KLRG-1+ Th1 cells , and thereby establishes an upper threshold limit of T-bet expression within the CD4+ effector T cell population . Importantly , IL-27 mediates its effects independently of IL-10 and Foxp3+ Tregs . Thus , our data highlight a critical and non-redundant role for IL-27/WSX-1 signalling in regulating the size and quality of the Th1 response during infection . Manipulation of the IL-27 pathway may therefore represent a therapeutic approach to limit T cell dependent immunopathology and/or enhance pathogen control during chronic inflammatory disorders . All animal work was approved following local ethical review by LSHTM and University of Manchester Animal Procedures and Ethics Committees and was performed in strict accordance with the U . K Home Office Animals ( Scientific Procedures ) Act 1986 ( approved H . O Project Licenses 70/6995 and 70/7293 ) . C57BL/6 mice were purchased from Charles River , UK . Breeding pairs of C57BL/6 IL-27R knockout ( WSX-1−/− ) mice [46] were provided by Amgen Inc ( Thousand Oaks , USA ) . C57BL/6 IL-10−/− and C57BL/6 IL-10R1−/− knockout mice were kindly provided by Professor Werner Muller ( University of Manchester ) . DEREG mice , which express DTR receptor and GFP under control of the FoxP3 promoter [47] , were kindly provided by Dr Mark Travis ( University of Manchester ) . All mice were maintained at the London School of Hygiene and Tropical Medicine and the University of Manchester . All transgenic mice were fully backcrossed to C57BL/6 background . Sex-matched 6 to 10 weeks old mice were used in separate experiments and maintained in individually ventilated cages . Cryopreserved P . berghei NK65 parasites were thawed and passaged once through C57BL/6 mice before being used to infect experimental animals . Mice were infected intravenously with 104 parasitized red blood cells ( pRBC ) . In some experiments , WSX-1−/− mice were injected intraperitoneally with 250 µg anti-IL-12p40 ( clone C17 . 8 ) , 250 µg anti-IL-2 ( JES6-5H4 ) or 300 µl of clodronate liposomes on days 7 , 9 , 11 and 13 of infection . Purified rat IgG2a was used to verify the specific in vivo activity of anti–IL-12p40 and anti-IL-2 Abs . All Abs were obtained from BioXCell ( West Lebanon , NH ) . DEREG mice and non-transgenic littermates were injected with 200 ng DT i . p . from day −1 and every two days p . i . The course of infection was monitored every 2nd day by microscopic examination of peripheral parasitaemia on Giemsa-stained thin blood smears and by assessing weight loss . Spleens were collected from naïve and malaria-infected mice ( days 7 , 9 , 11 or 13/14 ) and single-cell suspensions were prepared by homogenization through a 70 µm cell strainer ( BD Biosciences ) . RBCs were lysed ( RBC lysing buffer , BD Biosciences ) , splenocytes washed and resuspended in FACS buffer ( HBSS with 2% FCS ) . Live/dead cell differentiation and absolute cell numbers were calculated by trypan blue exclusion ( Sigma-Aldrich ) using a haemocytometer . CD4+ T cells were characterised by surface staining with anti-mouse antibodies against CD4 ( GK1 . 5 ) , CD44 ( IM7 ) , CD62L ( MEL-14 ) , CXCR3 ( CXCR3-173 ) , KLRG1 ( 2F1 ) , IFNγR1 ( 2E2 ) , IL-12Rβ1 ( 114 ) , PD-1 ( RMP1-30 ) , BTLA ( 8F4 ) , CTLA-4 ( UC10-4B9 ) , CD25 ( PC61 ) , IL-18Rα ( BG/IL18RA ) , IL-7Rα ( A7R34 ) , IL-15Rα ( DNT15Ra ) , IL-21R ( 4A9 ) , LAG-3 ( C9B7W ) , TIM-3 ( RMT3-23 ) and CD226 ( 10E5 ) . For intracellular staining , surface-stained cells were washed in FACS buffer and permeabilized with Foxp3 fixation/permeabilization buffers ( eBioscience ) for 30 min . The cells were then washed and stained in FACS buffer with anti-mouse antibodies against T-bet ( 4B10 ) , Foxp3 ( FJK-16s ) and CTLA-4 ( UC10-4B9 ) for 30 minutes . To assess intracellular IFN-γ and TNF production , 1×106 live cells were incubated in RPMI 1640 medium supplemented with 10% FCS , 200 ng/ml PMA ( Sigma ) and 1 µg/ml ionomycin ( Sigma ) in the presence of Brefeldin A ( 1∶1000 ) for 5 h at 37°C , 5% CO2 . For experiments where specific parasite responses were assessed , T cells were depleted in naïve splenocytes from WT or WSX-1−/− mice using anti-TCRβ PE antibodies and anti-PE conjugated MACS beads ( Miltenyi Biotec ) , according to the manufacturer's instructions . TCR-depleted splenocytes were seeded at 250 , 000/well and pulsed overnight with 15×106 P . berghei NK65 pRBC lysate/ml . Control samples included non-pulsed splenocytes . Cultures were then incubated with 125 , 000 purified naïve or day 13 infection-derived WT or WSX-1−/− CD4+ T cells . IFN-γ levels were assessed by intracellular staining after 18 h culture . To detect intracellular IL-2 , 1×106 cells were stimulated with 2 µg/ml of anti-CD3 ( BD biosciences ) for 96 hrs , followed by PMA and inonomycin restimulation in presence of brefeldin A , as described above . The cells were washed , stained for surface markers CD4 and CD44 , permeabilized and stained with anti-mouse IFN-γ ( XMG1 . 2 ) , anti-mouse TNF ( MP6-XT22 ) or anti-mouse IL-2 ( JES6-5H4 ) . All antibodies were purchased from eBioscience , Biolegend or BD Biosciences . Fluorescence minus one controls were used to validate flow cytometric results ( Figure S9 ) . All flow cytometry acquisition was performed using an LSR II ( BD Systems , UK ) . All FACS analysis was performed using Flowjo Software ( Treestar Inc , OR , USA ) . For the analysis of cell proliferation in vivo , 1 . 25 mg sterile BrdU ( 5-bromodeoxyuridine ) diluted in PBS was injected intraperitoneally 1 h before mice were killed and organs harvested . Single cell splenocyte suspensions were prepared and surface molecules stained as described above . Intracellular BrdU incorporation was measured by flow cytometry using an anti-BrdU antibody ( clone PRB-1 , eBioscience ) following the manufacturer's instructions . Cells were co-stained for the nuclear antigen Ki67 ( clone B56 , BD Biosciences ) . Survival of naïve ( CD62Lhigh CD44low ) and effector Th1 ( CD62low CD44high T-bet+ ) CD4+ T cells was assessed by intracellular staining of Bcl-2 ( clone BCL/10C4 , BioLegend ) . T cell apoptosis was assessed by flow cytometry using Annexin V ( BD biosciences ) and fixable viability dye ( eBioscience ) , following the eBioscience Annexin V staining protocol . Splenic single-cell suspensions from uninfected , day 9 and day 14 P . berghei NK65 infected C57BL/6 and WSX-1−/− mice were obtained as described above . 1×106 cells/sample were rested on ice in Medium for 30 min . Cells were incubated with 20 ng/ml IL-2 ( eBioscience ) or 2 . 5 ng/ml IL-12 ( R&D Systems ) for 10 min at 37°C , 5% CO2 and immediately fixed for 15 min on ice by addition of an equal volume of 4% paraformaldehyde . Cells were permeabilized with 90% ice-cold methanol at −20°C o/n and then stained for CD4 , CD44 , CD62L , T-bet and phosphorylated STAT4 ( at residue Y693 , clone 38 ) or phosphorylated STAT5 ( at residue Y694 , clone 47; both BD Biosciences ) in FACS buffer , washed and analysed by flow cytometry . Heparinised blood from uninfected and P . berghei NK65 infected C57BL/6 , IL-10−/− , WSX-1−/− , anti-IL-12p40 and clodronate liposomes treated WSX-1−/− mice was collected and spun at 5000 g for 6 minutes . Plasma was immediately stored at −80°C until further use . Plasma IL-12p70 , IL-2 and IFN-γ were measured by Cytometric bead array ( CBA ) assay ( BD Biosciences ) , following the manufacturer's instructions . Splenic MHC-II+ splenocytes from P . berghei NK65 infected WT and WSX-1−/− mice ( day 13 p . i . ) were presorted by positive magnetic selection using anti-MHC-II PE antibody and anti-PE MACS beads ( Miltenyi ) . Cells were stained with a cocktail of antibodies against CD3e ( 145-2C11 ) , CD8a ( 53-6 . 7 ) , CD11b ( 14 . 0112 . 81 ) , CD11c ( 17-0114-81 ) and F4-80 ( 14-4801-81 ) and different APC populations were sorted using a FACSAria according to the gating strategy described in Figure S7A . mRNA was isolated using the RNeasy isolation kit ( Qiagen , Valencia , CA ) and DNAse I treated ( Ambion/ABI , Austin , TX ) prior to cDNA synthesis . IL-12p35mRNA levels were quantified using validated gene expression assays from ABI Biosystems and cDNA expression was standardized using the housekeeping gene â-actin . ( Life Technologies Ltd , Paisley UK ) . A section of liver tissue was removed on day 13/14 p . i . from all animal groups and fixed in 10% formalin saline . Fixed tissues were paraffin embedded and sectioned , followed by H&E staining ( Independent Histological Services , London , U . K . ) . Sections were examined under a light microscope using ×20 magnification . All data were tested for normal distributions using the D'Agostino and Pearson omnibus normality test . In two group comparisons statistical significance was determined using the t test or the Mann–Whitney U test , depending on distribution of the data . For three or more group comparisons , statistical significance was determined using a one-way ANOVA , with the Tukey post hoc analysis for normally distributed data , or a Kruskal–Wallis test , with Dunn post hoc analysis for nonparametric data . All statistical analyses were performed using GraphPad Prism . Results were considered as significantly different when p<0 . 05 .
The cytokine interleukin 27 ( IL-27 ) , a member of the IL-12 family , is produced by cells of the innate immune system and has been shown to exert mainly suppressive effects during a wide range of inflammatory conditions , including malaria infection , where it suppresses the development of CD4+ T cell-dependent immunopathology . In this study we show that IL-27 suppresses the production of IFN-gamma by CD4+ T cells during blood stage malaria infection by preventing the development of terminally differentiated Th1 cells . We investigated the molecular mechanisms by which IL-27 inhibits the formation of terminally differentiated Th1 cells and found that it does so specifically by restricting IL-12 signals . Importantly , we demonstrate that IL-27 mediates its regulatory effects on the Th1 response through IL-10 and Foxp3+ regulatory T cell independent mechanisms . Thus , we have identified a new pathway though which IL-27 signalling regulates the size and quality of the Th1 response during malaria infection , which we believe will have relevance to many other pro-inflammatory conditions . Manipulation of the IL-27 pathway may therefore represent an amenable therapeutic approach during chronic inflammatory disorders .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "protozoan", "classification", "immune", "cells", "immunology", "microbiology", "host-pathogen", "interaction", "parasitology", "immune", "defense", "immunoregulation", "inflammation", "biology", "pathogenesis", "immune", "response", "immunopathology", "immunity", "protozoology" ]
2013
IL-27 Receptor Signalling Restricts the Formation of Pathogenic, Terminally Differentiated Th1 Cells during Malaria Infection by Repressing IL-12 Dependent Signals
Human T cell leukemia virus type 1 ( HTLV-1 ) is the etiologic agent of Adult T cell Leukemia ( ATL ) and the neurological disorder HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) . Although the majority of HTLV-1–infected individuals remain asymptomatic carriers ( AC ) during their lifetime , 2–5% will develop either ATL or HAM/TSP , but never both . To better understand the gene expression changes in HTLV-1-associated diseases , we examined the mRNA profiles of CD4+ T cells isolated from 7 ATL , 12 HAM/TSP , 11 AC and 8 non-infected controls . Using genomic approaches followed by bioinformatic analysis , we identified gene expression pattern characteristic of HTLV-1 infected individuals and particular disease states . Of particular interest , the suppressor of cytokine signaling 1—SOCS1—was upregulated in HAM/TSP and AC patients but not in ATL . Moreover , SOCS1 was positively correlated with the expression of HTLV-1 mRNA in HAM/TSP patient samples . In primary PBMCs transfected with a HTLV-1 proviral clone and in HTLV-1-transformed MT-2 cells , HTLV-1 replication correlated with induction of SOCS1 and inhibition of IFN-α/β and IFN-stimulated gene expression . Targeting SOCS1 with siRNA restored type I IFN production and reduced HTLV-1 replication in MT-2 cells . Conversely , exogenous expression of SOCS1 resulted in enhanced HTLV-1 mRNA synthesis . In addition to inhibiting signaling downstream of the IFN receptor , SOCS1 inhibited IFN-β production by targeting IRF3 for ubiquitination and proteasomal degradation . These observations identify a novel SOCS1 driven mechanism of evasion of the type I IFN antiviral response against HTLV-1 . Infection with the Human T cell Leukemia Virus type I ( HTLV-I ) can result in a number of disorders , including the aggressive T cell malignancy Adult T cell Leukemia ( ATL ) and the chronic , progressive neurologic disorder termed HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) [1] , [2] , [3] . In endemic areas including Southern Japan , the Caribbean basin , Western Africa and Central/South America - where infection rates range from 2 to 30%- these diseases are major causes of mortality and morbidity [4] . The majority of HTLV-1–infected individuals remain asymptomatic ( AC ) during their lifetime and only ∼2–5% of AC will develop either ATL or HAM/TSP [5] , [6] . Although the factors determining progression from AC to ATL or HAM/TSP remain unknown , it is well established that the risk of ATL vs . HAM/TSP development varies dramatically with the geographical distribution of HTLV-1-infected populations . Clinically , acute ATL is characterized by abnormally elevated T cell counts , accompanied by readily observed ‘flower cells’ – multi-lobed , leukemic cells with highly condensed chromatin - hypercalcemia , prominent skin lesions , hepatosplenomegaly and suffer from serious bacterial , viral , fungal and protozoan infections . Most patients present at this final acute stage , often unaware of their HTLV-1 positive status and given a poor prognosis , with a survival estimate of 6–10 months [7] . Transformation of CD4+ T lymphocytes by HTLV-1 and the development of ATL leukemogenesis generally occur in two stages [8] , [9] . After infection with the blood borne pathogen , HTLV-1 induces IL-2-dependent , CD4+ T cell proliferation , that over a period of decades in vivo , progresses with the emergence of an IL-2-independent malignant clone that has accumulated multiple secondary genetic changes in growth regulatory and tumor suppressor genes [9] , [10] . HTLV-1 encodes the 40-kDa nuclear oncoprotein Tax that promotes cellular transformation through dysregulation of mitotic checkpoints , activation of cellular signaling pathways and inactivation of tumor suppressors ( reviewed in [11] , [12] ) . HAM/TSP is a systemic immune-mediated inflammatory disease characterized by demyelination of motor neurons in the spinal cord , although other tissues can also be damaged [13] . HAM/TSP attacks in the prime of life ( median age of onset: 35 years ) and is associated with a clinical history that includes neurological symptoms in 80% of cases – gradual onset of leg weakness , paresthesis , and impairment of urinary or bowel function . Central nervous system ( CNS ) white matter lesions of the spinal cord harbor activated CD4+ and CD8+ T cells during early stages of disease , with a predominance of CD8+ T cells later in disease . HTLV-1 viral RNA has been found associated with CD4+ T cells and astrocytes in CNS lesions , suggesting that virus-infected cells migrate through the blood-brain barrier and infect CNS resident cells [14] , [15] . While the mechanisms resulting in HAM/TSP development remain unresolved , it has been suggested that Tax expression in CNS cells triggers a strong virus-specific CD8+ ( as well as CD4+ ) T cell response leading to inflammation , myelin loss , and axonal damage [16] , [17] . Elevated levels of proinflammatory cytokines ( IL-6 , IFN-γ , IL-15 , IL-1β , TNF-α and IL-12 ) have been detected in the serum and cerebrospinal fluid ( CSF ) of patients with HAM/TSP , corroborating the link between HAM/STP development and dysregulated inflammation [18] , [19] . It is widely accepted that type I interferon ( IFN-α/β ) has a negative impact on HIV-1 replication [20] , [21] , and although few reports have documented the IFN antiviral effects during HTLV-1 infection , type I IFN constitutes a potent anti-retroviral mechanism that affects HTLV-1 replication [22] , [23] . In return , HTLV-1 infection of pDCs results in impaired IFN-α production , and correlates with elevated HTLV-1 proviral load in infected individuals [24] . Central to the establishment of an antiviral state is the activation of diverse IFN-stimulated genes ( ISGs ) which restrict viral replication [25] . Interferon regulatory factors IRF3 and IRF7 play essential roles in the early phase of IFN gene activation [26] . IRF3 is constitutively expressed and is activated by C-terminal phosphorylation by IKKε and TBK1 , which promotes transactivation of downstream genes such as IFN-β and IFN-α [27] , [28] . In contrast , IRF7 protein is synthesized de novo upon IFN stimulation and contributes to the amplification of the IFN response , via expression of multiple IFN-α subtypes [29] . IRF-driven IFN secretion acts in a paracrine fashion to induce the expression of hundreds of genes through engagement of the IFN receptors and activation of the JAK/STAT signaling pathway , which leads to the development of an antiviral state ( reviewed in [30] , [31] ) . IFN-induced JAK/STAT signaling is negatively regulated at different levels by several cellular factors to control the extent of the antiviral response and limit tissue damage [32] , [33] . Suppressor of cytokine signaling 1 ( SOCS1 ) belongs to the SOCS protein family and is induced after virus infection [34] . SOCS1 suppresses IFN signaling by direct binding to phosphorylated type I IFN receptor and active JAK kinase , abrogating phosphorylation of STAT1 [35] . Through its SOCS-Box domain , SOCS1 targets various proteins such as JAK , MAL , p65 , Steel , Vav for proteasomal degradation [36] , [37] , [38] . The SOCS-Box serves as a recruiting platform for the formation of a E3 ligase complex composed of elongin B/C-Cullin 2 and Rbx2 [39] , [40] . Thus , SOCS1 initiates and orchestrates the events leading to proteasomal degradation of target proteins [34] . Recently , virus-induced upregulation of SOCS1 protein has emerged as a novel mechanism employed by several viruses to evade the antiviral response [41] , [42] , [43] . In the present study , global gene expression profiles in CD4+ T lymphocytes were examined in a unique cohort of 30 HTLV-1 infected individuals from the Caribbean basin including ATL , HAM/TSP and asymptomatic carriers ( AC ) patients . Interestingly , among the many genes dysregulated in HTLV-1 infected patients , SOCS1 was highly expressed in CD4+ T cells from HAM/TSP and AC patients , but not in ATL . Subsequent biochemical analysis demonstrated that HTLV-1-induced SOCS1 expression played a positive role in viral replication through inhibition of the IFN response . SOCS1 directly interacted with IRF3 and promoted its proteasomal degradation in a SOCS-Box dependent manner , thus identifying a novel mechanism of HTLV-1 mediated evasion of the IFN response . To analyze gene expression profiles of CD4+ T cells isolated from HTLV-1 infected patients , we gathered a unique cohort of 30 HTLV-1 infected individuals from the Caribbean basin , including 11 AC , 7 ATL , 12 HAM/TSP and 8 healthy , non-infected donors ( NI ) ( Table S1 ) . Microarray experiments were performed using the human ImmuneArray cDNA array ( UHN Microarray Center , University of Toronto ) , followed by higher order analysis . About three thousand genes were analyzed with Future Selection Subset/ANOVA on log-transformed data , followed by unsupervised hierarchical clustering on 1039 genes selected by Anova analysis ( p<0 . 01 ) ( Figure 1A ) . These genes displayed differential expression patterns depending on the type of HTLV-1-associated disease . Unsupervised clustering based on the 1039 genes signature accurately discriminated between NI , HAM/TSP and ATL patients . AC samples however did not separate as an individual cluster , but rather distributed amongst HAM/TSP and ATL samples . Also , two of the HAM/TSP patients and two AC clustered with the NI group , suggesting that the profile of their circulating CD4+ T lymphocytes had not undergone significant variation compared to healthy donors . Pair-wise correspondance analysis ( PCA ) was performed on the top 500 genes modulated in HTLV-1-infected versus non-infected samples ( p value <0 . 01 , false discovery rate ( FDR ) = 0 . 17% ) ( Figure 1B ) . PCA identified prevalent expression profiles among the three clinical groups , and confirmed significant class discrimination between non-HTLV-1-infected donors ( NI ) versus each of the HTLV-1-associated diseases when plotted in two dimensions ( Figure 1B ) . Gene clusters common to each HTLV-1-infected clinical group , and shared within pair-wise comparisons ( AC-HAM/TSP , AC-ATL and ATL-HAM/TSP ) , could be identified and are presented in the adjoining Tables of Figure 1B . For each grouping , genes with a high differential expression are located with quantitative spacing from the center comparator ( gene expression of NI group ) . Specifically , SOCS1 ( green square ) was identified as a strongly upregulated gene in both HAM/TSP and AC patients , in agreement with the prior observation by Nishiura et al . [44] . Since SOCS1 is known to counter-regulate the anti-viral response , it was selected as a gene of interest for further study . Efficient HTLV-1 spread must overcome cellular antiviral programs [45]; yet how HTLV-1 evades the host innate immune response is poorly understood . SOCS1 stood out among the many genes identified as having the potential to counteract the innate immune response against HTLV-1 . HAM/TSP and AC patients exhibited a greater than two fold increase in SOCS1 gene expression compared to NI individuals ( Fisher's test , p value = 0 . 054 and <0 . 05 , respectively ) ( Figure 2A ) . However , no significant difference in mRNA levels of SOCS1 was found between ATL and NI patients , suggesting that SOCS1 expression was upregulated in AC and HAM/TSP . This increase was specific for SOCS1 , as SOCS3 mRNA was unchanged in HTLV-1 infected samples compared to control samples ( fold change <2 ) ( Figure 2B ) . Using a separate cohort of patient samples ( Table S2 ) , we demonstrated that SOCS1 expression was strongly and positively correlated with HTLV-1 mRNA load in CD4+ T cells of HAM/TSP patients ( Pearson's p<0 . 0001 ) ( Figure 2C ) . Since high proviral load is a hallmark of HAM/TSP pathology [46] , we investigated the relationship between HTLV-1 replication and SOCS1 gene expression . Initially , the level of SOCS1 mRNA was examined in HTLV-1-carrying T cell lines ( MT-2 , C8166 , MT-4 , RMP ) , control T cell lines ( Jurkat and CEM , Figure 2D and Figure S2 ) , as well as PBMCs infected with the HTLV-1 infectious molecular clone pX1M-TM ( Figure 2D and 2E ) . In non-leukemic MT-2 cells that carry an integrated replication-competent provirus and produce infectious HTLV-1 viral particles , a ∼50-fold increase in SOCS1 mRNA was detected , as compared to non-infected CEM and Jurkat cells ( <5-fold ) . In leukemic MT-4 and C8166 cells , which carry a defective provirus , lower levels of SOCS1 mRNA were detected , suggesting that SOCS1 induction required an intact proviral genome ( Figure 2D ) . The RMP cell line derived from an ATL patient which express low amount of HTLV-1 mRNA also displayed lower SOCS1 level ( ∼10-fold ) . In order to determine whether de novo HTLV-1 infection induced SOCS1 expression , PBMCs expressing the HTLV-1 infectious molecular clone pX1M-TM ( Figure 2E ) were analyzed for the level of SOCS1 and HTLV-1 mRNA at different times post-transfection . HTLV-1 RNA expression was determined by amplifying the pX region ( tax/rex ) of the HTLV-1 proviral genome; HTLV-1 RNA expression was modest between 24 and 72 h ( <10-fold ) , but the viral mRNA load increased sharply at 96 h ( 50-fold ) , concomitent with a dramatic increase in SOCS1 gene expression ( ∼24-fold ) . The initial observation that SOCS1 was induced upon HTLV-1 infection prompted us to examine whether SOCS1 also influenced viral replication . To do so , the effect of SOCS1 expression on HTLV-1 provirus replication was examined in the CEM T cells , co-expressing a SOCS1 expression vector together with the HTLV-1 provirus . The level of HTLV-1 mRNA was consistently higher in SOCS1 expressing cells compared to CEM cells expressing HTLV-1 provirus alone ( e . g . 55-fold vs . 10-fold at 24 h ) ( Figure 3A ) . As a complementary strategy , SOCS1 expression was silenced in MT-2 cells ( Figure 3B ) ; siRNAs targeting SOCS1 ( siSOCS1 ( 1 ) siSOCS1 ( 2 ) and siSOCS1 ( 1 ) +siSOCS1 ( 2 ) ) inhibited SOCS1 levels by 50 , 75 and 90% , respectively . Knock-down of SOCS1 protein expression was confirmed by immunoblot assay ( Figure 3B , bottom panel ) . Real time PCR analysis of the HTLV-1 pX region demonstrated a significant reduction of HTLV-1 mRNA that directly correlated with the decrease in the observed SOCS1 levels ( ∼27 , 56 and 80% decrease , respectively ) . These data indicate that SOCS1 induction during HTLV-1 infection leads to enhanced HTLV-1 replication . Since SOCS1 has been shown to negatively regulate type I IFN signaling [34] , [42] , we sought to investigate the relationship between HTLV-1 infection , type I IFN response and SOCS1 gene expression . First , the profile of type I IFN ( IFN-β and IFN-α2 ) and IFN-stimulated gene expression ( IRF7 and CXCL10 ) was examined in PBMCs expressing the HTLV-1 provirus pX1M-TM ( Figure 4A ) . IFN-β , IFN-α2 and CXCL10 mRNAs were induced ( 30 , 3 . 5 and 35-fold , respectively ) at 24 h post-HTLV-1 transfection , and IRF7 mRNA expression ( ∼11-fold ) was maximal at 36 h . However , mRNA transcripts for all these genes decreased substantially ( below 50% of maximal levels ) by 48–72 h . At 96 h , when HTLV-1 and SOCS1 gene expression were maximal , no reactivation of antiviral gene transcription was detected ( Fig 2D and 4A ) . We interpret this result as indicating that early after infection , transient stimulation of the antiviral response occurs and restricts de novo HTLV-1 RNA expression; at 72–96 h after infection induction of SOCS1 results in the shutdown of the type I IFN response , thus promoting high HTLV-1 mRNA expression . IFN-α signaling is initiated by binding to the heterodimeric IFN-α receptor , followed by activation of JAK1 and TYK2 protein kinases , resulting in the phosphorylation of STAT1 and STAT2 [31] . To investigate whether HTLV-1 expression interfered with the type I IFN response , primary PBMCs expressing the HTLV-1 provirus pX1M-TM were treated with IFN-α for 10–120 min to focus on early IFN-triggered phosphorylation events . In control PBMCs , STAT1 and JAK1 phosphorylation was detected at 10 and 20 min post-IFN-α treatment , as determined by immunoblotting with specific antibodies ( Figure 4B ) . However , in PBMCs expressing the proviral clone pX1M-TM , IFN-α-induced phosphorylation of JAK1 and STAT1 was reduced >90 and 70% , respectively ( Figure 4B ) , while total protein levels of JAK1 and STAT1 remained unchanged in control and HTLV-1 expressing PBMCs . To further characterize the effect of HTLV-1 on antiviral response , PBMCs expressing the HTLV-1 provirus were infected with Sendai virus ( SeV ) - a strong inducer of the antiviral response - and kinetics of expression of IFN genes was assessed by Q-PCR ( Figure 4C , D , E ) . At 24 h post-transfection , PBMCs had significant HTLV-1 proviral load ( ∼700 fold higher than control , Figure 4C ) ; thus at this time , PBMCs were infected with SeV ( 20 HAU/mL ) to compare the levels IFN-α2 and IFN-β mRNA in the presence or absence of HTLV-1 provirus ( Figure 4D and E ) . Induction of IFN-β and IFN-α2 mRNA was detected in all PBMCs as early as 3 h post-SeV infection and was sustained up to 12 h ( Figure 4D and E ) . However , in HTLV-1 expressing PBMCs , induction of IFN-β and IFN-α2 mRNA was reduced >60% , relative to the level observed in the absence of HTLV-1 provirus . Decreased levels of IFN-β and IFN-α2 in cells expressing the HTLV-1 provirus were not due to inhibition of SeV replication , as demonstrated by immunoblot for SeV proteins ( Figure 4F ) . Similarly , knockdown of SOCS1 in MT-2 cells reversed the inhibition of antiviral gene expression imposed by HTLV-1 ( Figure 5 ) . Pooled siSOCS1 resulted in increased IFN-β ( 7 . 5-fold ) , ISG56 ( 2 . 5-fold ) , IFN-γ ( 4-fold ) and CXCL10 ( ∼10-fold ) gene expression compared to control siRNA . These results demonstrate that SOCS1 contributes to the inhibition of antiviral responses during HTLV-1 infection . Many pathogenic viruses strategically antagonize the early innate antiviral defenses in order to maintain viral replication , often inactivating IFN signaling components as part of their immune evasion strategy ( reviewed in [45] ) . Because IRF3 is essential for IFN gene activation , we assessed IRF3 dimerization ( as a measure of activation ) in PBMCs expressing the HTLV-1 provirus ( Figure 6A ) . In control PBMCs , SeV infection induced IRF3 dimer formation at 3–12 h post-infection , whereas IRF3 dimer formation was not detected in PBMCs expressing the HTLV-1 provirus . Furthermore , IRF3 monomer levels decreased sharply during the course of HTLV-1 replication ( Figure 6A ) . Immunoblot analysis for total IRF3 confirmed that IRF3 levels decreased in a time dependent manner in PBMCs and Jurkat cells expressing the HTLV-1 provirus , a phenomenon not observed in control PBMCs infected with SeV ( Figure 6C ) . IRF-3 was degraded via the proteasomal pathway , as the use of the proteasome inhibitor MG132 prevented HTLV-1 mediated reduction of IRF3 protein level ( Figure 6B ) . This observation demonstrates for the first time that HTLV-1 does not activate IRF3 in PBMCs , but rather prevents the initial steps of type I IFN production by targeting IRF3 for proteasomal degradation . Additionally , IRF3 silencing in Jurkat cells expressing the HTLV-1 provirus resulted in increased HTLV-1 mRNA expression ( Figure 6D ) – indicating that the degradation of IRF3 by SOCS1 enhances viral mRNA load . Given that SOCS1 upregulation during HTLV-1 infection inhibits the expression of IFN and ISGs , we sought to investigate the role of SOCS1 in HTLV-1-mediated degradation of IRF3 . In HEK293T cells expressing increasing amounts of SOCS1 together with a constant amount of IRF3 , SOCS1 expression induced IRF3 degradation in a dose-dependent manner ( Figure 7A ) . RT-PCR analysis with specific IRF3 primers showed that the level of IRF3 mRNA remained unchanged , indicating that SOCS1 had no effect on IRF3 gene expression ( Figure 7A ) . Moreover , SOCS1 silencing in HTLV-1 infected MT-2 cells restored endogenous IRF3 expression ( Figure S3 ) . Interestingly , the addition of the proteasome inhibitors lactacystin ( Figure 7B ) or MG132 ( data not shown ) prevented IRF3 degradation in the presence of SOCS1 . Furthemore , co-immunoprecipitation experiments demonstrated that SOCS1 physically interacted with IRF3 ( Figure 7C ) , indicaing that IRF3 degradation was triggered by physical association with SOCS1 . SOCS1 induces degradation of target proteins by recruiting Elongin B/C to its SOCS-Box domain , leading to the formation of an E3 ubiquitin ligase complex able to modify substrate proteins with K48-linked ubiquitin chains . To confirm that SOCS1-mediated IRF3 degradation required E3 ligase complex activity , increasing amounts of a SOCS1 deletion mutant lacking the SOCS-Box - SOCS1-ΔB/C-Box - was expressed together with a constant amount of IRF3 ( Figure 7D ) ; SOCS1-ΔBC did not induce IRF3 degradation at any concentration ( compare Figures 7D and 7A ) . Proteasome-mediated degradation requires the addition of K48-polyubiquitin chain to the target protein; exogenous addition of ubiquitin mutated in its ability to link K48-polyubiquitin chains ( ubiquitin-K48R , which contains a single K48R point mutation , or Ubi-KO , which contains no lysines ) prevented IRF-3degradation , while HEK293 cells expressing exogenous SOCS1 readily degraded IRF3 ( Figure 7E ) . In addition , IRF3 turnover was completely reversed in the presence of a 10-fold excess of HA-Ub K48R or HA-Ub KO ( Figure 7E ) , thus confirming that proteosome-mediated IRF3 degradation by SOCS1 requires recruitment of Elongin B/C E3 ligase machinery and is dependent on K48-polyubiquitin chain formation . The complexity of gene expression dysregulation in ATL or HAM/TSP diseases has been highlighted in a number of gene expression profiling [47] , [48] and protein profiling studies [49] . The present study however represents the first comparative genome-wide array analysis to establish gene expression profiles for HTLV-1-associated disease states . With a unique cohort of 30 HTLV-1-infected individuals from the Caribbean basin and a custom ImmuneArray [50] , we identified ∼1039 significant immune-related genes that were differentially regulated in CD4+ T cells from 11 AC , 7 ATL , 12 HAM/TSP patients , compared with CD4+ T cells from 8 NI donors from the same geographical region . Clear clinical discrimination was observed between the ATL , HAM/TSP and NI patients , both by unsupervised hierarchical cluster and principal component analysis . Our analysis revealed that the gene expression profile in ATL cells was clearly distinct from healthy CD4+ T cells , although similarities in gene expression patterns were observed between HAM/TSP samples and NI controls . This difference between HAM/TSP and ATL CD4+ T cells likely reflects numerous alterations in gene expression that occur during ATL transformation [12] . In contrast , evolution to HAM/TSP does not involve cellular transformation , but rather is characterized by a high HTLV-1 proviral load and the establishment of a pro-inflammatory microenvironment due to cytokine/chemokine production of infected and bystander immune cells . It is possible that T lymphocytes derived from early-stage HAM/TSP patients have a profile similar to healthy cells and that gene expression changes are observed only at later stages of the disease , an interesting hypothesis that needs to be investigated further . Interestingly , AC patients did not cluster as an individual group but rather distributed amongst NI , ATL and HAM/TSP patients , suggesting that extensive analysis of the genes modulated in NI , HAM/TSP and/or ATL groups may help to identify candidate genes important for early diagnosis of HTLV-1 diseases . Here , the major cellular pathways identified involved cell adhesion ( CXCR4 , CD2 , CD63 ) , antimicrobial defense ( KLRB1 , SPN , SELPLG ) , innate immune signaling ( SOCS1 , TRAF3 , AIM2 , TLR2 , IKBKG , STAT3 ) , antigen presentation ( TRA alpha locus ) , and chemotaxis ( CCL14 , SPN , CCL13 ) thus supporting the idea of a global disruption of the immune system during HTLV-1 infection . Among the many genes modulated during HTLV-1 infection , the suppressor of the interferon signaling - SOCS1 - was upregulated in HAM and AC patients but not in ATL . This observation is in agreement with a previous report published by Nishiura et al . demonstrating that SOCS1 mRNA levels were increased in HAM/TSP patients compared to NI [44] . We now demonstrate that CD4+ T cells from HAM/TSP and AC patients express increased levels of SOCS1 which strongly correlates with HTLV-1 mRNA load . Since HAM/TSP patients are characterized by a very high proviral load , we hypothesized that SOCS1 upregulation in HAM/TSP may represent an immune evasion strategy used by HTLV-1 to dampen the early IFN antiviral response . Indeed , in PBMCs expressing a HTLV-1 infectious molecular clone , and in cell lines harboring an intact HTLV-1 provirus , high levels of SOCS1 gene expression correlated with high levels of HTLV-1 transcription . Increasing HTLV-1 proviral expression blocked expression of type I IFN genes such as IFN-β , IRF7 , IFN-α2 , as well as the IFN-γ stimulated chemokine gene CXCL10 , with maximal inhibition observed when HTLV-1 and SOCS1 gene expression levels were coordinately elevated . Furthermore , depletion of SOCS1 using siRNA decreased HTLV-1 replication and restored the type I IFN response . IFN-α/β is known to have a negative impact on retrovirus replication . Although few studies have reported its effect on HTLV-1 , type I IFN constitutes a potent anti-retroviral mechanism that limits HTLV-1 replication [22] , [23] . Moreover , clinical studies using IFN-β therapy in HAM/TSP patients have demonstrated benefits in reducing HTLV-1 mRNA load and the number of pathogenic CD8+ T cells , as well as minimizing disease progression during therapy [51] . Accumulating evidence indicates that HTLV-1 possesses evasion mechanisms to counteract type I IFN signaling: for example , HTLV-1 down-regulates JAK-STAT activation by reducing phosphorylation of Tyk2 and STAT2 , possibly through a Gag- or Pr-mediated mechanism [52]; and Tax further negatively modulates IFN-α-induced JAK/STAT signaling by competing with STAT2 for CBP/p300 coactivators [53] . SOCS1 is a cytokine-inducible intracellular negative regulator that inhibits type I and II IFN signaling by triggering the degradation of various components of the JAK-STAT cascade ( reviewed in [32] , [54] ) . SOCS1 can also be induced during virus infection and plays a positive role in viral replication [55] , [56] , [57] . SOCS1 is induced during virus infection and binds directly to the type I IFN and/or II IFN receptors to suppress IFN signaling , thereby preventing chronic inflammation . However , SOCS1 could be subverted to enhance viral replication via untimely inhibition of the IFN response . SOCS1 induction may be a direct result of viral protein activity . Bioinformatics analysis of the SOCS1 promoter region reveal the presence of CRE , AP-1 and NF-κB binding regions , suggesting the possible involvement of HTLV-1 Tax in the induction of SOCS1 expression ( data not shown ) . Another possibility is that SOCS1 transcriptional activation is not directly regulated by viral proteins , but rather by recognition of viral RNA and downstream signaling events . For instance , Potlichet et al . reported that Influenza A virus suppresses the antiviral response by inducing SOCS1 and SOCS3 via TLR3-independent but RIG-I/IFNAR dependent pathways [43] . Moreover , IFN-γ gene expression in CD4+ T cells from HAM/TSP patients is elevated as compared to ATL or AC patients . Constitutive induction of IFN-γ may also augment SOCS1 expression , and thus increase HTLV-1 replication . SOCS proteins exert their negative effect by promoting the ubiquitination and proteosomal degradation of key proteins involved in cytokine signaling pathways: MAL in Toll like receptor 4 signaling ( TLR4 ) , JAK2 in IFN-γ mediated signaling and NF-κB p65/RelA are all known targets of SOCS1 [38] , [58] , [59] . Here , we identified IRF3 as an important target for SOCS1-induced proteasomal degradation that impacts the early type I IFN antiviral response . IRF3 is ubiquitously expressed in the cytoplasm and is activated in response to viral infection , triggering IFN-β and other early ISGs expression , thus initiating the antiviral response . To counter type I IFN , many viruses have evolved strategies to interfere with IRF3 activation as an efficient means to limit IFN-β production [26] , [60] . Interference of IRF3 activation also dampens the second wave of IFN signaling , including production of IFN-α . The mechanisms of IRF3 antagonism vary , and include inhibition of IRF3 phosphorylation , nuclear translocation , or transcription complex assembly as well as down-regulation of IRF3 by ubiquitin-mediated degradation . In this context , bovine herpes virus 1 infected cell protein 0 ( bICP0 ) has been shown to act as an E3 ligase and promote IRF3 degradation in a proteasome-dependent manner , thus inhibiting the IFN response [61] . The interaction between SOCS1 and IRF3 during HTLV-1 infection promotes proteasome-mediated degradation of IRF3 and thus abrogates early IFN antiviral signaling . SOCS1-dependent IRF3 degradation required the elongin B and C binding sites within SOCS1 and K48-linked polyubiquitination of IRF3 . Indeed , the SOCS box-mediated function of SOCS1 is chiefly exerted via its ubiquitin ligase activity [62] and biochemical binding studies have shown that the SOCS box interacts with the elongin B/C complex , a component of the ubiquitin/proteasome pathway that forms an E3 ligase with Cul2 ( or Cul5 ) and Rbx-1 [40] , [58] . Thus , SOCS1 serves as an adaptor to bring target proteins to the elongin B/C-Cullin E3 ligase complex for ubiquitination . Although we show from our current experiments that SOCS1 directly mediates K48-linked ubiquitination of IRF3 , further studies are required to elucidate the details of SOCS1-mediated IRF3 ubiquitination , as well as the mechanisms of regulation of SOCS1 during HTLV-1 infection . The present study reveals a novel mechanism of viral evasion of the IFN response in HTLV-1 infected T lymphocytes – the consequence of which can be directly related to the efficiency of HTLV-1 replication in patients suffering from HAM/TSP . Future studies are required to elucidate putative alternate consequences of SOCS1 upregulation in T cells [63] , as well as the effect of HTLV-1 induced SOCS1 expression in other relevant viral reservoirs such as dendritic cells and astrocytes [64] , [65] . Collectively , SOCS1-mediated degradation of IRF3 during HTLV-1 infection has substantial implications in the framework of known HTLV-1 pathobiology and as such opens new avenues of exploration for designing effective therapeutic strategies . Blood samples from HTLV-1 infected patients and non-infected ( NI ) donors were obtained from the Centre Hospitalier Universitaire de Fort-de-France in Martinique and Institut Pasteur de Cayenne in French Guyana . Patients suffering from ATL , HAM/TSP or HTLV-1 asymptomatic carriers were recruited according to World Health Organization ( WHO ) criteria . According to the French Bioethics laws , the collection of samples from HAM/TSP , ATL , AC and NI has been declared to the French Ministry of Research and the study was reviewed and approved by the CPP ( Comité de Protection des Personnes ) Sud-Ouest/Outre-Mer III , as well as the ARH ( Agence Régionale de l'Hospitalisation ) from Martinique . Because the protocol is non-interventional ( e . g . blood samples collected for routine health care with no additional samplings or specific procedures for subjects ) , no informed consent was provided by the patient , as stated by the French Public Health code and therefore the study was conducted anonymously . Clinical collection of samples for research purpose are stored at the Centre de Ressources Biologiques de Martinique ( CeRBiM ) . The CeRBiM database has been approved by the CNIL ( Commission nationale de l'informatique et des libertés ) . Leukophoresis from healthy donors were also obtained at the Royal Victoria Hospital , Montreal , Quebec , Canada . Informed consent were written and provided by study participants in accordance with the Declaration of Helsinki . The study was reviewed and approved by the Royal Victoria Hospital , the Jewish General Hospital , and McGill University Research Ethics Committee ( REC ) board of the SMBD-Jewish General Hospital . In total , we selected for study 12 HAM/TSP , 11 asymptomatics ( AC ) , 7 ATL and 8 not infected individuals ( NI ) . The diagnosis of the 7 ATL cases included in patient cohort number 1 respected the international consensus recently published by Tsukasaki et al . [7] . Diagnostic criteria for ATL included serologic evidence of HTLV-1 infection , and cytologically or histologically proven T cell malignancy . Six ATL cases were classified as acute leukemia type on the basis of leukemic manifestations , with >5% typical ATL cells in the peripheral blood , and immunologically confirmed mature CD4+ T cell phenotype . One case ( HISS0023 ) was a lymphoma type , with <5% circulating abnormal cells , the ATL cell phenotype and clonal integration of HTLV-1 being confirmed on lymph node tissue . Diagnosis of HAM/TSP was in accordance with WHO criteria [66] , which comprise ( 1 ) slowly progressive spastic paraparesis with symmetrical pyramidal signs , ( 2 ) disturbance of bladder function , ( 3 ) no radiologic evidence of significant spinal cord compression , and ( 4 ) intra-thecal synthesis of anti−HTLV-1 antibodies . The asymptomatic HTLV-1 carriers did not display any neurological symptoms ( Tables S1 and S2 ) . PBMCs were isolated by centrifugation ( 400 g at 20°C for 25 min ) on a Ficoll-Hypaque gradient ( GE Healthcare Bio-Sciences Inc . , Oakville , Canada ) . CD4+ T lymphocytes were isolated using a negative selection CD4 enrichment cocktail with the high-speed autoMACS system ( Miltenyi Biotec ) according to the manufacturer's instructions . In all cases , the purity of CD4+ T lymphocytes was between 90 and 95% as determined by flow cytometry . Cells were pellet and kept at −80°C until all samples were ready for RNA extraction . The HTLV-1-carrying T cell lines MT-2 , MT-4 , C8166 , RMP and the HTLV-1-negative T cell lines CEM and Jurkat were used for experiments . MT-2 , MT-4 and C8166 cells are derived from umbilical cord blood lymphocytes after cocultivation with leukemic cells from ATL patients [67] . MT-2 cells are reported to have integrated at least fifteen copies/cell , including defective types , of HTLV-1 proviral DNA whereas C8166 cells have only one copy of proviral DNA integrated in the genome [68] , [69] . The interleukin ( IL-2 ) -independent RMP cell line is derived from CD4+ T cell of a patient with acute ATL . All cell lines were maintained in RPMI 1640 medium supplemented with 10% heat-inactivated fetal bovine serum , 100 U/ml penicillinG , and 100 µg/ml streptomycin . HEK293T cells were used for transient transfection and were maintained in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with 10% heat-inactivated fetal bovine serum , 100U/ml penicillin G , and 100 µg/ml streptomycin . For proteasome inhibitor treatment , MG132 ( Sigma-Aldrich ) or Lactacystin ( Boston Biochem ) were used at 5 and 10 µM , respectively . Sendai virus CANTELL strain ( SeV ) was obtained from Charles River Laboratory ( North Franklin , CT ) . Cells were infected with SeV at 20 hemagglutinating units ( HAU ) per 106 cells in serum-free medium supplemented with 10% heat-inactivated fetal bovine serum 2 h postinfection and harvested for whole cell extracts or RNA extraction at indicated times . The HTLV-1 proviral clone pX1M-TM was kind gift from Dr David Derse ( National Cancer Institute-Frederick , Frederick , USA ) . Myc-tagged SOCS1 full length and the deletion mutant SOCS1-ΔBCBox ( amino acids 174–183 ) were kind gifts from Dr . Ferbeyre Gerardo ( Departement de Biochimie , Universite de Montreal , Canada ) . Ha-Ub-K48R and Ha-Ub-KO were kind gifts from Dr . Zhijan Chen ( Department of Molecular Biology , University of Texas Southwestern Medical Center , Dallas , Texas ) . Plasmid encoding for Flag-tagged IRF3 full length was decribed previously [27] . Total RNA was extracted using Trizol Reagent ( Invitrogen ) or RNeasy kit ( Qiagen ) according to the manufacturer's instructions . The RNA integrity and purity was assessed with the Agilent 2100 Bioanalyzer ( Agilent Technologies ) . Total RNA was amplified using the MessageAmp II mRNA kit ( Ambion , Austin , USA ) . Sample and universal human RNA probes ( Stratagene ) for microarray hybridization were prepared by labeling the amplified RNA with Cy5 or Cy3 , respectively , by reverse transcription , and hybridizing the labeled cDNA on the CANVAC ( http://www . canvac . ca/ ) human Immunoarray version 2 manufactured by the Microarray Center ( UHN , Toronto , ON , Canada ) containing 7256 duplicate spots representing 3628 expressed sequence tags ( ESTs ) . Details of the labeling and hybridization procedures can be obtained at http://transnet . uhnres . utoronto . ca . Microarrays were scanned using Scanarray Express Scanner ( Packard Biosciences ) or the Axon 4000B scanner at 10-µm resolution . Array images were inspected visually for poor quality spots and flagged for omission . Quantified raw data was acquired with QuantArray version 3 and saved as quantarray text files . The quantified raw data were managed and pre-processed in GeneTraffic ( Iobion Informatic ) . Following background correction and removal of genes where both channels were less than 100 or represented by less than 90% of the samples and polished data was generated by normalization by Lowess sub-grid . The final data array was analyzed using JExpress Pro software ( http://www . molmine ) . To establish differentially expressed genes , multi-class analysis was performed by one-way ANOVA on Log2 fold change ( Log2Fc ) data for ATL , HAM/TSP , AC and NI groups . Genes with a p value ≤0 . 01 were selected as significant ( 1039 total ) . Visualization was produced by unsupervised clustering of the 1039 genes using Pearson correlation parameters . Pair wise correspondance analysis ( PCA ) was performed on the first 500 genes by Future Subset Selection ( FSS ) t-test . Genes were selected based on false discovery rate ( FDR ) according to the Benjamini/Hochberg ( BH ) methods . Gene annotations were gathered using manual searches in NCBI as well as the ontology tools DAVID ( http://david . abcc . ncifcrf . gov/ ) and BioRag ( Bioresource for array genes , http://www . biorag . org ) . Fold change ( Fc ) for each gene was calculated as 2 ( Log2X-Log2NI ) , where Log2 X represents the Log2 ( Fc ) for either ATL , AC or HAM and Log2 NI represents the Log2 ( Fc ) for NI . Microarray data have been deposited in the NCBI Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) . The results of the microarray experiment were confirmed by quantitative PCR ( Q-PCR ) on 47 genes chosen on the basis of a fold change of at least 2-fold , with RNA from 3 patients per group used for validation . A strong correlation between the average fold-change determined by microarray and the average of the qPCR results was observed , with 25/47 genes having a Pearson correlation value of at least 0 . 6 ( Figure S1A , B , C ) and 18/47 genes with a value of at least 0 . 9 ( Figure S1A ) . Leukophoresis from healthy donors were obtained at the Royal Victoria Hospital , Montreal , Quebec , Canada . PBMCs were isolated by Ficoll-Hypaque gradient ( GE Healthcare Bio-Sciences Inc . , Oakville , Ontario , Canada ) and activated for 4 days with 2 µg/ml of phytohemagglutinin-P ( PHA-P ) ( Sigma Aldrich ) and 50 U of interleukin 2 per ml ( IL-2 ) ( PBL Biomedical Laboratories ) . 5 µg of pX1M-TM was pulsed into 10×106 cells PBMCs in a 0 . 4-cm cuvette using a Gene Pulser II ( Bio-Rad Laboratories ) set at 0 . 25 kV and 0 . 95 µF . Cells were plated in six-well plates in complete medium and collected at indicated times for whole cell extracts or RNA extraction . Validation of selected target genes was performed by relative quantification PCR ( RQ-PCR ) in 9 samples ( 3 NI , 3 ATL , 3 HAM ) . A total of 2 µg of amplified RNA from uninfected and HTLV-1-infected samples was converted to cDNA using the High Capacity cDNA Archive Kit ( Applied Biosystems , Foster City , CA ) according to the manufacturer's protocol . cDNA was amplified using SyBR Green I PCR master mix ( Roche Applied Science , Germany ) or TaqMan Universal PCR Master Mix ( Applied Biosystems , Foster City , CA , USA ) . Real-time PCR primers were designed using the primer3 website ( primer3_www . cgiv . 0 . 2 ) and listed in Supporting information ( Table S3 ) . Some predesigned primers and probe sets from TaqMan ( Applied Biosystems ) were also used and listed in Table S3 . Data were then collected using the AB 7500 Real-Time PCR System ( Applied Biosystems , Foster City , CA ) and analyzed by comparative CT method using the SDS v1 . 3 . 1 Relative Quantification ( RQ ) Software where ddCT = dCT ( Sample ) – dCT ( non-infected ) , dCT ( Sample ) = CT ( Sample ) - CT ( GAPDH ) and dCT ( non-infected ) = CT ( non-infected ) - CT ( GAPDH ) . Cells destined for immunoblotting were washed with PBS and lysed in lysis buffer ( 0 . 05% NP-40 , 1% glycerol , 30 mM NaF , 40 mM β-glycerophosphate , 10 mM Na3VO4 , 10 ng/ml of protease inhibitors cocktail ( Sigma Aldrich , Oakville , Ontario , Canada ) . The protein concentration was determined by using the Bradford assay ( Bio-Rad , Mississauga , Canada ) . Whole-cell extracts ( 30 µg ) were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) in a 10%-acrylamide gel and transferred to a nitrocellulose membrane ( Bio-Rad , Mississauga , Canada ) . Membranes were blocked in 5% nonfat dried milk in Tris-buffered saline ( TBS ) plus 0 . 1% Tween 20 for 1 h at room temperature . Membranes were then probed overnight with antibodies against Stat 1 phosphorylated ( Tyr701 ) ( 1∶1000; Cell Signaling ) and non-phosphorylated forms ( p91 ) ( 1 µg/ml; Santa Cruz ) ; phosphorylated Jak1 ( Tyr 1022/1023 ) ( 1∶1000; Cell Signaling ) ; total Jak 1 ( 1 µg/ml Santa Cruz ) ; SeV ( 1∶10 , 000 ) ; SOCS1 ( 1 µg/ml; Zymed laboratories ) , IRF3 ( 1∶10 , 000; IBL , Japan ) in 5% bovine serum albumin and PBS at 4°C . Incubation mixtures were washed in TBS-0 . 05% Tween 20 five times for a total of 25 min . Following washes , the membrane was incubated with peroxidase-conjugated goat anti-rabbit or anti-mouse antibody ( KPL , Gaithersburg , MD ) at a dilution of 1∶5 , 000 for 1 h at room temperature . Following the incubation with the secondary antibody , membranes were washed again ( 5 times , 5 min each ) and then visualized with an enhanced chemiluminescence ( detection system as recommended by the manufacturer ( ECL; GE Healthcare Bio-Sciences Inc . , Oakville , Ontario , Canada ) . Native-PAGE was conducted as described [70] . Briefly , 10 g WCE in native sample buffer ( 62 . 5 mMTris-HCl , pH 6 . 8 , 15% glycerol , and bromophenol blue ) were resolved by electrophoresis on a 7 . 5% acrylamide gel ( without SDS ) pre-runned for 30 min at 40 mA using 25 mMTris and 192 mM glycine , pH 8 . 4 , with and without 1% deoxycholate in the cathode and anode chamber , respectively . After transferred into nitrocellulose membrane , IRF3 monomers and dimers were detected by immunoblot using an IRF3 anti-NES antibody ( 1∶10 , 000 , IBL , Japan ) . HEK293 cells ( 1×106 cells/60-mm dish ) were transiently transfected with equal amounts ( 5 µg ) of IRF3 and MYC-tagged SOCS1 expression plasmids by using calcium phosphate precipitation method . Cells were harvested 24 h post-transfection , washed with 1 X phosphate-buffered saline ( PBS ) , and lysed in a 1% Triton X-100 lysis buffer ( 20 mM Tris-HCl , pH 7 . 5 , 200 mM NaCl , 1% Triton X-100 , 10% glycerol , 40 mM β-glycerophosphate , 0 . 1% protease inhibitor cocktail , 1 mM phenylmethylsulfonyl fluoride , 1 mM Na3VO4 , 5 mM NaF , 1 mM dithiothreitol ) . Immunoprecipitations were performed by incubating WCE ( 300 µg ) with 1 µg of anti-MYC ( 9E10; Sigma-Aldrich , St . Louis , MO ) or 1 µg of antiserum directed against IRF3 ( rabbit polyclonal antibody , IBL , Japan ) coupled to 50 µl of A/G Plus-agarose beads ( Santa Cruz Biotechnology , Santa Cruz , CA ) overnight at 4°C with constant agitation . Immunocomplexes were washed at least 3 times in lysis buffer eluted by boiling beads in 5 volumes SDS-PAGE sample buffer . The proteins were fractioned on 10% SDS-PAGE , transferred to nitrocellulose membrane and analyzed by immunoblot assay using anti-MYC ( Sigma-Aldrich ) or anti-IRF3 ( IBL , Japan ) antibodies . Control and SOCS1-specific RNA interference sequences were described previously [71] , [72] . SOCS1 protein was knocked down using siSOCS ( 1 ) , siSOCS ( 2 ) or a pool of the two siRNAs ( siSOCS ( 1 ) + siSOCS ( 2 ) ) . siRNAs were pulsed into MT-2 cells in a 0 . 4-cm cuvette using a Gene Pulser II ( Bio-Rad Laboratories ) set at 0 . 25 kV and 0 . 95 µF . Cells were plated in six-well plates in complete medium , washed 4 and 12 h later and collected at 72 h post-transfection . RNA extinction efficiency was demonstrated by real time PCR and immunoblot assay . Data are presented as the mean ± standard error of the mean ( SEM ) . Statistical significance for comparison of gene expression was assessed by an unpaired Student's t test , with the expection of Figure 4 , panels D and E where a two-way ANOVA with Bonferroni post-test was used . Analyses were performed using Prism 5 software ( GraphPad ) . Statistical significance was evaluated using the following p values: p<0 . 05 ( * ) , p<0 . 01 ( ** ) or p<0 . 001 ( *** ) . A list of accession numbers for genes and proteins mention in this study are listed in Table S4 .
Infection with HTLV-1 leads to the development of Adult T cell Leukemia ( ATL ) or the neurological disorder HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) . Although the majority of HTLV-1–infected individuals remain asymptomatic carriers ( AC ) during their lifetime , 2–5% will develop either ATL or HAM/TSP . Using gene expression profiling of CD4+ T lymphocytes from HTLV-1 infected patients , we identified Suppressor of cytokine signaling 1 ( SOCS1 ) as being highly expressed in HAM/TSP and AC patients . SOCS1 expression positively correlated with the high HTLV-1 mRNA load that is characteristic of HAM/TSP patients . SOCS1 inhibited cellular antiviral signaling during HTLV-1 infection by degrading IRF3 , an essential transcription factor in the interferon pathway . Our study reveals a novel evasion mechanism utilized by HTLV-1 that leads to increased retroviral replication , without triggering the innate immune response .
[ "Abstract", "Introduction", "Results", "Discussion", "Materials", "and", "Methods" ]
[ "infectious", "diseases/infectious", "diseases", "of", "the", "nervous", "system", "virology/viral", "replication", "and", "gene", "regulation", "cell", "biology/cell", "signaling", "virology/immunodeficiency", "viruses", "virology/viruses", "and", "cancer", "virology/immune", "evasion", "virology/effects", "of", "virus", "infection", "on", "host", "gene", "expression", "virology/host", "antiviral", "responses" ]
2010
HTLV-1 Evades Type I Interferon Antiviral Signaling by Inducing the Suppressor of Cytokine Signaling 1 (SOCS1)