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Tuber melanosporum Vittad. is a multicellular ascomycete whose genome has been sequenced and studied2; however, not yet its PCD genomic tool-kit has been described or some of the possible roles that it may have in the differentiation of reproductive organs, tissues, and cells (the fruiting body FB, the fertile veins, and the spores).
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Importantly, however, during the past decade, evidence of PCD has been obtained in both the unicellular fungus, the yeast Saccharomyces cerevisiae1 and some filamentous fungi9, organisms consisting of networks of tubular and multinuclear cells (hyphae), which might or might not be subdivided by cell septa. In these systems, PCD is involved in different biological processes, including interactions with other systems, development, and aging10. Some of these processes exhibit typical characteristics of apoptosis, which is one specific type of PCD: externalization of phosphatidylserine, release of cytochrome c, involvement of cysteine proteases, the presence of mitochondrial-signaling pathways via homologs of the human apoptosis-inducing factor (AIF)11. Apoptotic-like cell death was first described in Saccharomyces cerevisiae over 10 years ago, but yeast apoptosis remained controversial, mainly due to its questionable physiological relevance and a lack of molecular and genomic data12,13.
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review
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Later studies, including the identification and analysis of homologs of apoptotic genes, confirmed the existence of apoptotic-like cell death in fungi14. These studies also showed the connection between apoptotic-like cell death and important biological processes such as development, aging, stress responses, and pathogenesis. The emerging role of apoptosis as a key regulator of fungal development suggests that it might be possible to develop new means of controlling fungal infections through manipulation of apoptosis.
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review
| 99.8 |
However, apoptosis has been described and studied in only a few fungal species, and although homologs of apoptotic genes can be identified in all fungal genomes, to date only a handful of genes have been functionally analyzed. Further research is needed to identify the molecular components and cellular mechanisms controlling apoptosis in fungi. Recognition of the importance of apoptosis for fungal development has led to increased interest and more intense research in recent years, which provide information on various aspects related to fungal apoptosis15–17.
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review
| 99.75 |
The aims of the present work are the investigations on: a) the PCD-related genetic tool-kit of T. melanosporum; b) the homologies of T. melanosporum PCD-related genes to those of other ascomycetes and species included the human one; c) the involvement of PCD in the differentiation of T. melanosporum reproductive system structures.
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From a search within T. melanosporum genome2 a set of 67 genes involved in PCD has been found (Table S1). In Table S1 the functions of the genes reported are described; some of them not yet annotated while the others, the majority, annotated. The genes found in T. melanosporum genome have roles in the different subroutines of PCD (apoptosis, autophagy, necrosis).
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In the Table S1 the identity percentages of homology of T. melanosporum PCD genes with those of other ascomycetes (Tuber borchii, Botritis cinerea, Aspergillus nidulans, Neurospora crassa, Magnaporthe grisea, Saccharomyces cerevisiae) and the human ones are presented. In Table S1 the maximal identities found among T. melanosporum PCD genes compared to the homologous of the other ascomycetes reported in Table S1 are shown.
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From the set of PCD involved genes shown in Table S1, 14 genes with the highest homologies were chosen in order to investigate their expressions by qPCR, in different developmental stages of T. melanosporum (Table 1) and for a preliminary gene expression investigation by DNA microarrays (Fig. 1). Most of those genes are involved in apoptosis, some in autophagy. Some of the genes code for PCD promoting proteins (PET9, DNM1, NMA111, aif1, Aifm2, NUC1, STE20, YCA1, CDC48), others for PCD inhibiting proteins (BXI1, FIS1, MMS2), and ASF1 that codes for a chaperone protein involved in nucleosomes assembly and disassembly.Table 1The fourteen genes having the roles reported in the Table were chosen among the genes involved in PCD present in the T. melanosporum genome.Gene nameProteinBiological function/processTuber gene models Tuber melanosporumBlast/identities Saccharomyces cerevisiaeReviewed Max identHumanBXI1Bax inhibitor 1Protein involved in apoptosis; described as containing a BCL-2 homology (BH3) domain or as a member of the BAX inhibitor family; reported to promote apoptosis under some conditions and to inhibit it in others; translocates to mitochondria under apoptosis-inducing conditions in a process involving Mir1p and Cor1pGSTUMT00004899001YNL305C (34%)LFG4_HUMAN (42.86%)LFG4_HUMAN (42.86%)PET9ADP, ATP carrier protein 2Catalyzes the exchange of ADP and ATP across the mitochondrial inner membraneGSTUMT00005644001 (TmelADT)YBL030C (79%)ADT_NEUCR (87.00%)ADT4_HUMAN (53.00%)FIS1Mitochondrial fission 1 proteinFis1 inhibits Dnm1- and Mdv1-mediated mitochondrial fission and cell death, indicating a prosurvival function for Fis1 and a proapoptotic function for Dnm1 and Mdv1 during cell deathGSTUMT00002150001YIL065C (45%)FIS1_TUBBO (96.00%)FIS1_HUMAN (34.46%)DNM1Dynamin-related protein DNM1Microtubule-associated force-producing protein that participates mitochondrial fissionGSTUMT00001624001YLL001W (67%)DNM1_YEAST (67.00%)DNM1L_HUMAN (52.01%)NMA111Proapoptotic serine protease NMA111Nuclear serine protease which mediates apoptosis through proteolysis of the apoptotic inhibitor BIR1GSTUMT00008284001YNL123W (51%)NM111_ASPOR (68.89%)HTRA2_HUMAN (23.42%)aif1Apoptosis-inducing factor 1Putative FAD-dependent oxidoreductase. Translocates from mitochondria to the nucleus under apoptotic conditions, where it degrades DNA and induces apoptosisGSTUMT00001651001AIF1_YEAST (24.81%)AIF1_SCHPO (41.67%)AIFM3_HUMAN (35.21%)Aifm2Apoptosis-inducing factor 2Probable oxidoreductase that acts as a caspase-independent mitochondrial effector of apoptotic cell deathGSTUMT00004637001AIF1_YEAST (24.23%)AIFM2_MOUSE (27.40%)AIFM2_HUMAN (26.84%)NUC1Mitochondrial nucleaseMajor mitochondrial nuclease, has roles in mitochondrial recombination, apoptosis and maintenance of polyploidyGSTUMT00010203001YJL208C (60%)NUC1_YEAST (60.00%)NUCG_HUMAN (39.32%)STE20Serine/threonine-protein kinase STE20MAP4K component of the MAPK pathway required for the mating pheromone response, haploid invasive growth and diploid pseudohyphal development. Upon exposure to an apoptotic stimulus, the histone deacetylase Hos3p deacetylates K11 and allows Ste20p to phosphorylate S10, required for apoptotic cell deathGSTUMT00006969001 (TmelSte20)YHL007C (49%)STE20_TALMA (56.38%)STK4_HUMAN (40.75%)YCA1Metacaspase-1Mediates cell death (apoptosis) triggered by oxygen stress, salt stress, or chronological aging. Promotes the removal of insoluble protein aggregates during normal growthGSTUMT00007513001YOR197W (57%)MCA1A_ASPTN (69.55%)CASP7_HUMAN (22.55%)CDC48Cell division control protein 48Involved in spindle disassembly, degradation of ubiquitinated proteins and protein export from the endoplasmic reticulum to the cytoplasmGSTUMT00010158001YDL126C (75%)CDC48_EMENI (86.40%)TERA_HUMAN (72.86%)ATG8Autophagy-related protein 8Ubiquitin-like modifier involved in cytoplasm to vacuole transport (Cvt) vesicles and autophagosomes formation. With ATG4, mediates the delivery of the vesicles and autophagosomes to the vacuole via the microtubule cytoskeletonGSTUMT00002234001 (TmelAUT7)YBL078C (78%)ATG8_ASPOR (97.46%)GBRL2_HUMAN (58.97%)MMS2Ubiquitin-conjugating enzyme spm2Has a role in the DNA error-free postreplication repair (PRR) pathway. Lacks catalytic activity by itself. The UBC13/MMS2 heterodimer catalyzes the synthesis of non-canonical poly-ubiquitin chains that are linked through ‘Lys-63’GSTUMT00003288001YGL087C (62%)MMS2_SCHPO (63.77%)UB2V1_HUMAN (47.48%)ASF1Histone chaperone ASF1Histone chaperone that facilitates histone deposition and histone exchange and removal during nucleosome assembly and disassemblyGSTUMT00007519001YJL115W (51.69%)ASF1_EMENI (63.70%)ASF1A_HUMAN (45.13%)The choice is based on the highest identities with PCD genes of other ascomycetes and organismsFig. 1Expression of 14 Tuber genes related to programmed cell death in various stages (III–VI) of fruit body development.Heatmap of log2 arbitrary expression values. Relative expression indexes (REI) were calculated for the dataset. For each gene, a mean expression level was calculated from the four samples, and the REI corresponds to the ratio between the expression level measured for a given sample and the mean reference. Log2 transformed data were subjected to MeV software for visualization. Each gene is represented by a row of colored boxes (corresponding to REI values) and a single column represents each stage
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Heatmap of log2 arbitrary expression values. Relative expression indexes (REI) were calculated for the dataset. For each gene, a mean expression level was calculated from the four samples, and the REI corresponds to the ratio between the expression level measured for a given sample and the mean reference. Log2 transformed data were subjected to MeV software for visualization. Each gene is represented by a row of colored boxes (corresponding to REI values) and a single column represents each stage
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Figure 2 shows the relative expressions of the 14 chosen genes, assuming as 1 (100%) their expressions at the T. melanosporum developmental stage 3, measured by qPCR.Fig. 2The expressions, as measured by qPCR, of the 14 chosen genes from T. melanosporum genome, relative to the expressions at the developmental stage 3.The expression at the developmental stage 3 is assumed as 1 (100%)
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The increases of CDC48 and STE20 expressions up to stages 5 and 6 are in line with the role that the proteins coded by these genes have in the control of cell division and the regulation of sexual differentiation, respectively, during the FB ripening, when mitosis and meiosis occur during asci maturation and sporogenesis. The expression of aif1, FIS1, and DNM1, which steadily decreases from the developmental stage 3 up to stage 6, as found by histochemical and transmission electron microscopy (TEM) investigations (terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), Fig. 3 and TEM, Fig. 4), signs of PCD, would suggest that TUNEL positivity, in some cells of the T. melanosporum FB, is not due to the apoptotic subroutine of PCD but another one (autophagy or necrosis). However a large genetic tool-kit related to PCD is present in the T. melanosporum genome; some of the PCD genes are homologous to PCD genes of the human genome and of species other than Ascomycetes, such as mouse, Aves, Amphibia, Zebrafish, Ascidiacea, Mollusca, etc. thus vertebrates and invertebrates (Figure S2). In Figure S2, the deduced AA sequences identities of PCD involved genes of T. melanosporum genome versus the human homologous sequences are reported. Figure S2 shows also the percentual identities of the deduced AA sequences of various invertebrates and vertebrates versus the human homologous sequences.Fig. 3In situ cell death detection by means of TUNEL reaction on cryostat sections of T. melanosporum fruit bodies at different developmental stages,Stage 3 (a–c); stage 4 (d–h); stage 5 (i–k); stage 6 (l–n). The three columns illustrate representative images of, respectively, Giemsa staining (for structural analysis and stage assessment), DAPI staining (for total nuclei visualization), and TUNEL reaction. a asci, as ascospores, p peridium, pa paraphyses, sv sterile vein. Bars = 50 µm in b, c, g, h, j, and k; 100 µm in e, f, l, m, and n; 200 µm in a, d, and iFig. 4TEM analysis of cell death in T. melanosporum (stage 4) fruiting bodies.a Toluidine blue-stained semithin section, showing the paraphyses region at the interface between sterile and fertile veins, where significant TUNEL positivity has been detected. b, c Examples of intact sterile hyphae, with normal nuclei; d sterile hyphae showing cytoplasmic emptying and vacuolization. e, f Altered nuclei with irregular condensed chromatin masses and dilated nuclear envelope lumen (arrow). a asci, n nuclei, pa paraphyses, sv sterile vein. Bars = 50 µm in a; 4 µm in b, d; 2 µm in c; 1 µm in e, f. TEM transmission electron microscopy
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Stage 3 (a–c); stage 4 (d–h); stage 5 (i–k); stage 6 (l–n). The three columns illustrate representative images of, respectively, Giemsa staining (for structural analysis and stage assessment), DAPI staining (for total nuclei visualization), and TUNEL reaction. a asci, as ascospores, p peridium, pa paraphyses, sv sterile vein. Bars = 50 µm in b, c, g, h, j, and k; 100 µm in e, f, l, m, and n; 200 µm in a, d, and i
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a Toluidine blue-stained semithin section, showing the paraphyses region at the interface between sterile and fertile veins, where significant TUNEL positivity has been detected. b, c Examples of intact sterile hyphae, with normal nuclei; d sterile hyphae showing cytoplasmic emptying and vacuolization. e, f Altered nuclei with irregular condensed chromatin masses and dilated nuclear envelope lumen (arrow). a asci, n nuclei, pa paraphyses, sv sterile vein. Bars = 50 µm in a; 4 µm in b, d; 2 µm in c; 1 µm in e, f. TEM transmission electron microscopy
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The key players of T. melanosporum PCD, the yeast, and human homologs and the roles they have in PCD subroutines are reported in Fig. 5. It is evident from the Fig. 5 that T. melanosporum has the genetic tool-kit to perform PCD. Figure 3 shows the TUNEL assay positivity of T. melanosporum FBs at different developmental stages.Fig. 5 40 T. melanosporum PCD-related genes, with their human and yeast homologs, and the roles they have in programmed cell death.
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PCD phenomena in T. melanosporum FBs at different developmental stages were assessed by means of the TUNEL reaction, which can reveal the presence of nuclei with fragmented DNA through terminal deoxynucleotidyl transferase (TdT)-mediated labeling of free 3′-OH extremities of DNA breaks. The same sections used for the TUNEL reaction were subsequently stained with 4′,6-diamidino-2- phenylindole (DAPI) to visualize all of the nuclei and so evaluate the extension of the cell death.
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Stage 1 (“hyphal stage”) and 2 (“peridial stage”) FBs did not exhibit any significant positivity to the TUNEL reaction (not shown). In stage 3 (“veined stage”) FBs, on the other hand, some TUNEL-positive nuclei could be detected, particularly at the level of the interface between developing sterile and fertile veins, where specialized hyphae called paraphyses begin to appear (Fig. 3a–c). At stage 4 (“ascal stage”) more numerous TUNEL-positive nuclei were visible in the paraphyses (Fig. 3d–f), while (some) TUNEL positivity could be seen also in fertile veins and in some developing asci (Fig. 3g, h). In stage 5 (“sporal stage”) FBs TUNEL-positive nuclei were present both in sterile and fertile veins; in these latter, more specifically, they were particularly evident in some asci-surrounding hyphae (Fig. 3i–k) and, to some extent, at the level of the hypothecium (not shown). Finally, numerous TUNEL-positive nuclei were observed in stage 6 (“pigmented stage”) FBs, mostly at the interface between fertile veins and remnants of sterile veins (Fig. 3l–n).
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For TEM analysis, toluidine blue-stained semithin sections were preliminarily observed for general morphological examination and as survey sections to localize the areas of the samples for ultrathin sectioning. We focused in particular on the region at the interface between sterile and fertile veins, where paraphyses are organized in a palisade delimiting the sterile vein and where significant TUNEL positivity had been detected (Fig. 4a); in this zone we could observe the presence of altered nuclei (Fig. 4d–f), with irregular condensed chromatin masses reminding those found sometimes in (animal) apoptotic cells, within sterile hyphae showing cytoplasmic emptying and vacuolization (Fig. 4d). Another remarkable feature observed in these altered nuclei was the recurrent presence of a (generally) single, fairly large dilation of the nuclear envelope lumen (Fig. 4e, f).
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The expression during FB development of the 67 genes, related to PCD, found in the T. melanosporum genome was preliminarily investigated by DNA microarrays (Table S2, Figure S1 and Fig. 1). Fourteen PCD-related genes, on the base of the highest identities to the homologs of other species, were chosen from the 67 PCD-related genes found and their expression tested too by qPCR to strengthen the microarrays data.
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The TUNEL reaction positivity and TEM support that PCD occurs too in T. melanosporum as well as in other ascomycetes20. The autophagy subroutine of PCD in the ascomycete S. cerevisiae is associated with differentiation, development (e.g. reproduction and spore germination), and stress responses21. Several autophagy-related genes in addition to ATG8, whose expression has been investigated both by qPCR and microarray, occur and are expressed during T. melanosporum development and differentiation (Table S2, Figure S1 and Fig. 1). The involvement of autophagy in stress responses, for example, to reactive oxygen species (ROS)-generating processes, such as melanin synthesis might be of some interest in the case of T. melanosporum FB development.
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Melanin synthesis is important to fungal development and differentiation19,22; however, the processes potentially genotoxic and cytotoxic due to the generation of semiquinones, quinones, and ROS by the oxidation of polyphenols by tyrosinase (EC 1.14.18.1)23,24; ROS are known as trigger of PCD25. During T. melanosporum development tyrosinase activity steadily increases from the developmental stage 3 to stage 526 so that it is expected an increase of ROS and genotoxic species generation within the FBs, in fact evidences of PCD appear at the developmental stage 5.
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In conclusion the aims of this work have been addressed: (a) T. melanosporum has a genomic tool-kit related to PCD; (b) the T. melanosporum PCD-related genes are homologs to those of other ascomycetes and species included the human one; (c) PCD is involved in the FB development when sterile veins show TUNEL positivity and makes space for the fertile veins (Fig. 4) and also TUNEL positivity appears in some spores. The PCD occurring in the spores of ascomycetes has been previously described920; however, its role has not yet been made clear; a possible role might be the elimination of spores with damaged genome; may be single cell genomics might address this point and help to a better understanding of the reproductive differentiation of a gastronomic delicacy such as the truffle T. melanosporum27.
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Samples of T. melanosporum FBs were collected at different developmental stages in the field near the city of L’Aquila (Italy), using the methods described by Pacioni et al.28 in addition to the traditional use of trained dogs. According to the season climatic conditions, in the years of this research, specimen of stage 3 were collected between July and August, of stage 4 in August–September, of stage 5 in September–early November, and of stage 6 in late November to March (four biological replicates for each stage). All of the ascocarps were analyzed morphologically and microscopically and classified by maturation stage according to the criteria defined by Zarivi et al.29. For structural analysis and maturation stage assessment, 8–10 µm cryostat sections of each FB were observed after Giemsa staining (1 min).
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Cryostat sections (8–10 µm thick) of T. melanosporum FBs at different developmental stages were mounted on poly-l-lysine-coated microscope slides and fixed with 4% (w/v) paraformaldehyde in phosphate-buffered saline (PBS) for 20 min at room temperature (RT); then they were washed for 20 min with PBS, dehydrated 2 min in absolute ethanol, and stored at −20 °C until use. Before performing TUNEL reaction, cryopreserved sections were incubated in permeabilization solution (0.1% Triton X-100 in 0.1% Na-citrate) for 2 min at 4 °C. After washing with PBS, the sections were incubated in a humid chamber with complete TUNEL reaction mixture, prepared immediately before use according to the manufacturer’s instructions (“In situ cell death detection kit”; Roche Diagnostics, Mannheim, Germany) for 1 h at 37 °C in the dark. Then they were rinsed three times in PBS and mounted with Vectashield mounting medium (Vector Laboratories, Inc., Burlingame CA, USA) containing DAPI. Positive control sections were permeabilized and treated with DNase I 500 U/ml in 50 mM Tris-HCl buffer, pH 7.5, 10 mM MgCl2, 1 mg/ml bovine serum albumin, for 10 min at RT, before the TUNEL reaction. Negative control sections, after permeabilization, were incubated in label solution (without terminal transferase). Observations and photography were performed with a Zeiss Axio Imager.A2 (Jena, Germany) fluorescence microscope (Microscopy Center, University of L’Aquila, Italy) equipped for epi-illumination with appropriate filters.
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| 99.94 |
For ultrastructural analysis, FB samples were embedded in Durcupan ACM epoxy resin, as follows: the samples were pre-fixed with 3% glutaraldehyde in 0.1 M cacodilate buffer, pH 7.2, for 3 h at room temperature; after washing in the same buffer, they were post-fixed with buffered 1% osmium tetroxide for 2 h at 4 °C, dehydrated in an ethanol series, and embedded in the resin.
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| 99.94 |
Semithin (1 μm) sections were cut with a glass knife using a Sorvall Porter-Blum MT2-B ultramicrotome and stained with 1% toluidine blue in 1% Na-borate. Ultrathin sections (70 nm thick) were stained with 5% uranyl acetate in 70% ethanol and lead citrate (Reynolds) and observed using a Philips CM100 transmission electron microscope (Microscopy Center, University of L’Aquila, Italy).
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The putative genes encoding proteins involved in PCD were identified at the TuberDB Tuber genome database (http://mycor.nancy.inra.fr/IMGC/TuberGenome/). Searches were also performed using several protein databases (e.g., NPS@:BLAST HomologySearch: https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_blast.html; Interpro: https://www.ebi.ac.uk/interpro/; Pfam: http://www.sanger.ac.uk/Software/Pfam/; Prosite: http://www.expasy.org/prosite/; Uniprot: http://www.pir.uniprot.org/; Superfamily: http://supfam.cs.bris.ac.uk/SUPERFAMILY/), as well as genome and EST databases (NCBI: http://www.ncbi.nlm.nih.gov/; Yeast database: http://ycelldeath.com/) were searched for PCD-related sequences in order to probe the Tuber genome database using BLAST algorithms. The detected putative homologs were characterized on the basis of the conserved domains, identities and E-values. Further information about the name and structure of the genes was obtained using BLASTP, which is available on NCBI (http://www.ncbi.nlm.nih.gov/) and EMBL (http://www.ebi.ac.uk/Tools/blastall/index.html). Each validated homolog was also used for a BLAST search at http://mycor.nancy.inra.fr/IMGC/TuberGenome/blast.html, which has a database with five reference Ascomycota: Saccharomyces cerevisiae, Neurospora crassa Shear &B.O. Dodge, Magnaporthe grisea (T.T.Hebert)M.E.Barr, Aspergillus nidulans (Eidam)G.Winter and Botrytis cinerea Pers., and at https://genome.jgi.doe.gov/pages/blast-query.jsf?db=Tubbor1 which has a database with Tuber borchii Vittad genome.
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The consensus sequences were used for comparison with genomic sequences, to reveal the exon–intron structure. To facilitate the real-time PCR analysis of all the investigated genes under the same reaction conditions, primers were designed using Primer Express 3.0 software (PE Applied Biosystems, USA) under default parameters. The primers, wherever possible, were designed spanning an intron to detect any genomic DNA contamination. For information on primer sequences see Table 2Table 2Primers used in this studyNameAccession numberPrimer namePrimer sequence 5'–3'; Tm (°C).Product (bp)(%) PCR efficiency18S rRNAAM748736.118SF: 5′-CCAATGGAAGTTTGAGGCAATAA-3′ (53.8), R: 5′-CCAATGGTGATGAACTCGTTGA-3′ (55.3)10095.03Elongation factor 1-alphaGSTUMT00000021001TEFAF: 5′-AAGGGTGCCGAGTCTTTCAA-3′ (56.7), R: 5′-TATGAGCGGTGTGGCAGTCA-3′ (58.8)10094.57Glucose-6-phosphate dehydrogenaseGSTUMT00008696001G6PDF: 5′-CGCGATGAGAAGGTCAGAGTT-3′ (56.9), R: 5′-CAGGCTTGCTGCCATCAAG-3′ (57.0)10097.31Apoptosis-inducing factor 1GSTUMT00001651001AIF1F: 5′-AGCGACAATCAGAGCTGGTAAAC-3′ (60.6), R: 5′-CCCAGAGCCACCTCCAACTA-3′ (61.4)10099.55Apoptosis-inducing factor 2GSTUMT00004637001AIF2F: 5′-GGGCCGCGAAGAAGATTGTC-3′ (61.4), R: 5′-CGGTACCTGTGGCAGGAGTT-3′(61.4)13798.16Autophagy-related protein 8GSTUMT00002234001ATG8F: 5′-TATGCAGACCGTATTCCCAGTTATTTG-3′ (61.9), R: 5′-AGTCAAGTCCGCAGGAACCA-3′ (59.4)9695.44Mitochondrial nucleaseGSTUMT00010203001EndoGF: 5′-GGGGATCGGCATCGGAGCA-3′ (63.1), R: 5′-TGCGGCGGGGACCTGGT-3′ (62.4)11799.42Metacaspase-1, Ca2+-dependent cysteine proteaseGSTUMT00007513001YCA1F: 5′-CAAAGATGCACAACCCAATGA-3′ (55.9), R: 5′-TCGTACCCATCGCCTTATCAC- 3′ (59.8)9698.16Proapoptotic serine protease NMA111GSTUMT00008284001NMA111F: 5′-GTGGATTATTGAGTCCCTTGACAA-3′ (59.3), R: 5′-AGGTGTGCATGGTGTGAAGGT-3′ (59.8)13792.39Cell division control protein 48GSTUMT00010158001CDC48F: 5′-CCGGATTAGACTTGGCGATGT-3′ (59.8), R: 5′-TCCTTCAACAGTGTCTGCAATAGG-3′ (61.0)10097.63Bax Inhibitor 1GSTUMT00004899001BAX1F: 5′-TGTTCGATACGCAGATGATTATGA-3′ (57.6), R: 5′-CCTCAGGATAGCAAGGAACAAGTTA-3′ (61.3)10796.06Histone chaperone ASF1GSTUMT00007519001ASF1F: 5′-TTTGCCATCAAGTGGGACTCT-3′ (57.9), R: 5′-CTCCGTAATTGTCGGCATCA-3′ (57.3)10096.06Serine/threonine-protein kinase STE20GSTUMT00006969001STE20F: 5′-GCTCGCCAACGCTTTTTCT-3′ (56.7), R: 5′-TGAGTATTCCGATCACCAGCAA-3′ (58.4)10896.84Mitochondrial fission 1 proteinGSTUMT00002150001FIS1F: 5′-TTGGCGTCCAGACTAAGTTCAA-3′ (58.4), R: 5′-CGGAAGATATCAGTCAATAACCTAACC-3′ (61.9)10099.25ADP, ATP carrier protein 2GSTUMT00005644001PET9F: 5′-AGAACAATCTACTTTCCTCGTTGACTT-3′ (60.4), R: 5′-GATAAGGAGCTTGATACGCTCAATG-3′ (61.3)10097.63Dynamin-related proteinGSTUMT00001624001DNM1F: 5′-AGCTGCAGGATCTTGTCTTTAATACTATT-3′ (61.0), R: 5′-ACCGAGGATTTCCCGCTAGA-3′ (59.4)10099.46Ubiquitin-conjugating enzyme spm2GSTUMT00003288001SPM2F: 5′-CGAGAACCGCATTTACAGTTTG-3′ (58.4), R: 5′-AGGTGCCTTAACGCTGTACCA-3′ (57.6)10095.30Primer sequences, accession numbers, amplicon sizes and PCR efficiencies are indicated
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Total RNA were extracted from stages 3–6 (100 mg each) using TRIzol_Reagent with the PureLink_RNA Mini Kit (Ambion by Life Technologies Carlsbad, CA, USA). RNase-free mortars and pestles were used in combination with liquid nitrogen to disrupt frozen tissue samples into a powder. One hundred milligrams of powdered tissue samples in 1 mL TRIzol Reagent were homogenized by using a mortar and pestle26, and then through three cycles of pestle strokes at 200 riv/min in a potter Helvehjem homogenizer. Samples were centrifuged for 10 min at 12,000 g and the supernatant was removed and incubated for 3 min at room temperature. Then 0.2 mL chloroform per 1 mL TRIzol Reagent used were added, the tubes were vigorously shaken by hand for 15 s, incubated at room temperature for 3 min, and were centrifuged at 12,000 g for 15 min at 4 °C. The upper colorless phase containing the RNA was transferred to a new Rnase-free tube, adding an equal volume 100% ethanol and vortexing to mix well. Binding, washing, and elution steps were performed using the PureLink_RNA Mini Kit according to the manufacturer’s instructions (Ambion by Life Technologies Carlsbad, CA, USA). Then, the RNA was treated with Recombinant Rnase-free Dnase I from bovine pancreas (Roche Diagnostics, Indianapolis, USA) according to the manufacturer’s instructions. Absence of DNA was checked by comparing cDNA samples with RNA samples which were not reverse transcribed (minus RT control). The purity of all RNA samples was assessed at absorbance ratios of A260/A280 and A260/A230 using a Nanodrop 2000 spectrophotometer (Thermo Scientific, Waltham, WA) and the integrity of the RNA was immediately checked using 1.2% agarose gel electrophoresis (1.3 µg samples). RNA concentration was calculated based on absorbance values at 260 nm, and RNA samples were stored at −80 °C until use.
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One microgram of total RNA from each sample was reverse transcribed using the SuperScript III First-Strand Synthesis SuperMix for qRT-PCR (Invitrogen by Life Technologies, Carlsbad, CA, USA), following the manufacturer’s instructions. Quantitative PCR was performed with the SYBR® GreenER™ qPCR SuperMix for ABI PRISM®, which is a ready-to-use cocktail containing all components (including ROX Reference Dye at a final concentration of 500 nM), except primers and template. All the PCRs were performed under following conditions: 2 min at 50 °C, 10 min at 95 °C, and 40 cycles of 15 s at 95 °C and 1 min at 60 °C in 96-well optical reaction plates (Applied Biosystems, USA). The specificity of the qRT-PCR reactions was monitored through melting curve analysis (60–95 °C), after 40 cycles, using SDS software (version 1.4; Applied Biosystems), all PCR assays produced a single amplicon of the expected size. The gene-specific amplification efficiency was calculated by linear regression analysis of the standard curve. The sequences of T. melanosporum 18S rRNA, Elongation factor 1-alpha, glucose-6-phosphate dehydrogenase, employed as an internal standard29, and the sequences of the specific primers used to analyze the expression of the selected genes involved in the metabolism apoptosis, are provided in Supplementary Table 1. Each sample was tested in triplicate by quantitative PCR, and the samples obtained from at least four independent experiments were used to calculate the means and standard error; the results were considered to be significant if P < 0.05.
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Total RNA was isolated from Stage 3–6 FBs. Double-stranded cDNA was synthesized and amplified using the SMART PCR cDNA Synthesis Kit (Ozyme, Saint-Quentin-en-Yvelines, France), according to the manufacturer’s instructions, and used for hybridizations to NimbleGen oligoarrays2. Single dye labeling of samples, hybridization procedures, and data acquisition were performed at the NimbleGen facilities (NimbleGen Systems, Reykjavik, Iceland) following their standard protocol. The T. melanosporum custom-exon expression array (GPL8982) manufactured by Roche NimbleGen Systems (Madison, WI, USA) contained five independent, non-identical, 60-merprobes per gene model coding sequence. Included in the oligoarray were 7496 annotated protein-coding gene models, 5736 TE sequences, 3913 random 60-mer control probes, and labeling controls. For 1876 gene models, technical duplicates were included in the array.
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Microarray probe intensities were quantile normalized across chips and average expression levels were calculated for each gene from the independent probes on the array and were used for further analyses30. Raw array data were filtered for non-specific probes (a probe was considered as non-specific if it shared more than 90% homology with a gene model other than the gene model it was made for) and renormalized using the ARRAYSTAR software (DNASTAR, Madison, WI, USA). For 1015 gene models, no reliable probes remained. Expression values are arbitrary units from 1 to 57,000.
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Climate warming is expected to alter distribution patterns of fishes, with temperatures in some systems already approaching the upper thermal tolerance of endemic species (Caissie, 2006). In salmonids, warming water temperatures affects migration (Crossin et al., 2008), smoltification (McCormick et al., 1999), growth and survival (Swansburg et al., 2002). The Miramichi River, located in eastern Canada, is a prominent Atlantic salmon (Salmo salar) river (DFO, 2013) where maximum summer temperatures can reach 27–30°C (Caissie et al., 2014), well beyond the range for optimal growth in juveniles (~15–20°C; Jobling, 1981; Elliott and Hurley, 1997; Jonsson et al., 2001; Elliott and Elliott, 2010). The upper threshold for normal feeding behavior (i.e. 22–24°C; Breau et al., 2011) can be surpassed for as many as 62 days during the spring/summer (Caissie et al., 2012). Peak water temperatures typically occur in conjunction with diel fluctuations of ≤9°C in summer months (our unpublished work). Thus, the Miramichi River is an ideal system for understanding the effects of climate warming on salmon physiology. An appreciation of a fish's physiological capacity to cope with climate-driven environmental stress is emerging as a powerful approach in conservation and management as has been demonstrated for Pacific salmon (Cooke et al., 2012, Muñoz et al., 2014).
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Natural diel thermal cycles impact thermal tolerance (Wehrly et al., 2007), bioenergetics (Beauregard et al., 2013; Eldridge et al., 2015), and metabolic status (Oligny-Hébert et al., 2015) of fishes. However, largely due to practical issues of temperature control in the laboratory, comparatively few studies investigate how temperature cycling, compared to stable acclimation temperatures, affect fish biology (see Threader and Houston, 1983; Houston and Gingras-Bedard, 1994; Mesa et al., 2002; Narum et al., 2013; Tunnah et al., 2017 as examples). Given that water temperatures in traditionally productive Atlantic salmon habitat, such as the Miramichi River, are increasing beyond the presumed thermal limit for this species (Elliott and Elliott, 1995), we were interested in whether the nature of the thermal cycle differentially influenced physiology. Specific to current federal (DFO) regulations whereby river closures occur when water temperature is ≥20°C for two consecutive nights (DFO, 2012), we investigated the effects of warming temperature cycles with distinct thermal minimums on the physiological response (i.e. thermal tolerance) of juvenile salmon. Although federal guidelines are designed primarily with mature life stages in mind, juveniles were used as a readily accessible and abundant proxy for their adult counterpart. The link between adult and juvenile fish physiology has been defined in many fishes (see Rodnick et al., 2004; Pörtner et al., 2008; Fowler et al., 2009; Morita et al., 2010), and although a more thermally tolerant life stage, juveniles provide insight into the physiological capacity of salmonids to withstand extreme events.
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Our main objective was to determine how distinct, natural thermal variation, representative of summer high temperature events, affected the thermal tolerance and physiology of wild juvenile Atlantic salmon, with the goal of informing conservation and management efforts. To this end, we acclimated fish to four thermal cycles, representative of real-world conditions but with differing minimum nighttime temperatures (16°C, 18°C, 20°C, 22°C) and diel temperature fluctuations (e.g. Δ5°C–Δ9°C). In each cycling condition, we measured critical thermal maximum (CTMax) as a proxy for acute thermal tolerance (Beitinger et al., 2000), recognizing that CTMax is influenced by acclimation temperature (e.g. Fangue et al., 2006). We also measured indicators of physiological (HSP70, ubiquitin) and energetic (lactate, glycogen) stress. We hypothesized that nighttime temperature throughout a thermal event dictates physiological limits. If supported, then we predicted that fish exposed to conditions with the highest nighttime temperature will have reduced acute thermal tolerance, and will experience enhanced metabolic and cellular stress compared to those exposed to cooler nighttime temperatures.
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Wild Atlantic salmon parr (N = 320; fork length = 6.1–10.4 cm; weight = 1.9–12 g) were collected on 16 June 2013, using a Smith-Root LR-24 backpack electrofisher from the Cains River (N46°25′59. 5; W066°01′29. 1—N46°26′05. 0; W066°01′10. 8 ± 15 m), a tributary of the Southwest Miramichi River. Fish were transported to the Harold Crabtree Aquatic Facility at Mount Allison University, NB, Canada and placed in a 750 L (circular fiberglass) recirculation holding tank at 15.00 ± 0.03°C. Fish were fed a mixture of dehydrated krill and commercial pellet feed (Corey Nutrition Company) twice daily until satiation. Water temperature was maintained until parr were weaned to feed exclusively on pellets (~10 days). Fish were subsequently fed once daily to satiation and exposed to a fluctuating ‘acclimation regime’ with nighttime minimum and daytime maximum temperatures (Tmin and Tmax) of 16 and 21 ± 0.2°C, respectively (mean ± SD; 12 h warming: 12 h cooling) with a natural photoperiod (~16 h light:8 h dark). Water temperature was monitored using an iBCod temperature logger (±1°C, 15 min interval, Alpha Mach Inc.) and dissolved oxygen (DO) was measured daily (7.5–10 mg L−1; YSI Pro 20, Xylem Inc.).
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A significant heat event occurred in the Little Southwest Miramichi River (LSWM) in early July 2010 (Fig. 1A). Maximum daytime water temperatures during the July 6–8 event ranged from 28.0°C to 30.7°C (mean: 29.3 ± 0.5°C); nighttime temperatures ranged from 20.7°C to 24.5°C (mean: 22.8 ± 0.9°C). Such temperatures are known to alter metabolism in juvenile Atlantic salmon (Breau et al., 2011). To address our objectives, we chose to model this particular heat event for our experimental treatments. We established an acclimation regime based on the mean diel Tmax and Tmin of the 2 weeks prior to the event (16–21°C). To minimize thermal stress mortality, Tmax was set at 27°C for all treatments, just below the upper incipient lethal limit (7-day survival: 27.8°C; Elliott, 1991). Three temperature treatments were established within the limits of ΔT measured in the LSWM River in 2010 (Fig. 1B). We established minimum (i.e. nighttime) water temperatures as: (i) above the current legislated diel minimum temperature that determines river closure (≥20°C; DFO, 2012), 22–27°C; (ii) at the threshold, 20–27°C; and (iii) within the optimum range for growth and survival, 18–27°C. In order to subject parr to 27°C without exceeding the maximum natural diel ΔT (9°C) measured in the LSWM, an intermediate (‘ramp’) day was placed between the 16–21°C-acclimation regime and the temperature treatments. Temperatures on this day reached a maximum of 23°C and minimum of 18°C (Fig. 1B). Figure 1:(A) Thermal profile of the Little Southwest Miramichi (LSWM) River throughout early July 2010. A known thermal event occurred July 6–8. (B) Thermal profile of the LSWM River overlaid with experimental treatments. Details provided in text of Methods.
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Once in experimental tanks, fish remained at 16–21°C for a 5-day acclimation period. All fish were then subjected to a 1-day intermediate exposure (Day-6; 18–23°C) prior to exposure to 3 days of heat cycling (Day 7–9; Tmax = 27°C in all treatments) with treatment-specific thermal minima. A fourth treatment group was maintained at 16–21°C throughout the experimental procedure. We ran two experimental trials, each lasting 9.5 days (Trial 1: 16–21°C and 22–27°C treatments, July 13–22; Trial 2: 18–27°C and 20–27°C treatments, July 22–31). Each thermal treatment was assigned a bank of three 300 L circular fiberglass tanks with each bank connected to separate recirculation systems. Parr were randomly selected from the holding tank (at 16–21°C) and transferred to one of the two tank banks (i.e. total N = 6 tanks). Fish were distributed equally among all experimental tanks (i.e. 108 fish per trial; ~36 fish per tank). For each sampling event, nine fish were sampled from a single tank within a bank. Sampling regimens were scheduled such that no tank was subject to consecutive samplings in order to eliminate recurring stress from repeated sampling within short time periods (minimum time between sampling a particular tank = 48 h). Fish were not fed 24 h prior to sampling.
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Fish were sampled throughout the diel temperature cycle according to the following schedule: (i) Tmin following the ‘intermediate’ temperature increase (t = 48 h); (ii) Tmax, the first day of heat cycling (t = 60 h); (iii) the first Tmin throughout heat cycle (16°C, 18°C, 20°C or 22°C, depending on treatment, t = 72 h); (iv) Tmax, the third day of heat cycling (t = 108 h); and (v) Tmin, the third day of heat cycling (t = 120 h, Fig. 1B). These sampling time points were chosen to establish the physiological condition prior to heat exposure, the implications of 1 day of heat cycling, and the potential cumulative effect of 3 days of cycling. This 5-timepoint sampling regime was performed on all treatment groups. However, to address the potential effect of ‘trial’ on our results, two additional sampling time points (t = 12 h and t = 24 h) were established in one treatment group in each of the two trials (16–21°C for Trial 1 and 18–27°C for Trial 2), prior to the heat cycle. This additional sampling allowed us to further address the incipient, ‘pre-thermal stress’ condition.
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Fish were anaesthetized with a buffered ethyl 3-aminobenzoate methanesulfonate (MS-222; Sigma-Aldrich) solution with supplemental aeration. Once anesthetized, mass and fork length were measured, and blood extracted from the caudal artery. Whole blood (WB) lactate and glucose were measured using a Lactate Pro™ Portable Blood Lactate Analyzer and a OneTouch® Ultra 2 Meter (Gallant et al., 2017). Environmental stressors are known to alter the blood chemistry of fish. Blood glucose levels rise to supply ATP and fuel activity if the situation becomes critical. Similarly, blood lactate is a byproduct of anaerobic metabolism, and an increase in this metabolite indicates a switch to anaerobic ATP production suggesting aerobic energy stores are diminished. Parr were terminated by a swift blow to the head followed by severance of the spinal cord. Liver was dissected, immediately frozen in liquid nitrogen and stored at −80°C until processing. Blood samples were centrifuged at 5000 rpm for 3 min and 13°C to separate blood constituents. White blood cells and plasma were discarded while red blood cells (RBC) were flash frozen in liquid nitrogen and stored at −80°C.
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CTMax tests were performed on 9–11 salmon parr at each of three Tmin time points (between 04:00 and 09:00); to establish an initial pre-thermal stress value (24 h), the effect of a singular thermal cycle (60 h), and of multiple heat cycles (120 h; Fig. 1B). Prior to testing, fish were transported to a plastic CTMax experimental chamber (40 × 13.5 × 11 cm) with a clear Plexiglas® lid. Chambers contained an aerated water flow of 4 L min−1 and had an initial water temperature matching that of the experimental procedure. Once the fish was in the chamber, water temperature was increased acutely at a rate 0.32 ± 0.002°C min−1 (mean ± SEM; Becker and Genoway, 1979) until fish lost equilibrium. DO and temperature were measured at 1-min intervals; DO saturation remained >72% in all trials.
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In addition to protocol described above, a separate group of 10 parr were isolated at the time of field collection and maintained at a constant 16°C for 1 week prior to being measured for fork length (±1 mm), wet weight (±0.1 g) and individually tagged with visible implant elastomer (Northwest Marine Technology Inc.). Fish recovered for 60 h prior to CTMax testing on 4 July 2013 at 06:00 h. After testing, fish recovered at 16°C for 5 days prior to acclimation to 16–21°C for 36 days. The test was then repeated under the same conditions to evaluate the influence of the thermal cycle on CTMax.
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Protocols for the liver glycogen extraction (Clow et al., 2004) and assay were modified from Bergmeyer et al. (1974). Hydrolysates were frozen at −80°C until analyzed for glucose content. The glucose assay was modified to use 25 µl of sample, diluted 1:7 in assay media (Clow et al., 2004) and added to each well of a microtiter plate. Twenty-five microlitres of 100 µl/ml G-6-PDH was added to each well to eliminate any endogenous G-6-P that remained in solution. The plate was read on a VERSAmax Tunable Microplate Reader (Molecular Devices Corporation) at 340 nm until absorbance stabilized. Hexokinase (25 µl) was then added and the absorbance was read after 15–25 min.
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The induction of heat shock protein 70 (HSP70) may be considered an ecologically relevant indicator of thermal stress for Atlantic salmon (Lund et al. 2002; Chadwick et al., 2015; Tunnah et al., 2017). Soluble protein in liver and RBC were extracted as in Tunnah et al. (2017) and LeBlanc et al. (2011), respectively, and assayed using the Lowry-based DC protein assay kit (Bio-Rad, Mississauga, ON, Canada). Standards (bovine serum albumin; Bio-Rad) and samples were diluted in protein extraction buffer or salmon saline, respectively, and absorbance read at 750 nm using a SpectraMax M5 plate reader and SoftMax Pro software. Samples were prepared using 15 µg soluble protein and western blots performed as in Kolhatkar et al. (2014). We used a rabbit anti-salmonid HSP70 primary antibody (AgriSera, AS05061; 1:50 000 dilution in blocking buffer) and a goat anti-rabbit secondary (Enzo Life Sciences; SAB-300 1:50 000) for immunodetection. This antibody is specific for the inducible form of HSP70 and does not cross-react with the constitutive isoform in salmonids (Rendell et al., 2006; Fowler et al., 2009; Tunnah et al., 2017). Protein bands were visualized using an ECL Advance Chemiluminescent Western Blotting Detection kit (Amersham Pharmacia Biotech) imaged using a Versadoc Imaging System and Quantity One software (Bio-Rad). Relative band density was quantified using Image Lab software (Bio-Rad) and calculated from the standard curve on each blot.
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We used ubiquitin (Ub) as an indirect measure of protein damage/turnover. Soluble protein samples of known concentration were diluted and 5 µg of protein was dotted on a nitrocellulose membrane as in MacLellan et al. (2015). To ensure equal protein loading, a Ponceau-S stain (Sigma-Aldrich) was applied to each membrane after imaging, according to manufacturer's instructions.
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Data were analyzed using R statistical software (R Development Core Team, 2016). Prior to analyses, data were divided into two sections: t = 12 h and t = 24 h to assess the effect of ‘trial’ (i.e. temperature regime shared by all experimental groups), and t = 48 h through t = 120 h to test experimental effects of temperature and time. In the case of glycogen, WB glucose, WB lactate, HSP70 (liver & RBC) and liver Ub, data were log-transformed to meet the assumptions of normality and homoscedasticity. A linear model two-way ANOVA was conducted to compare the main effects of independent variables (thermal cycle and time point) and the inherent interaction effect on indicators of physiological and energetic stress. In case of a significant interaction between sampling time point and thermal cycle, a one-way ANOVA was used to discern differences between temperature treatments at individual time points. Pre-thermal stress sampling time points were treated in a similar fashion with the exception of the CTMax data, as only one pre-thermal stress time point occurred. In this instance, a linear one-way ANOVA was used to test for the effect of trial. When appropriate, a subsequent Tukey post-hoc test was used. In all cases, α = 0.05 and values were expressed as mean ± SEM. Although our study does not use a repeated measures design, line graphs are presented for a clearer view of trends within the data.
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Pre-thermal stress sampling time points differed in three of the variables analyzed (Table 1). There was a significant effect of sampling time (F1, 1 = 8.45, P = 0.006) and thermal cycle (F1, 1 = 6.70, P = 0.014) with no significant interaction (F1, 1 = 1.23, P = 0.276) in WB glucose. Significant differences occurred in incipient pre-exposure values for liver HSP70, where there was an effect of sampling time (F1, 1 = 27.62, P = <0.001) and thermal cycle (F1, 1 = 8.28, P = 0.008), but not the interaction (F1, 1 = 0.28, P = 0.601). Significant differences were also observed in RBC HSP70 where there was an effect of sampling time (F1, 1 = 16.88, P = < 0.001) and thermal cycle (F1, 1 = 182.09, P = <0.001), but not the interaction (F1, 1 = 0.06, P = 0.11; Table 1). No significant effects of sampling time or thermal cycle were observed in CTMax, WB lactate, liver Ub or RBC Ub (see Table 1). Table 1:Two-way ANOVA performed on physiological variables of juvenile Atlantic salmon exposed to pre-thermal stress sampling conditions (16–21°C)EndpointTimeTreatmentInteractiondfF-statisticP-valuedfF-statisticP-valuedfF-statisticP-valueCTMax**–––14.070.073–––L glycogen11.260.27210.990.33010.570.458WB glucose18.450.006*16.700.014*11.230.276WB lactate10.070.79010.150.70212.790.106L HSP70127.62<0.001*18.280.008*10.280.601L Ub10.230.63310.220.64010.300.588RBC HSP70116.88<0.001*1182.09<0.001*12.670.113RBC Ub10.120.73710.280.59810.350.558CTMax = critical thermal maximum; L = liver; M = muscle; WB = whole blood; RBC = red blood cell; HSP70 = heat shock protein 70; Ub = ubiquitin. Asterisks indicate significance of two-way ANOVA with α = 0.05 and P <0.05.**One-way ANOVA performed.
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Fish exposed to 16–21°C lost equilibrium at 32.5 ± 0.09°C, a temperature significantly higher than those maintained at a stable acclimation temperature of 16°C (31.4 ± 0.09°C; F2, 48 = 43.0, P < 0.001). Overall, CTMax increased in all thermally cycled groups compared to the 16–21°C-control group (F3, 64 = 31.92, P < 0.001). Significant increases in CTMax were observed in all temperature treatments after one day of cycling (t = 72 h; P < 0.001), with no significant differences observed between groups (Fig. 2B–D; P = 0.11–0.77). No significant differences were observed between t = 72 h and t = 120 h of heat cycling within or between temperature treatments (pooled mean of all heat exposed fish = 33.1 ± 0.08°C; P = 0.96–0.99; Table 2; Fig. 2). Figure 2:CTMax of wild juvenile salmon exposed to diel cycles: (A) 16–21°C (control group); or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–10). Open symbols (t = 24 h) represent pre-thermal stress sampling time points and were secondarily used to assess the effect of ‘trial’. Asterisks indicate significant differences among treatments (P < 0.05).Table 2:Two-way ANOVA performed on physiological variables of juvenile Atlantic salmon exposed to multi-day thermal stressEndpointTimeTreatmentInteractiondfF-statisticP-valuedfF-statisticP-valuedfF-statisticP-valueCTMax11.140.290331.93<0.001*30.160.920L glycogen46.93<0.001*36.73<0.001*122.630.003*WB glucose41.720.14932.550.057121.440.155WB lactate45.65<0.001*32.330.077121.740.062L HSP704100.61<0.001*3177.05<0.001*129.68<0.001*L Ub44.290.002*32.540.058121.380.179RBC HSP70473.18<0.001*3207.50<0.001*1222.25<0.001*RBC Ub44.780.001*315.03<0.001*121.070.388Asterisks indicate significance of two-way ANOVA with α = 0.05 and P <0.05.
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CTMax of wild juvenile salmon exposed to diel cycles: (A) 16–21°C (control group); or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–10). Open symbols (t = 24 h) represent pre-thermal stress sampling time points and were secondarily used to assess the effect of ‘trial’. Asterisks indicate significant differences among treatments (P < 0.05).
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Liver glycogen levels in the 16–21°C group remained relatively stable at a mean of 67.4 ± 4.8 mg g−1 throughout the experimental sampling period (Fig. 3). Although liver glycogen decreased over time in all but the 16–21°C group, a significant interaction was observed between time and temperature treatment (F12, 160 = 2.63, P < 0.003; Table 2) indicating that the pattern of decline was different in each thermally cycled group. No significant differences in glycogen were observed prior to the first heat cycle in any temperature treatment (t = 48 h; F3, 27 = 1.08, P = 0.37; Fig. 3). Differences among thermally cycled groups were apparent at the peak of the first heat cycle (t = 60 h). The 20–27°C and 22–27°C groups experienced the most pronounced decline in liver glycogen, but by the end of the experiment (t = 120 h) only the 22–27°C group was significantly different than the 16–21°C group (19.1 ± 4.0 mg·g−1, P = 0.006). One noteworthy exception to the overall pattern is the observed spike in liver glycogen at t = 72 h in the 20–27°C group (Fig. 3C) that was significantly greater than the 16–21°C and 22–27°C groups (P = 0.04 and P < 0.001, respectively). Figure 3:Liver glycogen in juvenile salmon exposed to diel cycles: (A) 16–21°C (control group); or multi-day thermal stress (60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 6–9). Pre-thermal stress sampling (t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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Liver glycogen in juvenile salmon exposed to diel cycles: (A) 16–21°C (control group); or multi-day thermal stress (60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 6–9). Pre-thermal stress sampling (t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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WB glucose did not change with temperature treatment (F3, 160 = 2.56, P = 0.057) or time (F4, 160 = 1.72, P = 0.15; Table 3). However, as noted above, significant differences were observed between WB glucose pre-thermal stress time points (P = 0.007; Table 1). Table 3:Mean whole blood lactate and glucose (±SEM) in juvenile Atlantic salmon exposed to 16–21°C (control group) for 5 days; or multi-day thermal stress (18–27°C, 20–27°C or 22–27°C)Treatment (°C)Time point (h)12*24**48a60a72a108a120aWhole blood glucose 16–211.9 ± 0.293.2 ± 0.373.1 ± 0.322.1 ± 0.392.1 ± 0.372.0 ± 0.272.0 ± 0.19 18–271.5 ± 0.152.0 ± 0.262.9 ± 0.292.7 ± 0.562.0 ± 0.262.7 ± 0.361.8 ± 0.18 20–27––1.8 ± 0.263.2 ± 0.422.7 ± 0.153.0 ± 0.421.9 ± 0.31 22–27––2.9 ± 0.282.8 ± 0.642.1 ± 0.361.9 ± 0.302.3 ± 0.2812*24*48a60b72ab108b120aWhole blood lactate 16–212.6 ± 0.283.3 ± 0.423.7 ± 0.443.4 ± 0.604.6 ± 0.714.8 ± 0.852.1 ± 0.22 18–273.7 ± 0.832.8 ± 0.343.1 ± 0.394.5 ± 0.882.6 ± 0.253.8 ± 0.301.9 ± 0.39 20–27––2.5 ± 0.374.3 ± 0.422.9 ± 0.374.5 ± 0.504.0 ± 0.73 22–27––3.6 ± 0.795.2 ± 0.503.2 ± 0.364.8 ± 0.923.2 ± 0.16Stress occurred from 60 to 120 h. Pre-thermal stress sampling (12 and 24 h) assessed the effect of ‘trial’ and ‘bank’ and was analyzed separately.Letters are indicative of significance between sampling time points during thermal ramping (t = 48 h–120 h; P < 0.05). Asterisks are indicative of significance between pre-thermal stress sampling time points.
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We did not observe any differences in blood lactate among temperature treatments (F3, 160 = 2.33, P = 0.08; Table 3); however, we did note differences in blood lactate over time (F4, 160 = 5.65, P < 0.001). Blood lactate at Tmin throughout the elevated thermal cycles (t = 72–120 h) did not differ from the pre-thermal stress intermediate Tmin (t = 48; P = 0.96 and P = 0.87, respectively), nor was there a significant difference at the peak of the first heat cycle (t = 60 h; P = 0.06). However, blood lactate was significantly higher at the peak of the third heat cycle compared with the initial pre-temperature stress condition prior to thermal ramping (t = 108 h; P = 0.02). Significant decreases in blood lactate were observed at t = 120 h compared with both thermal peaks (t = 60 h and t = 108 h; P = 0.004 and P = 0.001, respectively).
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Liver HSP70 was not induced under control conditions (Fig. 4A); however, a significant interaction was observed with time and temperature treatment (F12, 160 = 9.68, P < 0.001), indicating that the pattern of induction depended on thermal regime. Liver HSP70 was induced in the 18–27°C and 22–27°C groups at the pre-thermal stress sampling point after exposure to 23°C (t = 48 h; P < 0.001 & P = 0.02, respectively). The peak of the first day of heat exposure induced a significant increase in liver HSP70 in all three high thermal cycles compared to the 16–21°C group (t = 60 h; P < 0.001; Fig. 4); however, HSP70 was not significantly different among the temperature treatments. Although the specific pattern of liver HSP70 induction varied among temperature treatments, levels remained elevated throughout the duration of the 3-day heat event (t = 60–120 h; P < 0.001 in all cases). After the onset of the event, treatments did not vary from one another statistically (P = 0.07–0.99), with the exceptions of the diel minima following the first and third heat cycles (t = 72 and 120 h) where HSP70 levels in the 18–27°C were significantly greater than in the 22–27°C group (P = 0.018 and 0.008, respectively; Fig. 4). Figure 4:Liver HSP70 in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–9). Pre-thermal stress sampling (open symbols; t = 12 & 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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Liver HSP70 in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–9). Pre-thermal stress sampling (open symbols; t = 12 & 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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As was the case with HSP70, liver Ub was significantly increased over time (F4, 160 = 4.29, P = 0.002; Fig. 5), but we did not observe statistically significant differences among thermal groups (F3, 160 = 2.54, P = 0.058; Table 2). Although in several cases, differences between sampling time points approached significance (t = 48 h and t = 72 h, P = 0.06; t = 60 h and t = 108 h, P = 0.07; t = 108 and t = 120 h, P = 0.066), the only significant difference in liver Ub was observed at t = 108 h, where Ub was significantly higher than pre-thermal exposure values, t = 48 h (P = 0.003). Figure 5:Liver Ub in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 6–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Lettered shaded bars indicate significant differences between time points (P < 0.05).
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Liver Ub in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 6–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Lettered shaded bars indicate significant differences between time points (P < 0.05).
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Overall, relative RBC HSP70 levels were lower than those observed with liver HSP70 (Fig. 6). Similar to liver HSP70, a significant interaction (F12, 160 = 22.25, P < 0.001; Table 2) between thermal cycle and time was observed. RBC HSP70 was induced at the peak of the first heat cycle (t = 60 h) in all three-temperature treatments. At t = 60 h, RBC HSP70 in 22–27°C group was significantly higher than the other treatments (P < 0.001; Fig. 6). However, at the next sampling point (t = 72 h), relative RBC HSP70 was greater in the 18–27°C group than in the other temperature treatments. At the end of the experiment (t = 120 h), RBC HSP70 remained elevated in all thermal groups, but was significantly lower in the 20–27°C group compared to the 18–27°C and 22–27°C groups. Figure 6:RBC HSP70 in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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RBC HSP70 in juvenile salmon exposed to diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Data are presented as mean ± SEM (n = 5–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Letters indicate significant differences among treatments (P < 0.05) within sampling time points.
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As was the case with HSP70, RBC Ub levels were comparatively lower than in liver (Fig. 7). RBC Ub changed over time and between temperature treatments (F4, 160 = 4.78, P = 0.001; F3, 160 = 15.03, P < 0.001; Table 2). Similar to liver Ub, all three thermal groups had significantly greater RBC Ub than the control at 16–21°C (P < 0.001), but did not differ significantly from one another (P = 0.47–0.99). RBC Ub significantly increased at t = 72 h, after the peak of the first heat cycle (P = 0.007). Unlike the case in liver where Ub levels were no longer significantly different from pre-thermal exposure at 120 h (P = 0.91), RBC Ub remained significantly higher than the pre-thermal exposure (t = 48 h) after the final thermal cycle (t = 120 h; P < 0.001). Figure 7:RBC Ub in juvenile salmon exposed to the following diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Points represent mean ± SEM (n = 4–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Asterisks indicate significant differences between treatments. Lettered shaded bars indicate significant differences between time points (P < 0.05).
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RBC Ub in juvenile salmon exposed to the following diel cycles: (A) 16–21°C only; or multi-day thermal stress (closed symbols; 60–120 h) of (B) 18–27°C; (C) 20–27°C; (D) 22–27°C. Points represent mean ± SEM (n = 4–9). Pre-thermal stress sampling (open symbols; t = 12 and 24 h) assessed the effect of ‘trial’ and was not included in the analysis. Asterisks indicate significant differences between treatments. Lettered shaded bars indicate significant differences between time points (P < 0.05).
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Environmental thermal patterning has been recognized as being intrinsically linked to fish physiology and performance (Helfman et al., 2009; Vasseur et al., 2014) and important for predicting the effects of climate change. We hypothesized that the nature of the thermal cycle, specifically nighttime temperature would dictate the physiological limits of juvenile Atlantic salmon. We found that our thermal cycles did initiate increases in CTMax and provided evidence of both cellular and metabolic stress. However, contrary to our expectation, we did not observe a correlation between the overall metabolic/cellular condition throughout a simulated heat event and the daily thermal minima. Thus, when fish are exposed to warming diel cycles approaching their critical temperature, we conclude that the diel thermal minima normally experienced by juvenile Atlantic salmon may not play a critical role in the ability of these fish to deal with extreme events. Notably, our experimental design, where we used a fixed maximum temperature, did not allow us to disentangle possible effects of the magnitude of diel thermal fluctuation from minimum nighttime temperatures. However, recent research from our group concluded that the nature of ecologically relevant diel thermal cycling (e.g. accumulated thermal exposure, magnitude, rate of change) did not significantly affect metabolism or the stress response in wild Atlantic salmon (Tunnah et al., 2017). Regardless, distinguishing between the importance of Tmin and ΔT is an important direction for future research.
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Exposure to ecologically relevant thermal cycles (16–21°C) increased acute thermal tolerance (CTMax) compared to fish held at a stable acclimation temperature (16°C). Furthermore, we determined that exposure to a single elevated high temperature pulse (27°C) increased CTMax values by ~1°C but neither diel Tmin nor exposure to repeated diel pulses further elevated CTMax. Acclimation temperature has long been known to influence thermal tolerance in ectotherms (Beitinger et al., 2000); however, few studies have examined the effects of thermal cycles on CTMax (see Bennett and Beitinger, 1997; Currie et al., 2004; Fangue et al., 2011). In support of our findings, diel cycling did not affect CTMax in killifish (Fundulus heteroclitus) (Healy and Schulte, 2012) or the northern two-lined salamander (Eurycea bislineata) (Rutledge et al., 1987). In both cases, CTMax increased only when overall acclimation temperature was increased. Furthermore, Healy and Schulte (2012) suggest a complex association between variation in acute thermal tolerance and physiological (i.e. altered membrane fluidity) and environmental (i.e. photoperiod, hypoxia and time of day) processes. In nature, maximum temperature tolerance is poorly understood and thought to be a function of time, diel mean and ΔT (Wehrly et al., 2007) with periods of repeated sublethal stress capable of delaying mortality (Selong et al., 2001).
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Our thermal cycles induced significant changes in blood lactate and liver glycogen, with minimal differences among thermal regimes. Alterations to the initial metabolic condition when an organism is exposed to increasing (LeBlanc et al., 2011) and diel thermal stress are often short lived (<24 h; Tunnah et al., 2017). In our study, transitory cyclic increases in both blood lactate and glucose occurred in the warm thermal cycles. The modest decreases in liver glycogen we observed with high temperature cycling may be indicative of rapid mobilization of free glucose to surrounding metabolically active tissues resulting in a loss of metabolic capacity (Viant et al., 2003). After 3 days of thermal cycling, no difference in liver glycogen was apparent among treatments suggesting a comparably high energetic demand in all our diel thermal cycles. Our results therefore suggest that salmon metabolically manage diel cycles in an equivalent manner, regardless of nighttime temperature, refuting the notion that warmer thermal minima are most strenuous (see DFO, 2012). Wilkie et al. (1997) exposed exercised Atlantic salmon to stable recovery temperatures and determined fish were able to recover to a pre-stress metabolic status faster at warmer temperatures (23°C vs. 12 and 18°C). There is some field evidence for the preference of warm recovery temperatures during periods of thermal stress. For example, juvenile salmonids have been observed dispersing from aggregations formed at cool water sources at nightfall despite temperatures remaining above the species’ thermal optima (Belchik et al., 2004; Corey et al., unpublished data). Although it is implied that this behavior is driven by a thermal cue, our results indicate that this response may not be directly associated with a metabolic or cellular advantage to a particular Tmin, but may be an effort to minimize the magnitude of temperature change experienced by the fish.
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We know that temperatures >22°C will induce HSP70 in wild juvenile Atlantic salmon in the Miramichi River (Lund et al., 2002). Diel temperature stress induced an upregulation of six heat shock genes in redband trout (Oncorhynchus mykiss gairdneri) (Narum et al., 2013) and HSP70 in several tissues of Atlantic salmon (Tunnah et al., 2017). Given this information, the current temperature conditions of the Miramichi River, and regulations regarding recreational angling (closure when T ≥ 20°C for two consecutive nights; DFO, 2012), our prediction was that juveniles experiencing higher nighttime temperatures would display a higher magnitude heat shock response (HSR) than those experiencing a lower diel Tmin. Instead, our data indicated that exposure to diel, environmentally relevant, sub-lethal heat stress, had cellular level consequences but the nature of high temperature cycling (i.e. nighttime temperature) had minor effects on the HSR. Thus, the magnitude of the thermal stress, regardless of diel cycle, was consistent with the magnitude of the HSR. Assuming that thermally induced protein denaturation/damage triggers the HSR (Ananthan et al., 1986), our data suggest that protein damage is similar among our different diel cycles. In support of this, induction of Ub occurred at the peak of the first heat cycle and remained elevated throughout the heating event, regardless of thermal cycle, as was the case with HSP70. Tunnah et al. (2017) also demonstrated consistency of the HSR with Ub induction in thermally cycled Atlantic salmon.
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Our measured physiological responses to thermal cycling were strikingly similar amongst the treatments and could be indicative of partial acclimation to increased temperatures caused by a slow ramping rate, or could suggest phenotypic plasticity to cope with thermal variability (Schulte et al., 2011; McBryan et al., 2013; Anttila et al., 2014). Metabolic stress in Atlantic salmon occurs at temperatures between 22°C and 24°C (Breau et al., 2011) demonstrating a limited ability to tolerate temperatures >28°C (Garside, 1973; Elliott, 1991), enduring 33°C only in acute circumstances (Elliott and Elliott, 1995). It is possible that genetic makeup and thermal history, specifically the frequency that these upper thermal thresholds are surpassed, may play a larger role in the metabolic and cellular status of juvenile salmon, while nighttime temperature may have little influence on a fish's ability to re-establish basal cellular and metabolic conditions. Wehrly et al. (2007) determined maximum temperature tolerance to be a function of time in two trout species, Salvelinus fontinalis and Salmo trutta, where prolonged warm periods negatively influenced upper thermal tolerance limits. Furthermore, in chronically warmed European perch (Perca fluviatilis), Sandblom et al. (2016) determined that, despite cardiorespiratory plasticity to deal with a warmer resting condition, the upper thermal limit remained relatively rigid in both cold and warm adapted fish, consequently reducing the available ‘thermal buffer’.
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Understanding how animals cope with large thermal fluctuations is critical to safeguard species in a changing climate. It has been suggested that if the rate of evolutionary or plastic responses lag behind the rate of climate change, there could be local extinction due to limitations in physiological capacities compared to the environmental variation (Chown et al., 2010). Here, we investigated key markers of the stress response in Atlantic salmon to determine how fish physiology responded to distinct warming scenarios with different nighttime temperatures. If high nighttime temperatures resulted in physiological stress, we would expect that the warmest (22–27°C) treatment would elicit the most obvious signs of cellular and metabolic disturbance. However, this was not the case as different Tmin thermal scenarios had little effect on our dependent variables. These findings lead us to reject the hypothesis that environmentally relevant nighttime temperature is a principal driver in the ability of Atlantic salmon to tolerate multi-day thermal events at, or near, critical temperatures. With future climate change scenarios predicting an increase in thermal extremes and increases in diel thermal minima, it is likely that physiologically important thresholds will be surpassed more frequently. Current regulations regarding recreational angling close the Miramichi River when T ≥ 20°C for two consecutive nights (DFO, 2012). Our results suggest that these regulations be revisited given that the overall effects of ‘warm nights’, at least within the temperature ranges tested here, do not appear to be a critical factor influencing Atlantic salmon. We do show that environmentally relevant diel thermal cycles up to 27°C are stressful for these fish; thus, management decisions should focus on ecologically grounded and relevant simulations of thermal stress and pay attention to maximum temperatures and ΔT. While turning down the temperature of the planet is not an option, an understanding of such biological responses to warming water temperatures will inform the design of effective habitat management strategies to ensure the availability of cool water refugia, protecting Atlantic salmon during these inevitable thermal challenges.
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The vertebrate cortex is responsible for the high cognitive functions of the brain. It is organized into distinct layers of neurons and within each layer neurons share similar functions, morphology and birthdates1. This organization optimizes the processing of information and it requires the tightly regulated migration of neurons during development2. Most cortical pyramidal projecting neurons originate from asymmetric division of radial glia progenitors in the ventricular zone. They then migrate radially towards the marginal zone and through the subventricular zone (SVZ) and lower intermediate zone. This migration requires an intriguing intermediate step in the lower intermediate zone (IZ) where neurons transiently become multipolar and where they dynamically extend and retract multiple long projections and move in apparently random directions2–4. Subsequent to this stage polarity is necessary to define neuronal projections as dendrites or axons and axogenesis starts as cells approach the middle of the intermediate zone. After the axon emerges, the cells reorient their centrosomes and Golgi toward the pial surface, as they move to the upper part of the intermediate zone5. Their morphology then changes from multipolar to bipolar and they resume radial migration6. Bipolar cells have a thick, radially oriented leading process (the future principal dendrite) and a thin trailing axon, and move by locomotion plus somal or nuclear translocation along the radial glia processes2, 7, 8. Neuronal orientation and polarity are thought to be regulated by extracellular signals, providing instructive cues to migrating neurons9.
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Changes in polarity and morphology have been more extensively studied in vitro. In hippocampal neurons in culture, a particularly early event in neuronal polarization is the segregation of activatable, membrane inserted, IGF-1R to one neurite in neurons that do not yet exhibit a discernible axon (stage 2 of differentiation10). Subsequently, phosphatidylinositol-3 kinase (PI3K) is activated and its product, PIP3, accumulates in the distal region of the neurite, together with IGF-1R. These events are critical for the outgrowth of the future axons and the establishment of neuronal polarity10–12. Similarly, IGF-1R activation was reported to be necessary for the regulation of axonal outgrowth of motor neurons13. However, a possible role of the IGF-1R in neuronal migration and the establishment of polarity in the cortex has not been addressed.
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Here, we show that the IGF-1R regulates the migration of cortical pyramidal neurons. Neurons electroporated with a shRNA targeting IGF-1R (shRNA-IGF-1R) fail to migrate to the upper cortical layers and accumulate at the ventricular/subventricular zones. Co-electroporation with a constitutively active form of PI3K rescued migration. Knocking down IGF-1 abrogated the morphological change from multipolar to bipolar and cells were arrested as multipolar forming heterotopic tissue. This correlates with the disruption of the typical orientation of the Golgi complex towards the marginal zone found in control migrating bipolar neurons. The cells electroporated with the shRNA-IGF-1R were unable to form an axon. In summary, the results indicate a necessary role of IGF-1 signaling in migration and the dynamic changes in neuronal polarities that occur at the SVZ/IZ during cortical development.
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We set out to investigate a possible role of IGF-1R in cortical migration by utilizing in utero electroporation of cortical progenitors at embryonic day (E) 15 in order to manipulate and visualize neurons destined to comprise layers II-IV of the cortex, allowing analysis of the location and morphology of the progeny after in vivo differentiation. Electroporation of shRNA-IGF-1R resulted in effective suppression of IGF-1R expression in most electroporated cells, as shown in Fig. 1. In brains co-electroporated with a non-relevant shRNA (control) and a plasmid encoding green fluorescent protein (CAG-GFP) and then immunostained with an antibody to the IGF-1R, 57% of the electroporated cells exhibited a strong staining (Fig. 1a-top and 1b). In contrast only 10% of the cells electroporated with the shRNA-IGF-1R were stained (Fig. 1a middle and 1b). Co-electroporation with resistant IGF-1R construct14 (IGF-1R OPT) rescued IGF-1R expression to control levels (Fig. 1-bottom). Also, the number of proliferating progenitor cells as analyzed by the incorporation of bromodeoxyuridine (BrdU) was found to be unchanged by electroporation of shRNA-IGF-1R compared to control (Supplementary Fig. 1a): 46.7% of the cells electroporated with control shRNA vs. 49,3% of the cells electroporated with shRNA-IGF-1 incorporated BrdU. Staining with doublecourtin to identify migrating neurons15, 16 showed 64.4 or 63.8% of positive cells in controls or cells electroporated with shRNA-IGF-1R, respectively (Supplementary Fig. 1b). We next analyzed the normal differentiation of cells at E19 or postnatal (P) day 4. At E19, about one third of the neurons were located in the ventricular zone/sub-ventricular zone (VZ/SVZ), 25% of cells were found migrating through the IZ and the majority (over 40%) had reached the top of the cortical plate (Fig. 2a-left; quantification shown in Fig. 2b). By P4, almost 100% are found located in layers II-IV of the cortex (Fig. 2c-quantification shown in Fig. 2d), as expected. Cells with knocked-down expression of IGF-1R showed altered distribution and abnormal migration at both E19 and P4. At E19, over 60% of the cells remained arrested at the VZ/SVZ/IZ compared to 30% in the control experiments (Fig. 2a,b). At P4, over 70% of the GFP positive neurons were located at the VZ/SVZ/IZ when knocking down IGF1R, compared to about 10% in controls (Fig. 2c,d). To discard the possibility of nonspecific or off-target effects of the shRNA-IGF-1R, we co-electroporated brains with shRNA-IGF-1R plus IGF-1R OPT. The results of this experiment showed that co-electroporation with IGF-1R OPT cDNA rescued migration to near normal levels, with over 80% of the cells reaching layers II-IV compared to around 20% in the brains electroporated with shRNA-IGF-1R alone (Fig. 2c; quantification shown in Fig. 2d). This demonstrates the specificity of shRNA-IGF-1R-mediated defects in migration and implicates IGF-1R in cortical migration.Figure 1Electroporation with shRNA-IGF-1R (shIGF-1R) significantly reduces expression of IGF-1R. (a) Representative images of brains electroporated at E15 with control shRNA (top), shRNA-IGF-1R (middle) or co-electroporated with IGF-1R OPT and shRNA-IGF-1R (bottom) showing the expression of IGF-1 R (at E17). The ventricular zone (VZ) is labeled for orientation. All brains were co-electroporated with CAG-GFP. (b) Quantification of the number of electroporated cells positive forIGF-1R as shown in A. Note the significant decrease of IGF-1R expression in the cells electroporated with shRNA-IGF-1R. Student’s t test. ***p ≤ 0.0001, ns = not significant. n = 3 independent experiments. At least 100 cells were scored for each condition. Figure 2Expression of IGF-1R regulates neuronal migration. (a) Brains were electroporated with shRNA-IGF-1R (shIGF-1R/CAG-GFP) (right) or control shRNA/CAG-GFP (control-left), at E15 and analyzed at E19. Few GFP positive cells were located in the cortical plate (CP) and the marginal zone (MZ) when IGF-1R expression was knocked down compared to control. Calibration bar = 50 μm. (b) Quantification of the distribution of GFP-positive cells in CP, intermedial zone (IZ) and ventricular/subventricular zones (VZ/SVZ)as indicated in A. Student’s t test *p ≤ 0.05; **p ≤ 0.01; ns = not significant. (c) Brains were electroporated at E15 with shIGF-1R/CAG-GFP (middle), control shRNA/CAG-GFP (left) or co-electroporated with shIGF-1R/CAG-GFP plus cDNA coding for IGF-1R OPT and analyzed at P4. A few GFP positive cells are located in layers V-VI and noticeably fewer GFP positive cells are found in layers II-IV in the IGF-1R suppressed brain compared to the control. In contrast, an important accumulation of GFP positive cells was observed at the (VZ/SVZ/IZ) zones in the shRNA-IGF-1R brain. Note that co-transfection with cDNA coding for IGF-1R OPT (shRNA-refractive cDNA that will express the IGF-1R even in the presence of shRNA-IGF-1R) rescued the morphology. Calibration bar = 100 μm. (d) Quantification of the distribution of GFP positive neurons in VZ/SVZ/IZ, layers II-IV, V and VI as in c. Post hoc Turkey’s ANOVA **p ≤ 0.01 ***p ≤ 0.0001. n = 3 independent experiments. An average of 300 cells (a,b) or 500 cells (c,d) were scored for each condition.
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Electroporation with shRNA-IGF-1R (shIGF-1R) significantly reduces expression of IGF-1R. (a) Representative images of brains electroporated at E15 with control shRNA (top), shRNA-IGF-1R (middle) or co-electroporated with IGF-1R OPT and shRNA-IGF-1R (bottom) showing the expression of IGF-1 R (at E17). The ventricular zone (VZ) is labeled for orientation. All brains were co-electroporated with CAG-GFP. (b) Quantification of the number of electroporated cells positive forIGF-1R as shown in A. Note the significant decrease of IGF-1R expression in the cells electroporated with shRNA-IGF-1R. Student’s t test. ***p ≤ 0.0001, ns = not significant. n = 3 independent experiments. At least 100 cells were scored for each condition.
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Expression of IGF-1R regulates neuronal migration. (a) Brains were electroporated with shRNA-IGF-1R (shIGF-1R/CAG-GFP) (right) or control shRNA/CAG-GFP (control-left), at E15 and analyzed at E19. Few GFP positive cells were located in the cortical plate (CP) and the marginal zone (MZ) when IGF-1R expression was knocked down compared to control. Calibration bar = 50 μm. (b) Quantification of the distribution of GFP-positive cells in CP, intermedial zone (IZ) and ventricular/subventricular zones (VZ/SVZ)as indicated in A. Student’s t test *p ≤ 0.05; **p ≤ 0.01; ns = not significant. (c) Brains were electroporated at E15 with shIGF-1R/CAG-GFP (middle), control shRNA/CAG-GFP (left) or co-electroporated with shIGF-1R/CAG-GFP plus cDNA coding for IGF-1R OPT and analyzed at P4. A few GFP positive cells are located in layers V-VI and noticeably fewer GFP positive cells are found in layers II-IV in the IGF-1R suppressed brain compared to the control. In contrast, an important accumulation of GFP positive cells was observed at the (VZ/SVZ/IZ) zones in the shRNA-IGF-1R brain. Note that co-transfection with cDNA coding for IGF-1R OPT (shRNA-refractive cDNA that will express the IGF-1R even in the presence of shRNA-IGF-1R) rescued the morphology. Calibration bar = 100 μm. (d) Quantification of the distribution of GFP positive neurons in VZ/SVZ/IZ, layers II-IV, V and VI as in c. Post hoc Turkey’s ANOVA **p ≤ 0.01 ***p ≤ 0.0001. n = 3 independent experiments. An average of 300 cells (a,b) or 500 cells (c,d) were scored for each condition.
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IGF-1R signaling can activate the phosphatidyl inositol 3 kinase (PI3K) pathway, which promotes neurite growth and is involved in neuronal differentiation and polarization11, 17. To evaluate if this pathway is involved in the IGF-1R effects on the migration of cortical neurons we co-electroporated brains with shRNA-IGF-1R plus p110CAAX, a construct that expresses a constitutively active form of the catalytic subunit of PI3K. Analysis at P4 demonstrated rescue of migration with almost 70% of the GFP positive cells located in layers II-IV compared to 20% of cells electroporated with shRNA-IGF-1R alone (Fig. 3a,b). The results suggested that activation of the PI3K pathway is downstream of IGF-1R signaling and contributes to neuronal migration in the cerebral cortex.Figure 3Activation of phosphatidyl inositol-3 kinase (PI3K) rescues migration defects. (a) Coronal sections of P4 brains electroporated at E15 with shIGF-1R/CAG-GFP, control shRNA/CAG-GFP or shIGF-1R/CAG-GFP together with a constitutively active form of PI3K (p110CAAX-right); Calibration bar = 100 μm. (b) Quantification of the distribution of GFP-positive cells in VZ/SVZ/IZ, and layers II-IV and V-VI as indicated in (a). Note the significant increase in GFP positive cells in the deep layers (VZ/SVZ/IZ) zones and the decrease of GFP positive cells in the upper layers (II-IV) when knocking down IGF-1R. Co-transfection with p110CAAX rescued migration defects Post hoc Turkey’s ANOVA **p ≤ 0.01, ***p ≤ 0,0001. n = 3 independent experiments. An average of 500 cells was scored for each condition.
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Activation of phosphatidyl inositol-3 kinase (PI3K) rescues migration defects. (a) Coronal sections of P4 brains electroporated at E15 with shIGF-1R/CAG-GFP, control shRNA/CAG-GFP or shIGF-1R/CAG-GFP together with a constitutively active form of PI3K (p110CAAX-right); Calibration bar = 100 μm. (b) Quantification of the distribution of GFP-positive cells in VZ/SVZ/IZ, and layers II-IV and V-VI as indicated in (a). Note the significant increase in GFP positive cells in the deep layers (VZ/SVZ/IZ) zones and the decrease of GFP positive cells in the upper layers (II-IV) when knocking down IGF-1R. Co-transfection with p110CAAX rescued migration defects Post hoc Turkey’s ANOVA **p ≤ 0.01, ***p ≤ 0,0001. n = 3 independent experiments. An average of 500 cells was scored for each condition.
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We next performed ankyrin-G staining at P4 to analyze neuronal polarity and the acquisition of a mature axonal structure18. These immunostainings demonstrated that most cells electroporated with shRNA-IGF-1R arrested at the VZ/SVZ/IZ did not express ankyrin-G (Fig. 4a bottom). Only the few cells that migrate to layers II-IV (Fig. 4a top) or layers V-VI (Fig. 4 middle) exhibited an axon as shown by immunostaining for the axonal protein ankyrin-G In contrast, in control brains close to 100% of the electroporated cells migrate to layers II-IV (see Fig. 2) and develop mature axons enriched in ankyrin-G (Fig. 4b).Figure 4shRNA-IGF-1R arrested neurons fail to acquire axonal polarity as shown by ankyrin-G staining (lack of ankyrin-G clusters). (a) Brains were electroporated with shIGF-1R/CAG-GFP at E15 and analyzed at P4 after staining with an antibody to ankyrin-G to show axons. Cells in the V-VI layers (middle) or layers II-IV (top) show co-staining of the trailing process with ankyrin-G indicating normal polarity and the correct compartmentalization/specialization of the apical neurite into anaxonal structure. Cells arrested in the VZ/SVZ/IZ show lack of ankyrin-G staining indicating failure to develop dendritic-axonal polarity. (b) Brains were electroporated with control shRNA/CAG-GFP at E15 and analyzed at P4 after staining with an antibody to ankyrin-G to show axons. Cells in layers II-IV exhibit axons stained with ankyrin G. Virtually no cells were found in the VZ/SVZ/IZ and layers V-VI under this experimental condition (see Fig. 2) Calibration bar 10 μm.
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shRNA-IGF-1R arrested neurons fail to acquire axonal polarity as shown by ankyrin-G staining (lack of ankyrin-G clusters). (a) Brains were electroporated with shIGF-1R/CAG-GFP at E15 and analyzed at P4 after staining with an antibody to ankyrin-G to show axons. Cells in the V-VI layers (middle) or layers II-IV (top) show co-staining of the trailing process with ankyrin-G indicating normal polarity and the correct compartmentalization/specialization of the apical neurite into anaxonal structure. Cells arrested in the VZ/SVZ/IZ show lack of ankyrin-G staining indicating failure to develop dendritic-axonal polarity. (b) Brains were electroporated with control shRNA/CAG-GFP at E15 and analyzed at P4 after staining with an antibody to ankyrin-G to show axons. Cells in layers II-IV exhibit axons stained with ankyrin G. Virtually no cells were found in the VZ/SVZ/IZ and layers V-VI under this experimental condition (see Fig. 2) Calibration bar 10 μm.
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We also studied early cell orientation by co-electroporating brains with a construct encoding the Golgi resident enzyme Gal-T2 tagged with yellow fluorescent protein (YFP) (Gal-T2-YFP) plus DsRed, in control and shRNA-IGF-1R conditions. The results of these experiments showed that, in control brains, the Golgi complex of over 75% of the DsRed positive cells were oriented towards the marginal zone (Fig. 5a left). In contrast, only 60% of the shRNA-IGF-1R electroporated cells exhibited the Golgi complex oriented toward the outer cortical plate, showing a close to random arrangement (Fig. 5a and b). For quantifications, we considered that a cells has the Golgi not oriented to the cortical plate when the majority of the staining was concentrated in the lower part of the axis as shown in the diagram (Fig. 5c). These experiments indicate that in the absence of IGF-1R neurons fail to maintain or acquire proper orientation.Figure 5shRNA-IGF-1R disrupts the polarized location of migrating neurons. (a) Co-electroporation of shIGF-1R/DsRed and GalT2-YFP into brains at E15 (left) decreases the proportion of DsRed-positive cells in the VZ and/or IZ with a Golgi apparatus oriented towards the radial axe fate at E17 compared to a control vector (left). Lower magnification pictures (bottom) and higher magnification insets (top) are shown. Calibration bar = 50 μm (bottom) or 25 μm (top). (b) Quantification of the experiment shown in A. Student’s t test; **p-value = 0.01. Note that in the brains suppressed for IGF-1R the number of cells facing the cortical plate is close to 60% (random distribution = 50%). n = 3 independent experiments. An average of 300 cells was scored for each condition. (c) For quantifications, we considered that a cell has the Golgi not oriented to the CP when the majority of the GalT2 staining was concentrated below the axis.
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shRNA-IGF-1R disrupts the polarized location of migrating neurons. (a) Co-electroporation of shIGF-1R/DsRed and GalT2-YFP into brains at E15 (left) decreases the proportion of DsRed-positive cells in the VZ and/or IZ with a Golgi apparatus oriented towards the radial axe fate at E17 compared to a control vector (left). Lower magnification pictures (bottom) and higher magnification insets (top) are shown. Calibration bar = 50 μm (bottom) or 25 μm (top). (b) Quantification of the experiment shown in A. Student’s t test; **p-value = 0.01. Note that in the brains suppressed for IGF-1R the number of cells facing the cortical plate is close to 60% (random distribution = 50%). n = 3 independent experiments. An average of 300 cells was scored for each condition. (c) For quantifications, we considered that a cell has the Golgi not oriented to the CP when the majority of the GalT2 staining was concentrated below the axis.
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study
| 100.0 |
Next, we studied if IGF-1R is necessary for the early transition from multipolar to bipolar morphology. Animals were electroporated at E15 and observed at E17. At this time, previous studies have shown that most cells in the lower intermediate zone and SVZ are multipolar, whereas most cells in the upper intermediate zone and cortical plate are bipolar2–4, 19, 20. Consequently, these regions were named the multipolar migration zone (MMZ) and the radial migrating zone (RMZ), respectively21. Results showed that nearly80% of control cells located in the RMZ exhibited a bipolar morphology, as defined by the absence of more than two projections (Fig. 6a,b,c). In contrast, around 60% of the shRNA-IGF-1R electroporated cells found in the RMZ were arrested as multipolar cells. Co-electroporation of IGF-1R OPT and shRNA-IGF-1R rescued normal polarization of the electroporated cells (Fig. 6a,b,c).Figure 6IGF-1R stimulates polarity switch of migrating neurons. (a) shRNA-IGF-1R (center) decreases the proportion of bipolar cells in the radial migration zone (RMZ) at E17 compared to a control vector (left). Co-electroporation of shRNA-IGF-1R and IGF-1 OPT rescued normal polarization (right). (b) Cell morphologies of shRNA-IGF-1R and control cells are shown at higher magnification at the RMZ and multipolar marginal zone MMZ Calibration bar = 50 μm. (c) Quantification of in the morphologies of cells located in the RMZ from a. Student’s t test; ***p-value = 0.002. n = 3 independent experiments. An average of 100 cells was scored for each condition.
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study
| 100.0 |
IGF-1R stimulates polarity switch of migrating neurons. (a) shRNA-IGF-1R (center) decreases the proportion of bipolar cells in the radial migration zone (RMZ) at E17 compared to a control vector (left). Co-electroporation of shRNA-IGF-1R and IGF-1 OPT rescued normal polarization (right). (b) Cell morphologies of shRNA-IGF-1R and control cells are shown at higher magnification at the RMZ and multipolar marginal zone MMZ Calibration bar = 50 μm. (c) Quantification of in the morphologies of cells located in the RMZ from a. Student’s t test; ***p-value = 0.002. n = 3 independent experiments. An average of 100 cells was scored for each condition.
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study
| 100.0 |
At P4, the majority of IGF-1R knocked-down cells remained arrested at the VZ/SVZ/IZ, exhibited a multipolar morphology, and clustered forming highly heterotrophic arrays (Fig. 7, right); in contrast, control cells migrated normally and exhibited a normal branched morphology of apical neurites and a tailing axon (Fig. 7, left).Figure 7IGF-1R suppressed neurons remain as multipolar cells even at P4. Cells arrested in the VZ/SVZ/IZ in brains electroporated with the shRNA-IGF-1R and analyzed at P4 are mainly multipolar cells arranged in heterotopic groups (right). Control cells in layers II-IV show normal differentiation with a ramified dendrite (arrowhead) and a trailing axon (left). Calibration bar = 10 μm.
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study
| 100.0 |
IGF-1R suppressed neurons remain as multipolar cells even at P4. Cells arrested in the VZ/SVZ/IZ in brains electroporated with the shRNA-IGF-1R and analyzed at P4 are mainly multipolar cells arranged in heterotopic groups (right). Control cells in layers II-IV show normal differentiation with a ramified dendrite (arrowhead) and a trailing axon (left). Calibration bar = 10 μm.
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study
| 99.94 |
In this work we provide evidence indicating that early expression of IGF-1R could be required for the normal orientation of cortical neuron precursors, with the Golgi complex oriented toward the cortical plate22. Migrating immature cortical plate neurons acquire a transient multipolar morphology in the VZ/SVZ. Then, after a polarity switch from multipolar to bipolar, they extend an axon at the upper IZ3, 4, 19, 20.This polarity switch is an important step during radial migration that has been implicated in specification of neuron subtype identity, cortical lamination, and projection formation3, 9, 23–25. Loss of function of the IGF-1R increases the proportion of neurons with multipolar morphology at the expense of bipolar cells in the RMZ. Therefore, IGF-1R is necessary for the polarity switch as well as neuronal migration, since most cells with knocked-down expression of IGF-1R remain arrested at the VZ/SVZ/IZ and are unable to form an axon, stopping neuronal polarity. We show that the IGF-1R acts through the activation of the PI3K pathway, as co- with shRNA-IGF-1R and a constitutively active form of PI3K rescues the migration defects.
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study
| 100.0 |
Both ex vivo and in vivo studies have demonstrated the capacity of IGF-1 to stimulate neuronal differentiation. Studies demonstrating IGF-1 stimulation of neuritic outgrowth were among the first showing IGF-1 actions on neural cells26. Later IGF-1 was shown to increase dendrite growth in cultured neonatal Purkinje cells27 and to increase the number of pyramidal cell dendrites and their branching in somatosensory cortical explants28. In cultured hippocampal neurons, IGF-1 stimulates the assembly of axonal growth cones29, 30 and the establishment of neuronal polarity10. IGF-1R knock-out mice die shortly after birth and have serious defects in central nervous system development31. In humans, both homozygous and heterozygous mutations of the IGF-1R have been described and several developmental defects are consistently found in these patients, including microcephaly and cortical layer disorganization32. The PI3K pathway is also essential for neuronal polarization in hippocampal neurons in culture11, 17.
|
review
| 99.7 |
In summary, the results reported in this study show that IGF-1R is necessary for the early orientation and polarity switch of cortical plate neurons and, therefore, for normal neuron migration and differentiation, including axonal outgrowth and the establishment of neuronal polarity. Finally, we propose that the PI3K pathway could be involved in IGF-1R effects on cortex formation. More investigation will be needed in order to identify all the components of the IGF-1R/PI3K pathway implicated in the regulation of these phenomena.
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study
| 100.0 |
shRNA plasmids: shRNA-IGF-1R (1) Clone identity: NM_010513.1-3300s1c1 (TRCN0000023490):5′GCAGAATAATCTAGTCCTCAT-3′ and shIGF-1R (2) Clone identity: NM_010513.1-3656s1c1 (TRCN0000023493): 5′-CCAACGAGCAAGTTCTTCGTT-3′ cloned into the plasmid pLKO 1. (Sigma Chemical Co, Mo, USA) Control shRNA does not recognize any mouse sequence. The construct pCAG-DsRed and pCAG-GFP were generous gifts from Connie Cepko. The construct IGF-1R OPT was prepared in GeneScrip (Piscataway, NJ, USA). p110CAAX was constructed at Dr. Marta Nieto Laboratory.
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other
| 99.75 |
In utero electroporation was performed as previously described33 with minor modifications. Briefly, C57BL/6J mice pregnant at E15 days were anaesthetized with isoflurane (Piramal UK). Needles for injection were pulled from P-97 Flaming/Brownglass capillaries (World Precision Instruments, Sarasota, FL, USA). shRNA solutions were mixed in 10 mM Tris, pH 8.0, Tripan blue and plasmid and injected at a concentration of 0.5–1.5 µg/µl each construct. Five pulses of 38V (50 ms ON, 950 OFF) were applied using 5 mm electrodes and a dedicated electroporator (LIADE National University of Córdoba, Argentina). The embryos were placed back into the abdominal cavity to avoid excessive temperature loss and the abdominal cavity was sutured.
|
study
| 99.94 |
Mice were perfused transcardially with 4% paraformaldehyde (PFA) in PBS. The perfused brains were removed and post-fixed in 4% paraformaldehyde at 4 °C. Dissected brains were post-fixed overnight with 4% PFA in PBS. To make coronal sections, the brains were cryoprotected by overnight immersion in 30% sucrose in PBS and embedded in OCT. Floating cryosections of 50 μm were permeabilized whit PBS containing 0.5% Triton-X 100 and blocked with 2% BSA and 0.3% Triton X-100 in PBS The sections were incubated overnight at 4 °C with primary antibodies and washed with PBS, incubated with Alexa 546. (1 h at room temperature) and washed with PBS.
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study
| 99.9 |
Rat monoclonal antibody to ankyrin-G clone N106/36, NeuroMab Davis, CA, USA, diluted 1:1000; goat polyclonal antibody to doublecortin (Santa Cruz Biotechnology, Inc., CA, USA; diluted1:200; mouse monoclonal antibody to BrdU, Roche Diagnostic, Lewes, UK, diluted 1:1000; mouse monoclonal antibody to IGF-1R, clone ab80547, Abcam, Cambridge, MA, USA; diluted 1/100.
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other
| 99.94 |
Confocal microscopy was performed with using a confocal microscope Olympus FV1200 with Tilescan (Olympus, Japan). Images were captured and digitized using Olympus Fluoview Viewer software using a 1024 × 1024 scan format with 20x and 63x objective. All images were processed using Adobe PhotoShop (Adobe Systems, San Jose, CA, USA).
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other
| 99.94 |
In recent years, the broadened understanding of the interplay between components of the immune system and malignant cells has paved the way for establishing powerful tools of immunotherapy in the clinics. One major goal of cancer immunotherapy is to stimulate tumor-reactive T cells, which are often silenced in the tumor microenvironment. Molecules related to tumor escape from T-cell attack include cytotoxic T lymphocyte-associated protein-4 (CTLA-4) and programmed death-1 (PD-1), which are upregulated on T cells as a counter-regulatory mechanism upon prolonged stimulation . The interaction of these “immune checkpoint” molecules with their ligands, B7.1/B7.2 and PD-L1/PD-L2 expressed on antigen-presenting cells and tumor cells, respectively, inhibits positive signals mediated by the T-cell receptor (TCR) or the costimulatory receptor CD28 and thereby leads to suppression of T-cell responses [2–5]. Therefore, antibody-mediated blocking of immune checkpoints is an effective approach to boost tumor-reactive T-cell functions.
|
review
| 99.9 |
Ipilimumab, Nivolumab and Pembrolizumab are human or humanized monoclonal antibodies (mAb) that target CTLA-4 or PD-1, respectively, and interfere with inhibitory signals delivered by these receptors to the T cell. The CTLA-4-directed mAb Ipilimumab has been approved as first- and second-line therapy for patients with malignant melanoma and showed promising results in terms of overall survival [6, review in 7]. Combination therapies including Ipilimumab and anti-PD-1 [8–10] or other mAbs even proved to be superior to treatment with a single mAb.
|
review
| 99.9 |
A drawback of combining different immune checkpoint inhibitors is their unspecific mode of action involving “off-site” activation of T cells, which gives rise to undesired side effects . Therefore, we established a novel combination therapy making use of only one immune checkpoint inhibitor. This approach allows the activity of Ipilimumab to be targeted to T cells that strongly express CTLA-4 as a consequence of their specific stimulation in the presence of tumor cells. The tumor-specific T-cell activation is secured by trifunctional bispecific antibodies (trAbs), which selectively redirect T cells to tumor cells by virtue of two different binding arms recognizing CD3 and a tumor-associated antigen (TAA), respectively. Additionally, the intact Fc region of trAbs recruits and stimulates accessory cells such as dendritic cells (DCs) or macrophages via activating Fc receptors [13, 14]. These cells provide additional stimuli to T cells, take up tumor cell debris and present tumor-derived peptides to the immune system [15, 16]. Thus, trAbs not only lead to T cell-dependent tumor destruction, but also induce a long-lasting tumor-specific immunologic memory [16–18]. The role of the intact Fc region was established by experiments using Fc blocking or Fc-devoid antibody constructs [15–17, 19]. TrAbs are already in clinical use. Catumaxomab, for example, which binds to the TAA epithelial cell adhesion molecule (EpCAM), has been approved for the treatment of malignant ascites . Other trAb constructs are investigated in clinical studies.
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study
| 99.9 |
In an attempt to endow mAb-mediated blockade of CTLA-4 with increased specificity for tumor-reactive T cells, we examined whether trAb-induced T-cell activation and neutralization of the concomitant CTLA-4 upregulation on T cells cooperate with regard to enhanced tumor rejection and induction of an immunologic memory. A model tumor used in this paper is the B16F0-derived melanoma B78-D14, which is engineered to express GD2 . This ganglioside is a promising antigen for targeting small cell lung cancer and malignancies of neuroectodermal origin such as neuroblastoma, glioma, sarcoma or melanoma in humans [22–24]. We also included the more immunogenic melanoma B16-EpCAM , which expresses the antigen recognized by the clinically relevant trAb Catumaxomab . The constructs Surek [17, 19, 25, 26] and BiLu served as surrogate trAbs cross-linking GD2 or EpCAM, respectively, with the CD3 receptor on murine T cells.
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study
| 100.0 |
It was anticipated that the strong CD3-mediated T-cell activation induced by tumor-directed trAbs not only ignites T-cell effector functions, but also entails CTLA-4 upregulation on the surface of activated T cells. For combining anti-CTLA-4 treatment with trAb therapy, it is necessary to establish the upregulation of CTLA-4 following trAb-dependent activation. Therefore, we determined CD69 and CTLA-4 levels at different time points after in vitro incubation of T cells isolated from mouse spleens together with DCs and tumor cells (B78-D14 or B16-EpCAM) in the presence of Surek or BiLu. While the T-cell activation marker CD69 already increased by day 1, CTLA-4 expression only peaked after 48 to 72 hours (Figure 1).
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study
| 100.0 |
T cells were cultivated with DCs, irradiated B78-D14 or B16-EpCAM cells and trAb Surek or BiLu, respectively, as outlined in Materials and Methods. At different time points, surface expression of CD69 and CTLA-4 on CD4+ and CD8+ T cells was determined by FACS analyses. Mean values and standard deviations from 3 independent experiments are shown.
|
study
| 99.94 |
To examine CTLA-4 expression in vivo, a single dose of Surek was injected into mice along with irradiated B78-D14 cells. In this setting, a significant upregulation of CTLA-4 was observed after 4 days (Figure 2A). The frequency of FoxP3+ CD4+ regulatory T cells (Tregs) was also markedly increased at this time point (Figure 2B). As shown by Ki67 staining, this was likely due to enhanced Treg proliferation (Figure 2C). Interestingly, CTLA-4 upregulation on the CD4+ T cells was mainly restricted to the FoxP3+ population (Figure 2D). Since CTLA-4 mediates suppressive functions of Tregs, the data supported the concept of blocking this molecule during trAb therapy.
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study
| 100.0 |
Mice received irradiated B78-D14 cells with or without 10 μg of trAb Surek i.p. After 2 and 4 days, spleens were isolated and CD4+ T cells were phenotypically characterized. (A) Expression of CTLA-4 on CD4+ T cells. (B) Percentages of CD4+FoxP3+ cells. (C) Ki67 as a proliferation marker was stained in CD4+FoxP3+ T cells. (D) CTLA-4 upregulation is mainly restricted to the Treg population. Gating was done for CD4+ cells. At least 3 animals were included in each group. Columns indicate means and SEM. Statistics was done using the Mann-Whitney test.
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study
| 100.0 |
We then evaluated the therapeutic potential of a combined trAb/anti-CTLA-4 treatment in vivo in comparison to monotherapy. Based on previous experiments , the tumor models were adjusted to suboptimal antibody doses to secure detection of any synergisms of the combination approach. Therapy started 2 days after a lethal challenge with B78-D14 melanoma. Treatment with the anti-CTLA-4 mAb HB304 alone had only a marginal effect (Figure 3A), while monotherapy with Surek rescued up to 60% of mice bearing an established B78-D14 burden (Figure 3B). When both antibodies were combined, however, the overall survival of mice increased to 90% (Figure 3B). The data indicate that the approach combining both antibodies has a beneficial effect as compared to Surek monotherapy albeit with a significance of P = 0.08 (logrank).
|
study
| 100.0 |
Antibody treatment of mice started 2 days after challenge with 105 B78-D14 or B16-EpCAM cells. In the experiments shown, 5 to 10 mice were included. (A) Blocking of CTLA-4 alone by HB304 has only a marginal effect on tumor killing. (B) Survival of mice after therapy with Surek alone or with Surek simultaneously delivered with HB304. (C) Moderate survival benefit of mice treated with trAb BiLu and HB304 in comparison to monotherapy in the B16-EpCAM model. Significances were determined using the logrank test.
|
study
| 100.0 |
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